Knee

The concept of robotics is relatively new in medical practice. The term “robot” itself is less than 100 years old, having been first introduced to popular culture in 1917 by Joseph Capek in the science fiction story Opilec.^1,2 Robots eventually transitioned from this initial fictional literary setting to reality in 1958, when General Motors began adding automated machines to its assembly lines.¹ However, it was not until the 1980s that robotics and their exacting efficiencies would be introduced in the medical field, and it would take another decade before they would enter the specialty of orthopedics.^1-4

The first robotic-assisted orthopedic surgery was reportedly performed in 1992, when the Robodoc autonomous system was utilized for total hip arthroplasty.^2-4 A robotic system for total knee arthroplasty (TKA) was first described in 1993, but it would take several more years until a system for unicompartmental knee arthroplasty (UKA) would be commercialized and used clinically.^5,6 The rationale for advancement of robotic technology for isolated medial or lateral knee arthritis stems from the recognition that while UKA is effective and durable when components and limb are well aligned and soft tissues appropriately balanced, they are less forgiving of even slight component malalignment of as little as 2° to 3° and prone to premature loosening or wear in those circumstances.^7-13,14 In the mid 2000s, Cobb and colleagues⁶ reported using a semiautonomous robot for UKA. Since then, emergence of other semiautonomous robotic systems has led to greater market penetration and technology utilization.¹⁵

Currently, an estimated 15% to 20% of UKA surgeries are being performed with robotic assistance.¹⁶ Further, patent activity and peer-reviewed publications related to robotic technology in UKA (which can be considered surrogate measures of interest and evolving development and experience with robotic technologies) have increased dramatically over the past few years.^{2,6,14,17,18-34} To date, while the most dramatic growth of robotic utilization and case volumes has occurred in the subspecialty of UKA, semiautonomous robotic systems have been used with increasing frequency for patellofemoral and bicompartmental knee arthroplasty.^35,36 Robotics have been used sparingly for TKA, and limited to autonomous systems;^37,38 however, it is anticipated that emergence of semiautonomous platforms for TKA will further expand the role of robotics over the next decade, particularly as our focus shifts beyond component and limb alignment in TKA and more towards the role of robotics in soft tissue balancing, reduction in instrumentation and inventory and its attendant cost savings, and surgical efficiencies. One semiautonomous robotic technology first used in 2006 (Mako, Stryker) reported a 130% increase in robotic volume from 2011 to 2012; another, first used in 2013, reported growth of 480% between 2013 and 2014, due to its improved cost structure, ease of use, smaller footprint, image-free platform and applicability in ambulatory surgery centers (Navio, Smith & Nephew; data supplied by manufacturer), demonstrating the growing popularity of robotic technology.^17,39 Further, a recent analysis of potential market penetration over the next decade published by Medical Device and Diagnostic Industry (http://www.mddionline.com) projected that nearly 37% of UKAs and 23% of TKAs will be performed with robotics in 10 years.

Distinction Between Robotic-Assisted Technologies

Autonomous systems involve pre-programming the system with parameters that define the amount and orientation of bone to be removed, after which the system prepares the surfaces independent of surgeon control, other than having access to a “shutdown” switch. There are currently no autonomous robotic tools approved by the US Food and Drug Administration (FDA) for knee arthroplasty.

Semiautonomous systems involve the mapping of condylar landmarks and determination of alignment indices, which also defines the volume and orientation of bone to be removed. While the systems remove bone and cartilage within the pre-established parameters, the robotic tools are controlled and manipulated by the surgeon (Figure 1). The predetermined safe zones modulate and safeguard the surgical actions. These systems also provide real-time quantification of soft tissue balancing, which may contribute to the reported successful clinical and functional outcomes with semiautonomous systems (Figure 2).^2,4,19,22 There are several semiautonomous robotic systems that are approved for use by the FDA.

Each robotic-assisted surgery (RAS) system utilizes some sort of 3-dimensional digital map of the surgical surfaces after a process of surface mapping and landmark registration.² In the case of Mako, this planning process also requires a preoperative computed tomography (CT) scan. Over the past few years, the requirement of a CT scan has proven problematic and costly, as increasingly third-party payers and insurers are denying coverage for additional studies used for preoperative planning, leaving the burden of cost on the patients and/or hospitals. Additionally, in an era in which bundled payment arrangements are commonplace or in which providers are held accountable for costly care, the use of costly preoperative imaging is untenable. Furthermore, there is a growing concern regarding the risk of radiation exposure from CT scans that makes image-free technologies, such as Navio, an alternative for stakeholders.⁴⁰

At this time, the 2 semiautonomous systems in use for UKA employ different methods to safeguard against inadvertent bone preparation: one by providing haptic constraint beyond which movement of the bur is limited (Mako); the other by modulating the exposure or speed of the handheld robotic bur (Navio) (Figure 3).

Outcomes of RAS in UKA

Compared to conventional UKA, robotic assistance has consistently demonstrated improved surgical accuracy, even through minimally invasive incisions (Figures 4, 5).^6,20-28 Several studies have found substantial reduction in variability and error of component positioning with use of semiautonomous robotic tools.^6,21,25 In fact, precision appears to be comparable regardless of whether an image-free system or one requiring a preoperative CT scan is used (Table). Further, in addition to improving component and limb alignment, Plate and colleagues²² demonstrated that RAS-based UKA systems can help the surgeon precisely reproduce plans for soft-tissue balancing. The authors reported ligament balancing to be accurate up to .53 mm compared to the preoperative plan, with approximately 83% of cases balanced within 1 mm of the plan through a full range of flexion.²²

When evaluating advanced and novel technologies, there is undoubtedly concern that there will be increased operative time and a substantial learning curve with those technologies. Karia and colleagues³⁰ found that when inexperienced surgeons performed UKA on synthetic bone models using robotics, the mean compound rotational and translational errors were lower than when conventional techniques were used. Among those using conventional techniques, although surgical times improved during the learning period, positional inaccuracies persisted. On the other hand, robotic assistance enabled surgeons to achieve precision and accuracy when positioning UKA components irrespective of their learning experience.³⁰ Another study, by Coon,³¹ similarly suggested a shorter learning curve and greater accuracy with RAS using the Mako system compared to conventional techniques. A prospective, multicenter, observational study evaluated the operative times of 11 surgeons during their initial clinical cases using Navio robotic technology for medial UKA after a period of training using cadaver knees and sawbones.⁴¹ The learning curve for total surgical time (tracker placement to implant trial phase) indicates that it takes 8 cases to achieve 95% of total learning and maintain a steady state surgical time.

Potential Disadvantages of RAS in UKA

RAS for UKA has several potential disadvantages that must be weighed against their potential benefits. One major barrier to broader use of RAS is the increased cost associated with the technologies.^17,19,27,32 Capital and maintenance costs for these systems can be high, and those that require additional advanced imaging, such as CT scans, further challenge the return on investment.^17,19,32 In a Markov analysis of one robotic system (Mako), Moschetti and colleagues¹⁷ found that if one assumes a system cost of $1.362 million, value can be attained due to slightly better outcomes despite being more expensive than traditional methods. Nonetheless, their analysis of the Mako system estimated that each robot-assisted UKA case cost $19,219, compared to $16,476 with traditional UKA, and was associated with an incremental cost of $47,180 per quality-adjusted life-year. Their analysis further demonstrated that the cost-effectiveness was very sensitive to case volume, with lower costs realized once volumes surpassed 94 cases per year. On the other hand, costs (and thus value) will also obviously vary depending on the capital costs, annual service charges, and avoidance of unnecessary preoperative scans.¹⁹ For instance, assuming a cost of $500,000 for the image-free Navio robotic system, return on investment is achievable within 25 cases annually, roughly one-quarter of the cases necessary with the image-based system.

Another disadvantage of RAS systems in UKA is the unique complications associated with their use. Both RAS and conventional UKA can be complicated by similar problems such as component loosening, polyethylene wear, progressive arthritis, infection, stiffness, instability, and thromboembolism. RAS systems, however, carry the additional risk of specific robot-related issues.^19,27 Perhaps most notably, the pin tracts for the required optical tracking arrays can create a stress riser in the cortical bone,^19,27,33,42 highlighting the importance of inserting these pins in metaphyseal, and not diaphyseal, bone. Soft tissue complications have been reported during bone preparation with autonomous systems in total knee and hip arthroplasty;^37,38 however, the senior author (JHL) has not observed that in 1000 consecutive cases with either semiautonomous surgeon-driven robotic tool.¹⁹

Finally, systems that require a preoperative CT scan pose an increased radiation risk.⁴⁰ Ponzio and Lonner⁴⁰ recently reported that each preoperative CT scan for robotic-assisted knee arthroplasty (using a Mako protocol) is associated with a mean effective dose of radiation of 4.8 mSv, which is approximately equivalent to 48 chest radiographs.³⁴ Further, in that study, at least 25% of patients had been subjected to multiple scans, with some being exposed to cumulative effective doses of up to 103 mSv. This risk should not be considered completely negligible given that 10 mSv may be associated with an increase in the possibility of fatal cancer, and an estimated 29,000 excess cancer cases in the United States annually are reportedly caused by CT scans.^40,43,44 However, this increased radiation risk is not inherent to all RAS systems. Image-free systems, such as Navio, do not require CT scans and are thus not associated with this potential disadvantage.

Conclusion

Robotics has come a long way from its humble conceptual beginnings nearly a century ago. Rapid advances in medical technology over the past 10 years have led to the development and growing popularity of RAS in orthopedic surgery, particularly during UKA. Component placement, quantified soft tissue balance, and radiographic alignment appear to be improved and the incidence of outliers reduced with the use of RAS during UKA. Further assessment is needed to determine whether the improved alignment and balance will impact clinical function and/or durability. Early results are very promising, though, creating optimism that the full benefits of RAS in UKA will be further confirmed with additional time and research.

The concept of robotics is relatively new in medical practice. The term “robot” itself is less than 100 years old, having been first introduced to popular culture in 1917 by Joseph Capek in the science fiction story Opilec.^1,2 Robots eventually transitioned from this initial fictional literary setting to reality in 1958, when General Motors began adding automated machines to its assembly lines.¹ However, it was not until the 1980s that robotics and their exacting efficiencies would be introduced in the medical field, and it would take another decade before they would enter the specialty of orthopedics.^1-4

The first robotic-assisted orthopedic surgery was reportedly performed in 1992, when the Robodoc autonomous system was utilized for total hip arthroplasty.^2-4 A robotic system for total knee arthroplasty (TKA) was first described in 1993, but it would take several more years until a system for unicompartmental knee arthroplasty (UKA) would be commercialized and used clinically.^5,6 The rationale for advancement of robotic technology for isolated medial or lateral knee arthritis stems from the recognition that while UKA is effective and durable when components and limb are well aligned and soft tissues appropriately balanced, they are less forgiving of even slight component malalignment of as little as 2° to 3° and prone to premature loosening or wear in those circumstances.^7-13,14 In the mid 2000s, Cobb and colleagues⁶ reported using a semiautonomous robot for UKA. Since then, emergence of other semiautonomous robotic systems has led to greater market penetration and technology utilization.¹⁵

Currently, an estimated 15% to 20% of UKA surgeries are being performed with robotic assistance.¹⁶ Further, patent activity and peer-reviewed publications related to robotic technology in UKA (which can be considered surrogate measures of interest and evolving development and experience with robotic technologies) have increased dramatically over the past few years.^{2,6,14,17,18-34} To date, while the most dramatic growth of robotic utilization and case volumes has occurred in the subspecialty of UKA, semiautonomous robotic systems have been used with increasing frequency for patellofemoral and bicompartmental knee arthroplasty.^35,36 Robotics have been used sparingly for TKA, and limited to autonomous systems;^37,38 however, it is anticipated that emergence of semiautonomous platforms for TKA will further expand the role of robotics over the next decade, particularly as our focus shifts beyond component and limb alignment in TKA and more towards the role of robotics in soft tissue balancing, reduction in instrumentation and inventory and its attendant cost savings, and surgical efficiencies. One semiautonomous robotic technology first used in 2006 (Mako, Stryker) reported a 130% increase in robotic volume from 2011 to 2012; another, first used in 2013, reported growth of 480% between 2013 and 2014, due to its improved cost structure, ease of use, smaller footprint, image-free platform and applicability in ambulatory surgery centers (Navio, Smith & Nephew; data supplied by manufacturer), demonstrating the growing popularity of robotic technology.^17,39 Further, a recent analysis of potential market penetration over the next decade published by Medical Device and Diagnostic Industry (http://www.mddionline.com) projected that nearly 37% of UKAs and 23% of TKAs will be performed with robotics in 10 years.

Distinction Between Robotic-Assisted Technologies

Autonomous systems involve pre-programming the system with parameters that define the amount and orientation of bone to be removed, after which the system prepares the surfaces independent of surgeon control, other than having access to a “shutdown” switch. There are currently no autonomous robotic tools approved by the US Food and Drug Administration (FDA) for knee arthroplasty.

Semiautonomous systems involve the mapping of condylar landmarks and determination of alignment indices, which also defines the volume and orientation of bone to be removed. While the systems remove bone and cartilage within the pre-established parameters, the robotic tools are controlled and manipulated by the surgeon (Figure 1). The predetermined safe zones modulate and safeguard the surgical actions. These systems also provide real-time quantification of soft tissue balancing, which may contribute to the reported successful clinical and functional outcomes with semiautonomous systems (Figure 2).^2,4,19,22 There are several semiautonomous robotic systems that are approved for use by the FDA.

Each robotic-assisted surgery (RAS) system utilizes some sort of 3-dimensional digital map of the surgical surfaces after a process of surface mapping and landmark registration.² In the case of Mako, this planning process also requires a preoperative computed tomography (CT) scan. Over the past few years, the requirement of a CT scan has proven problematic and costly, as increasingly third-party payers and insurers are denying coverage for additional studies used for preoperative planning, leaving the burden of cost on the patients and/or hospitals. Additionally, in an era in which bundled payment arrangements are commonplace or in which providers are held accountable for costly care, the use of costly preoperative imaging is untenable. Furthermore, there is a growing concern regarding the risk of radiation exposure from CT scans that makes image-free technologies, such as Navio, an alternative for stakeholders.⁴⁰

At this time, the 2 semiautonomous systems in use for UKA employ different methods to safeguard against inadvertent bone preparation: one by providing haptic constraint beyond which movement of the bur is limited (Mako); the other by modulating the exposure or speed of the handheld robotic bur (Navio) (Figure 3).

Outcomes of RAS in UKA

Compared to conventional UKA, robotic assistance has consistently demonstrated improved surgical accuracy, even through minimally invasive incisions (Figures 4, 5).^6,20-28 Several studies have found substantial reduction in variability and error of component positioning with use of semiautonomous robotic tools.^6,21,25 In fact, precision appears to be comparable regardless of whether an image-free system or one requiring a preoperative CT scan is used (Table). Further, in addition to improving component and limb alignment, Plate and colleagues²² demonstrated that RAS-based UKA systems can help the surgeon precisely reproduce plans for soft-tissue balancing. The authors reported ligament balancing to be accurate up to .53 mm compared to the preoperative plan, with approximately 83% of cases balanced within 1 mm of the plan through a full range of flexion.²²

When evaluating advanced and novel technologies, there is undoubtedly concern that there will be increased operative time and a substantial learning curve with those technologies. Karia and colleagues³⁰ found that when inexperienced surgeons performed UKA on synthetic bone models using robotics, the mean compound rotational and translational errors were lower than when conventional techniques were used. Among those using conventional techniques, although surgical times improved during the learning period, positional inaccuracies persisted. On the other hand, robotic assistance enabled surgeons to achieve precision and accuracy when positioning UKA components irrespective of their learning experience.³⁰ Another study, by Coon,³¹ similarly suggested a shorter learning curve and greater accuracy with RAS using the Mako system compared to conventional techniques. A prospective, multicenter, observational study evaluated the operative times of 11 surgeons during their initial clinical cases using Navio robotic technology for medial UKA after a period of training using cadaver knees and sawbones.⁴¹ The learning curve for total surgical time (tracker placement to implant trial phase) indicates that it takes 8 cases to achieve 95% of total learning and maintain a steady state surgical time.

Potential Disadvantages of RAS in UKA

RAS for UKA has several potential disadvantages that must be weighed against their potential benefits. One major barrier to broader use of RAS is the increased cost associated with the technologies.^17,19,27,32 Capital and maintenance costs for these systems can be high, and those that require additional advanced imaging, such as CT scans, further challenge the return on investment.^17,19,32 In a Markov analysis of one robotic system (Mako), Moschetti and colleagues¹⁷ found that if one assumes a system cost of $1.362 million, value can be attained due to slightly better outcomes despite being more expensive than traditional methods. Nonetheless, their analysis of the Mako system estimated that each robot-assisted UKA case cost $19,219, compared to $16,476 with traditional UKA, and was associated with an incremental cost of $47,180 per quality-adjusted life-year. Their analysis further demonstrated that the cost-effectiveness was very sensitive to case volume, with lower costs realized once volumes surpassed 94 cases per year. On the other hand, costs (and thus value) will also obviously vary depending on the capital costs, annual service charges, and avoidance of unnecessary preoperative scans.¹⁹ For instance, assuming a cost of $500,000 for the image-free Navio robotic system, return on investment is achievable within 25 cases annually, roughly one-quarter of the cases necessary with the image-based system.

Another disadvantage of RAS systems in UKA is the unique complications associated with their use. Both RAS and conventional UKA can be complicated by similar problems such as component loosening, polyethylene wear, progressive arthritis, infection, stiffness, instability, and thromboembolism. RAS systems, however, carry the additional risk of specific robot-related issues.^19,27 Perhaps most notably, the pin tracts for the required optical tracking arrays can create a stress riser in the cortical bone,^19,27,33,42 highlighting the importance of inserting these pins in metaphyseal, and not diaphyseal, bone. Soft tissue complications have been reported during bone preparation with autonomous systems in total knee and hip arthroplasty;^37,38 however, the senior author (JHL) has not observed that in 1000 consecutive cases with either semiautonomous surgeon-driven robotic tool.¹⁹

Finally, systems that require a preoperative CT scan pose an increased radiation risk.⁴⁰ Ponzio and Lonner⁴⁰ recently reported that each preoperative CT scan for robotic-assisted knee arthroplasty (using a Mako protocol) is associated with a mean effective dose of radiation of 4.8 mSv, which is approximately equivalent to 48 chest radiographs.³⁴ Further, in that study, at least 25% of patients had been subjected to multiple scans, with some being exposed to cumulative effective doses of up to 103 mSv. This risk should not be considered completely negligible given that 10 mSv may be associated with an increase in the possibility of fatal cancer, and an estimated 29,000 excess cancer cases in the United States annually are reportedly caused by CT scans.^40,43,44 However, this increased radiation risk is not inherent to all RAS systems. Image-free systems, such as Navio, do not require CT scans and are thus not associated with this potential disadvantage.

Conclusion

Robotics has come a long way from its humble conceptual beginnings nearly a century ago. Rapid advances in medical technology over the past 10 years have led to the development and growing popularity of RAS in orthopedic surgery, particularly during UKA. Component placement, quantified soft tissue balance, and radiographic alignment appear to be improved and the incidence of outliers reduced with the use of RAS during UKA. Further assessment is needed to determine whether the improved alignment and balance will impact clinical function and/or durability. Early results are very promising, though, creating optimism that the full benefits of RAS in UKA will be further confirmed with additional time and research.

The concept of robotics is relatively new in medical practice. The term “robot” itself is less than 100 years old, having been first introduced to popular culture in 1917 by Joseph Capek in the science fiction story Opilec.^1,2 Robots eventually transitioned from this initial fictional literary setting to reality in 1958, when General Motors began adding automated machines to its assembly lines.¹ However, it was not until the 1980s that robotics and their exacting efficiencies would be introduced in the medical field, and it would take another decade before they would enter the specialty of orthopedics.^1-4

The first robotic-assisted orthopedic surgery was reportedly performed in 1992, when the Robodoc autonomous system was utilized for total hip arthroplasty.^2-4 A robotic system for total knee arthroplasty (TKA) was first described in 1993, but it would take several more years until a system for unicompartmental knee arthroplasty (UKA) would be commercialized and used clinically.^5,6 The rationale for advancement of robotic technology for isolated medial or lateral knee arthritis stems from the recognition that while UKA is effective and durable when components and limb are well aligned and soft tissues appropriately balanced, they are less forgiving of even slight component malalignment of as little as 2° to 3° and prone to premature loosening or wear in those circumstances.^7-13,14 In the mid 2000s, Cobb and colleagues⁶ reported using a semiautonomous robot for UKA. Since then, emergence of other semiautonomous robotic systems has led to greater market penetration and technology utilization.¹⁵

Currently, an estimated 15% to 20% of UKA surgeries are being performed with robotic assistance.¹⁶ Further, patent activity and peer-reviewed publications related to robotic technology in UKA (which can be considered surrogate measures of interest and evolving development and experience with robotic technologies) have increased dramatically over the past few years.^{2,6,14,17,18-34} To date, while the most dramatic growth of robotic utilization and case volumes has occurred in the subspecialty of UKA, semiautonomous robotic systems have been used with increasing frequency for patellofemoral and bicompartmental knee arthroplasty.^35,36 Robotics have been used sparingly for TKA, and limited to autonomous systems;^37,38 however, it is anticipated that emergence of semiautonomous platforms for TKA will further expand the role of robotics over the next decade, particularly as our focus shifts beyond component and limb alignment in TKA and more towards the role of robotics in soft tissue balancing, reduction in instrumentation and inventory and its attendant cost savings, and surgical efficiencies. One semiautonomous robotic technology first used in 2006 (Mako, Stryker) reported a 130% increase in robotic volume from 2011 to 2012; another, first used in 2013, reported growth of 480% between 2013 and 2014, due to its improved cost structure, ease of use, smaller footprint, image-free platform and applicability in ambulatory surgery centers (Navio, Smith & Nephew; data supplied by manufacturer), demonstrating the growing popularity of robotic technology.^17,39 Further, a recent analysis of potential market penetration over the next decade published by Medical Device and Diagnostic Industry (http://www.mddionline.com) projected that nearly 37% of UKAs and 23% of TKAs will be performed with robotics in 10 years.

Distinction Between Robotic-Assisted Technologies

Autonomous systems involve pre-programming the system with parameters that define the amount and orientation of bone to be removed, after which the system prepares the surfaces independent of surgeon control, other than having access to a “shutdown” switch. There are currently no autonomous robotic tools approved by the US Food and Drug Administration (FDA) for knee arthroplasty.

Semiautonomous systems involve the mapping of condylar landmarks and determination of alignment indices, which also defines the volume and orientation of bone to be removed. While the systems remove bone and cartilage within the pre-established parameters, the robotic tools are controlled and manipulated by the surgeon (Figure 1). The predetermined safe zones modulate and safeguard the surgical actions. These systems also provide real-time quantification of soft tissue balancing, which may contribute to the reported successful clinical and functional outcomes with semiautonomous systems (Figure 2).^2,4,19,22 There are several semiautonomous robotic systems that are approved for use by the FDA.

Each robotic-assisted surgery (RAS) system utilizes some sort of 3-dimensional digital map of the surgical surfaces after a process of surface mapping and landmark registration.² In the case of Mako, this planning process also requires a preoperative computed tomography (CT) scan. Over the past few years, the requirement of a CT scan has proven problematic and costly, as increasingly third-party payers and insurers are denying coverage for additional studies used for preoperative planning, leaving the burden of cost on the patients and/or hospitals. Additionally, in an era in which bundled payment arrangements are commonplace or in which providers are held accountable for costly care, the use of costly preoperative imaging is untenable. Furthermore, there is a growing concern regarding the risk of radiation exposure from CT scans that makes image-free technologies, such as Navio, an alternative for stakeholders.⁴⁰

At this time, the 2 semiautonomous systems in use for UKA employ different methods to safeguard against inadvertent bone preparation: one by providing haptic constraint beyond which movement of the bur is limited (Mako); the other by modulating the exposure or speed of the handheld robotic bur (Navio) (Figure 3).

Outcomes of RAS in UKA

Compared to conventional UKA, robotic assistance has consistently demonstrated improved surgical accuracy, even through minimally invasive incisions (Figures 4, 5).^6,20-28 Several studies have found substantial reduction in variability and error of component positioning with use of semiautonomous robotic tools.^6,21,25 In fact, precision appears to be comparable regardless of whether an image-free system or one requiring a preoperative CT scan is used (Table). Further, in addition to improving component and limb alignment, Plate and colleagues²² demonstrated that RAS-based UKA systems can help the surgeon precisely reproduce plans for soft-tissue balancing. The authors reported ligament balancing to be accurate up to .53 mm compared to the preoperative plan, with approximately 83% of cases balanced within 1 mm of the plan through a full range of flexion.²²

When evaluating advanced and novel technologies, there is undoubtedly concern that there will be increased operative time and a substantial learning curve with those technologies. Karia and colleagues³⁰ found that when inexperienced surgeons performed UKA on synthetic bone models using robotics, the mean compound rotational and translational errors were lower than when conventional techniques were used. Among those using conventional techniques, although surgical times improved during the learning period, positional inaccuracies persisted. On the other hand, robotic assistance enabled surgeons to achieve precision and accuracy when positioning UKA components irrespective of their learning experience.³⁰ Another study, by Coon,³¹ similarly suggested a shorter learning curve and greater accuracy with RAS using the Mako system compared to conventional techniques. A prospective, multicenter, observational study evaluated the operative times of 11 surgeons during their initial clinical cases using Navio robotic technology for medial UKA after a period of training using cadaver knees and sawbones.⁴¹ The learning curve for total surgical time (tracker placement to implant trial phase) indicates that it takes 8 cases to achieve 95% of total learning and maintain a steady state surgical time.

Potential Disadvantages of RAS in UKA

RAS for UKA has several potential disadvantages that must be weighed against their potential benefits. One major barrier to broader use of RAS is the increased cost associated with the technologies.^17,19,27,32 Capital and maintenance costs for these systems can be high, and those that require additional advanced imaging, such as CT scans, further challenge the return on investment.^17,19,32 In a Markov analysis of one robotic system (Mako), Moschetti and colleagues¹⁷ found that if one assumes a system cost of $1.362 million, value can be attained due to slightly better outcomes despite being more expensive than traditional methods. Nonetheless, their analysis of the Mako system estimated that each robot-assisted UKA case cost $19,219, compared to $16,476 with traditional UKA, and was associated with an incremental cost of $47,180 per quality-adjusted life-year. Their analysis further demonstrated that the cost-effectiveness was very sensitive to case volume, with lower costs realized once volumes surpassed 94 cases per year. On the other hand, costs (and thus value) will also obviously vary depending on the capital costs, annual service charges, and avoidance of unnecessary preoperative scans.¹⁹ For instance, assuming a cost of $500,000 for the image-free Navio robotic system, return on investment is achievable within 25 cases annually, roughly one-quarter of the cases necessary with the image-based system.

Another disadvantage of RAS systems in UKA is the unique complications associated with their use. Both RAS and conventional UKA can be complicated by similar problems such as component loosening, polyethylene wear, progressive arthritis, infection, stiffness, instability, and thromboembolism. RAS systems, however, carry the additional risk of specific robot-related issues.^19,27 Perhaps most notably, the pin tracts for the required optical tracking arrays can create a stress riser in the cortical bone,^19,27,33,42 highlighting the importance of inserting these pins in metaphyseal, and not diaphyseal, bone. Soft tissue complications have been reported during bone preparation with autonomous systems in total knee and hip arthroplasty;^37,38 however, the senior author (JHL) has not observed that in 1000 consecutive cases with either semiautonomous surgeon-driven robotic tool.¹⁹

Finally, systems that require a preoperative CT scan pose an increased radiation risk.⁴⁰ Ponzio and Lonner⁴⁰ recently reported that each preoperative CT scan for robotic-assisted knee arthroplasty (using a Mako protocol) is associated with a mean effective dose of radiation of 4.8 mSv, which is approximately equivalent to 48 chest radiographs.³⁴ Further, in that study, at least 25% of patients had been subjected to multiple scans, with some being exposed to cumulative effective doses of up to 103 mSv. This risk should not be considered completely negligible given that 10 mSv may be associated with an increase in the possibility of fatal cancer, and an estimated 29,000 excess cancer cases in the United States annually are reportedly caused by CT scans.^40,43,44 However, this increased radiation risk is not inherent to all RAS systems. Image-free systems, such as Navio, do not require CT scans and are thus not associated with this potential disadvantage.

Conclusion

Robotics has come a long way from its humble conceptual beginnings nearly a century ago. Rapid advances in medical technology over the past 10 years have led to the development and growing popularity of RAS in orthopedic surgery, particularly during UKA. Component placement, quantified soft tissue balance, and radiographic alignment appear to be improved and the incidence of outliers reduced with the use of RAS during UKA. Further assessment is needed to determine whether the improved alignment and balance will impact clinical function and/or durability. Early results are very promising, though, creating optimism that the full benefits of RAS in UKA will be further confirmed with additional time and research.

Total knee arthroplasty (TKA) continues to be a widely utilized treatment option for end-stage knee osteoarthritis, and the number of patients undergoing TKA is projected to continually increase over the next decade.¹ Although TKA is highly successful for many patients, studies continue to report that approximately 20% of patients are dissatisfied after undergoing TKA, and nearly 25% of knee revisions are performed for instability or malalignment.^2,3 Technological advances have been developed to help improve clinical outcomes and implant survivorship. Over the past decade, computer navigation and intraoperative guides have been introduced to help control surgical variables and overcome the limitations and inaccuracies of traditional mechanical instrumentation. Currently, there are a variety of technologies available to assist surgeons with component alignment, including extramedullary devices, computer-assisted navigation systems (CAS), and patient-specific instrumentation (PSI) that help achieve desired alignment goals.^4,5

Computer-assisted navigation tools were introduced in an effort to improve implant alignment and clinical outcomes compared to traditional mechanical guides. Some argue that the use of computer-assisted surgery has a steep learning curve and successful use is dependent on the user’s experience; however, studies have suggested computer-assisted surgery may allow less experienced surgeons to reliably achieve anticipated intraoperative alignment goals with a low complication rate.^6,7 Various studies have looked at computer-assisted TKA at short to mid-term follow-up, but few studies have reported long-term outcomes.^6-9 de Steiger and colleagues¹⁰ recently found that computer-assisted TKA reduced the overall revision rate for aseptic loosening following TKA in patients younger than age 65 years, which suggests benefit of CAS for younger patients. Short-term follow-up has also shown the benefit of CAS TKA in patients with severe extra-articular deformity, where traditional instrumentation cannot be utilized.¹¹ Currently, there is no consensus that computer-assisted TKA leads to improved postoperative patient reported outcomes, because many studies are limited by study design or small cohorts; however, current literature does show an improvement in component alignment as compared to mechanical instrumentation.^9,12,13 As future implant and position targets are defined to improve implant survivorship and clinical outcomes in total joint arthroplasty, computer-assisted devices will be useful to help achieve more precise and accurate component positioning.

In addition to CAS devices, some companies have sought to improve TKA surgery by introducing PSI. PSI was introduced to improve component alignment in TKA, with the purported advantages of a shorter surgical time, decrease in the number of instruments needed, and improved clinical outcomes. PSI accuracy remains variable, which may be attributed to the various systems and implant designs in each study.^14-17 In addition, advanced preoperative imaging is necessary, which further adds to the overall cost.¹⁷ While the recent advancement in technology may provide decreased costs at the time of surgery, the increased cost and time incurred by the patient preoperatively has not resulted in significantly better clinical outcomes.^18,19 Additionally, recent work has not shown PSI to have superior accuracy as compared to currently available CAS devices.¹⁴ These findings suggest that the additional cost and time incurred by patients may limit the widespread use of PSI.

Although computer navigation has been shown to be more accurate than conventional instrumentation and PSI, the lack of improvement in long-term clinical outcome data has limited its use. In a meta-analysis, Bauwens and colleagues²⁰ suggested that while navigated TKAs have improved component alignment outcomes as compared to conventional surgery, the clinical benefit remains unclear. Less than 5% of surgeons are currently using navigation systems due to the perceived learning curve, cost, additional surgical time, and imaging required to utilize these systems. Certain navigation systems can be seemingly cumbersome, with large consoles, increased number of instruments required, and optical instruments with line-of-sight issues. Recent technological advances have worked to decrease this challenge by using accelerometer- and gyroscope-based electronic components, which combine the accuracy of computer-assisted technology with the ease of use of mechanical guides.

Accelerometer and gyroscope technology systems, such as the iAssist system, are portable devices that do not require a large computer console or navigation arrays. This technology relies on accelerator-based navigation without additional preoperative imaging. A recent study demonstrated the iAssist had reproducible accuracy in component alignment that could be easily incorporated into the operating room without optical trackers.²¹ The use of portable computer-assisted devices provides a more compact and easily accessible technology that can be used to achieve accurate component alignment without additional large equipment in the operating room.²² These new handheld intraoperative tools have been introduced to place implants according to a preoperative plan in order to minimize failure due to preoperative extra-articular deformity or intraoperative technical miscues.²³ Nam and colleagues²⁴ used an accelerometer-based surgical navigation system to perform tibial resections in cadaveric models, and found that the accelerometer-based guide was accurate for tibial resection in both the coronal and sagittal planes. In a prospective randomized controlled trial evaluating 100 patients undergoing a TKA using either an accelerometer-based guide or conventional alignment methods, the authors showed that the accelerometer-based guide decreased outliers in tibial component alignment compared to conventional guides.²⁵ In the accelerometer-based guide cohort, 95.7% of tibial components were within 2° of perpendicular to the tibial mechanical axis, compared to 68.1% in the conventional group (P < .001). These results suggested that portable accelerometer-based navigation allows surgeons to achieve satisfactory tibial component alignment with a decrease in the number of potential outliers.^24,25 Similarly, Bugbee and colleagues²⁶ found that accelerometer-based handheld navigation was accurate for tibial coronal and sagittal alignment and no additional surgical time was required compared to conventional techniques.

The relationship between knee alignment and clinical outcomes for TKA remains controversial. Regardless of the surgeon’s alignment preference, it is important to reliably and accurately execute the preoperative plan in a reproducible fashion. Advances in technology that assist with intraoperative component alignment can be useful, and may help decrease the incidence of implant malalignment in clinical practice.

Preoperative Planning and Intraoperative Technique

Preoperative planning is carried out in a manner identical to the use of conventional mechanical guides. Long leg films are taken for evaluation of overall limb alignment, and calibrated lateral images are taken for templating implant sizes. Lines are drawn on the images to determine the difference between the mechanical and anatomic axis of the femur, and a line drawn perpendicular to the mechanical axis is placed to show the expected bone cut. In similar fashion a perpendicular line to the tibial mechanical axis is also drawn to show the expected tibial resection. This preoperative plan allows the surgeon to have an additional intraoperative guide to ensure accuracy of the computer-assisted device.

After standard exposure, the distal femoral or proximal tibial cut can be made based on surgeon preference. The system being demonstrated in the accompanying photos is the KneeAlign 2 system (OrthAlign).

Distal Femoral Cut

The KneeAlign 2 femoral cutting guide is attached to the distal femur with a central pin that is placed in the middle of the distal femur measured from medial to lateral, and 1 cm anterior to the intercondylar notch. It is important to note that this spot is often more medial than traditionally used for insertion of an intramedullary rod. This central point sets the distal point of the femoral mechanical axis. The device is then held in place with 2 oblique pins, and is solidly fixed to the bone. Using a rotating motion, the femur is rotated around the hip joint. The accelerometer and gyroscope in the unit are able to determine the center of the hip joint from this motion, creating the proximal point of the mechanical axis of the femur. Once the mechanical axis of the femur is determined, varus/valgus and flexion/extension can be adjusted on the guide. One adjustment screw is available for varus/valgus, and a second is available for flexion/extension. Numbers on the device screen show real-time alignment, and are easily adjusted to set the desired alignment (Figure 1). Once alignment is obtained, a mechanical stylus is used to determine depth of resection, and the distal femoral cutting block is pinned. After pinning the block, the 3 pins in the device are removed, and the device is removed from the bone. This leaves only the distal femoral cutting block in place. In experienced hands, this part of the procedure takes less than 3 minutes.

Proximal Tibial Cut

The KneeAlign 2 proximal tibial guide is similar in appearance to a standard mechanical tibial cutting guide. It is attached to the proximal tibia with a spring around the calf and 2 pins that hold the device aligned with the medial third of the tibial tubercle. A stylus is then centered on the anterior cruciate ligament (ACL) footprint, which sets the proximal mechanical axis point of the tibia (Figure 2). An offset number is read off the stylus on the ACL footprint, and this number is matched on the ankle offset portion of the guide. The device has 2 sensors. One sensor is on the chassis of the device, and the other is on a mobile arm. Movements between the 2 are monitored by the accelerometers, allowing for accurate maintenance of alignment position even with motion in the leg. A point is taken from the lateral malleolus and then a second point is taken from the medial malleolus. These points are used to determine the center of the ankle joint, which sets the distal mechanical axis point. Once mechanical axis of the tibia is determined, the tibial cutting guide is pinned in place, and can be adjusted with real-time guidance of the varus/valgus and posterior slope values seen on the device (Figure 3). Cut depth is once again determined with a mechanical stylus.

Limitations

Although these devices have proven to be very accurate, surgeons must continue to recognize that all tools can have errors. With computerized guides of any sort, these errors are usually user errors that cannot be detected by the device. Surgeons need to be able to recognize this and always double-check bone cuts for accuracy. Templating the bone cuts prior to surgery is an effective double-check. In addition, many handheld accelerometer devices do not currently assist with the rotational alignment of the femoral component. This is still performed using the surgeon’s preferred technique, and is a limitation of these systems.

Discussion

Currently, TKA provides satisfactory 10-year results with modern implant designs and survival rates as high as 90% to 95%.^27,28 Even with good survival rates, a percentage of patients fail within the first 5 years.³ At a single institution, 50% of revision TKAs were related to instability, malalignment, or failure of fixation that occurred less than 2 years after the index procedure.²⁹ In general, TKA with mechanical instrumentation provides satisfactory pain relief and postoperative knee function; however, studies have consistently shown that the use of advanced technology decreases the risk of implant malalignment, which may decrease early implant failure rates as compared to mechanical and some PSI.^13,14,22 While there is a paucity of literature that has shown better clinical outcomes with the use of advanced technology, there are studies supporting the notion that proper limb alignment and component positioning improves implant survivorship.^23,30

CAS may have additional advantages if the surgeon chooses to place the TKA in an alignment other than a neutral mechanical axis. Kinematic alignment for TKA has gained increasing popularity, where the target of a neutral mechanical axis alignment is not always the goal.^31,32 The reported benefit is a more natural ligament tension with the hope of improving patient satisfaction. One concern with this technique is that it is a departure from the long-held teaching that a TKA aligned to a neutral mechanical axis is necessary for long-term implant survivorship.^33,34 In addition, if the goal of surgery is to cut the tibia and femur at a specific varus/valgus cut, standard instrumentation may not allow for this level of accuracy. This in turn increases the risk of having a tibial or femoral cut that is outside the commonly accepted standards of alignment, which may lead to early implant failure. If further research suggests alignment is a variable that differs from patient to patient, the use of precise tools to ensure accuracy of executing the preoperatively templated alignment becomes even more important.

As the number of TKAs continues to rise each year, even a small percentage of malaligned knees that go on to revision surgery will create a large burden on the healthcare system.^1,3 Although the short-term clinical benefits of CAS have not shown substantial differences as compared to conventional TKA, the number of knees aligned outside of a desired neutral mechanical axis alignment has been shown in multiple studies to be decreased with the use of advanced technology.^7,12,34 Although CAS is an additional cost to a primary TKA, if the orthopedic community can decrease the number of TKA revisions due to malalignment from 6.6% to nearly zero, this may decrease the revision burden and overall cost to the healthcare system.^1,3

TKA technology continues to evolve, and we must continue to assess each new advance not only to understand how it works, but also to ensure it addresses a specific clinical problem, and to be aware of the costs associated before incorporating it into routine practice. Some argue that the use of advanced technology requires increased surgical time, which in turn ultimately increases costs; however, one study has documented no increase in surgical time with handheld navigation while maintaining the accuracy of the device.³⁴ In addition, no significant radiographic or clinical differences have been found between handheld navigation and larger console CAS systems, but large console systems have been associated with increased surgical times.²² The use of handheld accelerometer- and gyroscope-based guides has proven to provide reliable coronal and sagittal implant alignment that can easily be incorporated into the operating room. More widespread use of such technology will help decrease alignment outliers for TKA, and future long-term clinical outcome studies will be necessary to assess functional outcomes.

Conclusion

Advanced computer based technology offers an additional tool to the surgeon for reliably improving component positioning during TKA. The use of handheld accelerometer- and gyroscope-based guides increases the accuracy of component placement while decreasing the incidence of outliers compared to standard mechanical guides, without the need for a large computer console. Long-term radiographic and patient-reported outcomes are necessary to further validate these devices.

Total knee arthroplasty (TKA) continues to be a widely utilized treatment option for end-stage knee osteoarthritis, and the number of patients undergoing TKA is projected to continually increase over the next decade.¹ Although TKA is highly successful for many patients, studies continue to report that approximately 20% of patients are dissatisfied after undergoing TKA, and nearly 25% of knee revisions are performed for instability or malalignment.^2,3 Technological advances have been developed to help improve clinical outcomes and implant survivorship. Over the past decade, computer navigation and intraoperative guides have been introduced to help control surgical variables and overcome the limitations and inaccuracies of traditional mechanical instrumentation. Currently, there are a variety of technologies available to assist surgeons with component alignment, including extramedullary devices, computer-assisted navigation systems (CAS), and patient-specific instrumentation (PSI) that help achieve desired alignment goals.^4,5

Computer-assisted navigation tools were introduced in an effort to improve implant alignment and clinical outcomes compared to traditional mechanical guides. Some argue that the use of computer-assisted surgery has a steep learning curve and successful use is dependent on the user’s experience; however, studies have suggested computer-assisted surgery may allow less experienced surgeons to reliably achieve anticipated intraoperative alignment goals with a low complication rate.^6,7 Various studies have looked at computer-assisted TKA at short to mid-term follow-up, but few studies have reported long-term outcomes.^6-9 de Steiger and colleagues¹⁰ recently found that computer-assisted TKA reduced the overall revision rate for aseptic loosening following TKA in patients younger than age 65 years, which suggests benefit of CAS for younger patients. Short-term follow-up has also shown the benefit of CAS TKA in patients with severe extra-articular deformity, where traditional instrumentation cannot be utilized.¹¹ Currently, there is no consensus that computer-assisted TKA leads to improved postoperative patient reported outcomes, because many studies are limited by study design or small cohorts; however, current literature does show an improvement in component alignment as compared to mechanical instrumentation.^9,12,13 As future implant and position targets are defined to improve implant survivorship and clinical outcomes in total joint arthroplasty, computer-assisted devices will be useful to help achieve more precise and accurate component positioning.

In addition to CAS devices, some companies have sought to improve TKA surgery by introducing PSI. PSI was introduced to improve component alignment in TKA, with the purported advantages of a shorter surgical time, decrease in the number of instruments needed, and improved clinical outcomes. PSI accuracy remains variable, which may be attributed to the various systems and implant designs in each study.^14-17 In addition, advanced preoperative imaging is necessary, which further adds to the overall cost.¹⁷ While the recent advancement in technology may provide decreased costs at the time of surgery, the increased cost and time incurred by the patient preoperatively has not resulted in significantly better clinical outcomes.^18,19 Additionally, recent work has not shown PSI to have superior accuracy as compared to currently available CAS devices.¹⁴ These findings suggest that the additional cost and time incurred by patients may limit the widespread use of PSI.

Although computer navigation has been shown to be more accurate than conventional instrumentation and PSI, the lack of improvement in long-term clinical outcome data has limited its use. In a meta-analysis, Bauwens and colleagues²⁰ suggested that while navigated TKAs have improved component alignment outcomes as compared to conventional surgery, the clinical benefit remains unclear. Less than 5% of surgeons are currently using navigation systems due to the perceived learning curve, cost, additional surgical time, and imaging required to utilize these systems. Certain navigation systems can be seemingly cumbersome, with large consoles, increased number of instruments required, and optical instruments with line-of-sight issues. Recent technological advances have worked to decrease this challenge by using accelerometer- and gyroscope-based electronic components, which combine the accuracy of computer-assisted technology with the ease of use of mechanical guides.

Accelerometer and gyroscope technology systems, such as the iAssist system, are portable devices that do not require a large computer console or navigation arrays. This technology relies on accelerator-based navigation without additional preoperative imaging. A recent study demonstrated the iAssist had reproducible accuracy in component alignment that could be easily incorporated into the operating room without optical trackers.²¹ The use of portable computer-assisted devices provides a more compact and easily accessible technology that can be used to achieve accurate component alignment without additional large equipment in the operating room.²² These new handheld intraoperative tools have been introduced to place implants according to a preoperative plan in order to minimize failure due to preoperative extra-articular deformity or intraoperative technical miscues.²³ Nam and colleagues²⁴ used an accelerometer-based surgical navigation system to perform tibial resections in cadaveric models, and found that the accelerometer-based guide was accurate for tibial resection in both the coronal and sagittal planes. In a prospective randomized controlled trial evaluating 100 patients undergoing a TKA using either an accelerometer-based guide or conventional alignment methods, the authors showed that the accelerometer-based guide decreased outliers in tibial component alignment compared to conventional guides.²⁵ In the accelerometer-based guide cohort, 95.7% of tibial components were within 2° of perpendicular to the tibial mechanical axis, compared to 68.1% in the conventional group (P < .001). These results suggested that portable accelerometer-based navigation allows surgeons to achieve satisfactory tibial component alignment with a decrease in the number of potential outliers.^24,25 Similarly, Bugbee and colleagues²⁶ found that accelerometer-based handheld navigation was accurate for tibial coronal and sagittal alignment and no additional surgical time was required compared to conventional techniques.

The relationship between knee alignment and clinical outcomes for TKA remains controversial. Regardless of the surgeon’s alignment preference, it is important to reliably and accurately execute the preoperative plan in a reproducible fashion. Advances in technology that assist with intraoperative component alignment can be useful, and may help decrease the incidence of implant malalignment in clinical practice.

Preoperative Planning and Intraoperative Technique

Preoperative planning is carried out in a manner identical to the use of conventional mechanical guides. Long leg films are taken for evaluation of overall limb alignment, and calibrated lateral images are taken for templating implant sizes. Lines are drawn on the images to determine the difference between the mechanical and anatomic axis of the femur, and a line drawn perpendicular to the mechanical axis is placed to show the expected bone cut. In similar fashion a perpendicular line to the tibial mechanical axis is also drawn to show the expected tibial resection. This preoperative plan allows the surgeon to have an additional intraoperative guide to ensure accuracy of the computer-assisted device.

After standard exposure, the distal femoral or proximal tibial cut can be made based on surgeon preference. The system being demonstrated in the accompanying photos is the KneeAlign 2 system (OrthAlign).

Distal Femoral Cut

The KneeAlign 2 femoral cutting guide is attached to the distal femur with a central pin that is placed in the middle of the distal femur measured from medial to lateral, and 1 cm anterior to the intercondylar notch. It is important to note that this spot is often more medial than traditionally used for insertion of an intramedullary rod. This central point sets the distal point of the femoral mechanical axis. The device is then held in place with 2 oblique pins, and is solidly fixed to the bone. Using a rotating motion, the femur is rotated around the hip joint. The accelerometer and gyroscope in the unit are able to determine the center of the hip joint from this motion, creating the proximal point of the mechanical axis of the femur. Once the mechanical axis of the femur is determined, varus/valgus and flexion/extension can be adjusted on the guide. One adjustment screw is available for varus/valgus, and a second is available for flexion/extension. Numbers on the device screen show real-time alignment, and are easily adjusted to set the desired alignment (Figure 1). Once alignment is obtained, a mechanical stylus is used to determine depth of resection, and the distal femoral cutting block is pinned. After pinning the block, the 3 pins in the device are removed, and the device is removed from the bone. This leaves only the distal femoral cutting block in place. In experienced hands, this part of the procedure takes less than 3 minutes.

Proximal Tibial Cut

The KneeAlign 2 proximal tibial guide is similar in appearance to a standard mechanical tibial cutting guide. It is attached to the proximal tibia with a spring around the calf and 2 pins that hold the device aligned with the medial third of the tibial tubercle. A stylus is then centered on the anterior cruciate ligament (ACL) footprint, which sets the proximal mechanical axis point of the tibia (Figure 2). An offset number is read off the stylus on the ACL footprint, and this number is matched on the ankle offset portion of the guide. The device has 2 sensors. One sensor is on the chassis of the device, and the other is on a mobile arm. Movements between the 2 are monitored by the accelerometers, allowing for accurate maintenance of alignment position even with motion in the leg. A point is taken from the lateral malleolus and then a second point is taken from the medial malleolus. These points are used to determine the center of the ankle joint, which sets the distal mechanical axis point. Once mechanical axis of the tibia is determined, the tibial cutting guide is pinned in place, and can be adjusted with real-time guidance of the varus/valgus and posterior slope values seen on the device (Figure 3). Cut depth is once again determined with a mechanical stylus.

Limitations

Although these devices have proven to be very accurate, surgeons must continue to recognize that all tools can have errors. With computerized guides of any sort, these errors are usually user errors that cannot be detected by the device. Surgeons need to be able to recognize this and always double-check bone cuts for accuracy. Templating the bone cuts prior to surgery is an effective double-check. In addition, many handheld accelerometer devices do not currently assist with the rotational alignment of the femoral component. This is still performed using the surgeon’s preferred technique, and is a limitation of these systems.

Discussion

Currently, TKA provides satisfactory 10-year results with modern implant designs and survival rates as high as 90% to 95%.^27,28 Even with good survival rates, a percentage of patients fail within the first 5 years.³ At a single institution, 50% of revision TKAs were related to instability, malalignment, or failure of fixation that occurred less than 2 years after the index procedure.²⁹ In general, TKA with mechanical instrumentation provides satisfactory pain relief and postoperative knee function; however, studies have consistently shown that the use of advanced technology decreases the risk of implant malalignment, which may decrease early implant failure rates as compared to mechanical and some PSI.^13,14,22 While there is a paucity of literature that has shown better clinical outcomes with the use of advanced technology, there are studies supporting the notion that proper limb alignment and component positioning improves implant survivorship.^23,30

CAS may have additional advantages if the surgeon chooses to place the TKA in an alignment other than a neutral mechanical axis. Kinematic alignment for TKA has gained increasing popularity, where the target of a neutral mechanical axis alignment is not always the goal.^31,32 The reported benefit is a more natural ligament tension with the hope of improving patient satisfaction. One concern with this technique is that it is a departure from the long-held teaching that a TKA aligned to a neutral mechanical axis is necessary for long-term implant survivorship.^33,34 In addition, if the goal of surgery is to cut the tibia and femur at a specific varus/valgus cut, standard instrumentation may not allow for this level of accuracy. This in turn increases the risk of having a tibial or femoral cut that is outside the commonly accepted standards of alignment, which may lead to early implant failure. If further research suggests alignment is a variable that differs from patient to patient, the use of precise tools to ensure accuracy of executing the preoperatively templated alignment becomes even more important.

As the number of TKAs continues to rise each year, even a small percentage of malaligned knees that go on to revision surgery will create a large burden on the healthcare system.^1,3 Although the short-term clinical benefits of CAS have not shown substantial differences as compared to conventional TKA, the number of knees aligned outside of a desired neutral mechanical axis alignment has been shown in multiple studies to be decreased with the use of advanced technology.^7,12,34 Although CAS is an additional cost to a primary TKA, if the orthopedic community can decrease the number of TKA revisions due to malalignment from 6.6% to nearly zero, this may decrease the revision burden and overall cost to the healthcare system.^1,3

TKA technology continues to evolve, and we must continue to assess each new advance not only to understand how it works, but also to ensure it addresses a specific clinical problem, and to be aware of the costs associated before incorporating it into routine practice. Some argue that the use of advanced technology requires increased surgical time, which in turn ultimately increases costs; however, one study has documented no increase in surgical time with handheld navigation while maintaining the accuracy of the device.³⁴ In addition, no significant radiographic or clinical differences have been found between handheld navigation and larger console CAS systems, but large console systems have been associated with increased surgical times.²² The use of handheld accelerometer- and gyroscope-based guides has proven to provide reliable coronal and sagittal implant alignment that can easily be incorporated into the operating room. More widespread use of such technology will help decrease alignment outliers for TKA, and future long-term clinical outcome studies will be necessary to assess functional outcomes.

Conclusion

Advanced computer based technology offers an additional tool to the surgeon for reliably improving component positioning during TKA. The use of handheld accelerometer- and gyroscope-based guides increases the accuracy of component placement while decreasing the incidence of outliers compared to standard mechanical guides, without the need for a large computer console. Long-term radiographic and patient-reported outcomes are necessary to further validate these devices.

Total knee arthroplasty (TKA) continues to be a widely utilized treatment option for end-stage knee osteoarthritis, and the number of patients undergoing TKA is projected to continually increase over the next decade.¹ Although TKA is highly successful for many patients, studies continue to report that approximately 20% of patients are dissatisfied after undergoing TKA, and nearly 25% of knee revisions are performed for instability or malalignment.^2,3 Technological advances have been developed to help improve clinical outcomes and implant survivorship. Over the past decade, computer navigation and intraoperative guides have been introduced to help control surgical variables and overcome the limitations and inaccuracies of traditional mechanical instrumentation. Currently, there are a variety of technologies available to assist surgeons with component alignment, including extramedullary devices, computer-assisted navigation systems (CAS), and patient-specific instrumentation (PSI) that help achieve desired alignment goals.^4,5

Computer-assisted navigation tools were introduced in an effort to improve implant alignment and clinical outcomes compared to traditional mechanical guides. Some argue that the use of computer-assisted surgery has a steep learning curve and successful use is dependent on the user’s experience; however, studies have suggested computer-assisted surgery may allow less experienced surgeons to reliably achieve anticipated intraoperative alignment goals with a low complication rate.^6,7 Various studies have looked at computer-assisted TKA at short to mid-term follow-up, but few studies have reported long-term outcomes.^6-9 de Steiger and colleagues¹⁰ recently found that computer-assisted TKA reduced the overall revision rate for aseptic loosening following TKA in patients younger than age 65 years, which suggests benefit of CAS for younger patients. Short-term follow-up has also shown the benefit of CAS TKA in patients with severe extra-articular deformity, where traditional instrumentation cannot be utilized.¹¹ Currently, there is no consensus that computer-assisted TKA leads to improved postoperative patient reported outcomes, because many studies are limited by study design or small cohorts; however, current literature does show an improvement in component alignment as compared to mechanical instrumentation.^9,12,13 As future implant and position targets are defined to improve implant survivorship and clinical outcomes in total joint arthroplasty, computer-assisted devices will be useful to help achieve more precise and accurate component positioning.

In addition to CAS devices, some companies have sought to improve TKA surgery by introducing PSI. PSI was introduced to improve component alignment in TKA, with the purported advantages of a shorter surgical time, decrease in the number of instruments needed, and improved clinical outcomes. PSI accuracy remains variable, which may be attributed to the various systems and implant designs in each study.^14-17 In addition, advanced preoperative imaging is necessary, which further adds to the overall cost.¹⁷ While the recent advancement in technology may provide decreased costs at the time of surgery, the increased cost and time incurred by the patient preoperatively has not resulted in significantly better clinical outcomes.^18,19 Additionally, recent work has not shown PSI to have superior accuracy as compared to currently available CAS devices.¹⁴ These findings suggest that the additional cost and time incurred by patients may limit the widespread use of PSI.

Although computer navigation has been shown to be more accurate than conventional instrumentation and PSI, the lack of improvement in long-term clinical outcome data has limited its use. In a meta-analysis, Bauwens and colleagues²⁰ suggested that while navigated TKAs have improved component alignment outcomes as compared to conventional surgery, the clinical benefit remains unclear. Less than 5% of surgeons are currently using navigation systems due to the perceived learning curve, cost, additional surgical time, and imaging required to utilize these systems. Certain navigation systems can be seemingly cumbersome, with large consoles, increased number of instruments required, and optical instruments with line-of-sight issues. Recent technological advances have worked to decrease this challenge by using accelerometer- and gyroscope-based electronic components, which combine the accuracy of computer-assisted technology with the ease of use of mechanical guides.

Accelerometer and gyroscope technology systems, such as the iAssist system, are portable devices that do not require a large computer console or navigation arrays. This technology relies on accelerator-based navigation without additional preoperative imaging. A recent study demonstrated the iAssist had reproducible accuracy in component alignment that could be easily incorporated into the operating room without optical trackers.²¹ The use of portable computer-assisted devices provides a more compact and easily accessible technology that can be used to achieve accurate component alignment without additional large equipment in the operating room.²² These new handheld intraoperative tools have been introduced to place implants according to a preoperative plan in order to minimize failure due to preoperative extra-articular deformity or intraoperative technical miscues.²³ Nam and colleagues²⁴ used an accelerometer-based surgical navigation system to perform tibial resections in cadaveric models, and found that the accelerometer-based guide was accurate for tibial resection in both the coronal and sagittal planes. In a prospective randomized controlled trial evaluating 100 patients undergoing a TKA using either an accelerometer-based guide or conventional alignment methods, the authors showed that the accelerometer-based guide decreased outliers in tibial component alignment compared to conventional guides.²⁵ In the accelerometer-based guide cohort, 95.7% of tibial components were within 2° of perpendicular to the tibial mechanical axis, compared to 68.1% in the conventional group (P < .001). These results suggested that portable accelerometer-based navigation allows surgeons to achieve satisfactory tibial component alignment with a decrease in the number of potential outliers.^24,25 Similarly, Bugbee and colleagues²⁶ found that accelerometer-based handheld navigation was accurate for tibial coronal and sagittal alignment and no additional surgical time was required compared to conventional techniques.

The relationship between knee alignment and clinical outcomes for TKA remains controversial. Regardless of the surgeon’s alignment preference, it is important to reliably and accurately execute the preoperative plan in a reproducible fashion. Advances in technology that assist with intraoperative component alignment can be useful, and may help decrease the incidence of implant malalignment in clinical practice.

Preoperative Planning and Intraoperative Technique

Preoperative planning is carried out in a manner identical to the use of conventional mechanical guides. Long leg films are taken for evaluation of overall limb alignment, and calibrated lateral images are taken for templating implant sizes. Lines are drawn on the images to determine the difference between the mechanical and anatomic axis of the femur, and a line drawn perpendicular to the mechanical axis is placed to show the expected bone cut. In similar fashion a perpendicular line to the tibial mechanical axis is also drawn to show the expected tibial resection. This preoperative plan allows the surgeon to have an additional intraoperative guide to ensure accuracy of the computer-assisted device.

After standard exposure, the distal femoral or proximal tibial cut can be made based on surgeon preference. The system being demonstrated in the accompanying photos is the KneeAlign 2 system (OrthAlign).

Distal Femoral Cut

The KneeAlign 2 femoral cutting guide is attached to the distal femur with a central pin that is placed in the middle of the distal femur measured from medial to lateral, and 1 cm anterior to the intercondylar notch. It is important to note that this spot is often more medial than traditionally used for insertion of an intramedullary rod. This central point sets the distal point of the femoral mechanical axis. The device is then held in place with 2 oblique pins, and is solidly fixed to the bone. Using a rotating motion, the femur is rotated around the hip joint. The accelerometer and gyroscope in the unit are able to determine the center of the hip joint from this motion, creating the proximal point of the mechanical axis of the femur. Once the mechanical axis of the femur is determined, varus/valgus and flexion/extension can be adjusted on the guide. One adjustment screw is available for varus/valgus, and a second is available for flexion/extension. Numbers on the device screen show real-time alignment, and are easily adjusted to set the desired alignment (Figure 1). Once alignment is obtained, a mechanical stylus is used to determine depth of resection, and the distal femoral cutting block is pinned. After pinning the block, the 3 pins in the device are removed, and the device is removed from the bone. This leaves only the distal femoral cutting block in place. In experienced hands, this part of the procedure takes less than 3 minutes.

Proximal Tibial Cut

The KneeAlign 2 proximal tibial guide is similar in appearance to a standard mechanical tibial cutting guide. It is attached to the proximal tibia with a spring around the calf and 2 pins that hold the device aligned with the medial third of the tibial tubercle. A stylus is then centered on the anterior cruciate ligament (ACL) footprint, which sets the proximal mechanical axis point of the tibia (Figure 2). An offset number is read off the stylus on the ACL footprint, and this number is matched on the ankle offset portion of the guide. The device has 2 sensors. One sensor is on the chassis of the device, and the other is on a mobile arm. Movements between the 2 are monitored by the accelerometers, allowing for accurate maintenance of alignment position even with motion in the leg. A point is taken from the lateral malleolus and then a second point is taken from the medial malleolus. These points are used to determine the center of the ankle joint, which sets the distal mechanical axis point. Once mechanical axis of the tibia is determined, the tibial cutting guide is pinned in place, and can be adjusted with real-time guidance of the varus/valgus and posterior slope values seen on the device (Figure 3). Cut depth is once again determined with a mechanical stylus.

Limitations

Although these devices have proven to be very accurate, surgeons must continue to recognize that all tools can have errors. With computerized guides of any sort, these errors are usually user errors that cannot be detected by the device. Surgeons need to be able to recognize this and always double-check bone cuts for accuracy. Templating the bone cuts prior to surgery is an effective double-check. In addition, many handheld accelerometer devices do not currently assist with the rotational alignment of the femoral component. This is still performed using the surgeon’s preferred technique, and is a limitation of these systems.

Discussion

Currently, TKA provides satisfactory 10-year results with modern implant designs and survival rates as high as 90% to 95%.^27,28 Even with good survival rates, a percentage of patients fail within the first 5 years.³ At a single institution, 50% of revision TKAs were related to instability, malalignment, or failure of fixation that occurred less than 2 years after the index procedure.²⁹ In general, TKA with mechanical instrumentation provides satisfactory pain relief and postoperative knee function; however, studies have consistently shown that the use of advanced technology decreases the risk of implant malalignment, which may decrease early implant failure rates as compared to mechanical and some PSI.^13,14,22 While there is a paucity of literature that has shown better clinical outcomes with the use of advanced technology, there are studies supporting the notion that proper limb alignment and component positioning improves implant survivorship.^23,30

CAS may have additional advantages if the surgeon chooses to place the TKA in an alignment other than a neutral mechanical axis. Kinematic alignment for TKA has gained increasing popularity, where the target of a neutral mechanical axis alignment is not always the goal.^31,32 The reported benefit is a more natural ligament tension with the hope of improving patient satisfaction. One concern with this technique is that it is a departure from the long-held teaching that a TKA aligned to a neutral mechanical axis is necessary for long-term implant survivorship.^33,34 In addition, if the goal of surgery is to cut the tibia and femur at a specific varus/valgus cut, standard instrumentation may not allow for this level of accuracy. This in turn increases the risk of having a tibial or femoral cut that is outside the commonly accepted standards of alignment, which may lead to early implant failure. If further research suggests alignment is a variable that differs from patient to patient, the use of precise tools to ensure accuracy of executing the preoperatively templated alignment becomes even more important.

As the number of TKAs continues to rise each year, even a small percentage of malaligned knees that go on to revision surgery will create a large burden on the healthcare system.^1,3 Although the short-term clinical benefits of CAS have not shown substantial differences as compared to conventional TKA, the number of knees aligned outside of a desired neutral mechanical axis alignment has been shown in multiple studies to be decreased with the use of advanced technology.^7,12,34 Although CAS is an additional cost to a primary TKA, if the orthopedic community can decrease the number of TKA revisions due to malalignment from 6.6% to nearly zero, this may decrease the revision burden and overall cost to the healthcare system.^1,3

TKA technology continues to evolve, and we must continue to assess each new advance not only to understand how it works, but also to ensure it addresses a specific clinical problem, and to be aware of the costs associated before incorporating it into routine practice. Some argue that the use of advanced technology requires increased surgical time, which in turn ultimately increases costs; however, one study has documented no increase in surgical time with handheld navigation while maintaining the accuracy of the device.³⁴ In addition, no significant radiographic or clinical differences have been found between handheld navigation and larger console CAS systems, but large console systems have been associated with increased surgical times.²² The use of handheld accelerometer- and gyroscope-based guides has proven to provide reliable coronal and sagittal implant alignment that can easily be incorporated into the operating room. More widespread use of such technology will help decrease alignment outliers for TKA, and future long-term clinical outcome studies will be necessary to assess functional outcomes.

Conclusion

Advanced computer based technology offers an additional tool to the surgeon for reliably improving component positioning during TKA. The use of handheld accelerometer- and gyroscope-based guides increases the accuracy of component placement while decreasing the incidence of outliers compared to standard mechanical guides, without the need for a large computer console. Long-term radiographic and patient-reported outcomes are necessary to further validate these devices.

Unicompartmental knee arthroplasty (UKA) and total knee arthroplasty (TKA) are 2 reliable treatment options for patients with primary osteoarthritis. Recently published systematic reviews of cohort studies have shown that 10-year survivorship of medial and lateral UKA is 92% and 91%, respectively,¹ while 10-year survivorship of TKA in cohort studies is 95%.² National and annual registries show a similar trend, although the reported survivorship is lower.^1,3-7

In order to improve these survivorship rates, the surgical variables that can intraoperatively be controlled by the orthopedic surgeon have been evaluated. These variables include lower leg alignment, soft tissue balance, joint line maintenance, and alignment, size, and fixation of the tibial and femoral component. Several studies have shown that tight control of lower leg alignment,^8-14 balancing of the soft tissues,^15-19 joint line maintenance,^20-23 component alignment,^24-28 component size,^29-34 and component fixation^35-40 can improve the outcomes of UKA and TKA. As a result, over the past 2 decades, several computer-assisted surgery systems have been developed with the goal of more accurate and reliable control of these factors, and thus improved outcomes of knee arthroplasty.

These systems differ with regard to the number and type of variables they control. Computer navigation systems aim to control one or more of these surgical variables, and several meta-analyses have shown that these systems, when compared to conventional surgery, improve mechanical axis accuracy, decrease the risk for mechanical axis outliers, and improve component positioning in TKA^41-49 and UKA surgery.^50,51 Interestingly, however, meta-analyses have failed to show the expected superiority in clinical outcomes following computer navigation compared to conventional knee arthroplasty.^48,52-55 Furthermore, authors have shown that, despite the fact that computer-navigated surgery increases the accuracy of mechanical alignment and surgical cutting, there is still room for improvement.⁵⁶ As a consequence, robotic-assisted systems have been developed.

Similar to computer navigation, these robotic-assisted systems aim to control the surgical variables; in addition, they aim to improve the surgical precision of the procedure. Interestingly, 2 recent studies have shown that robotic-assisted systems are superior to computer navigation systems with regard to less cutting time and less resection deviations in coronal and sagittal plane in a cadaveric study,⁵⁷ and shorter total surgery time, more accurate mechanical axis, and shorter hospital stay in a clinical study.⁵⁸ Although these results are promising, the exact role of robotic surgery in knee arthroplasty remains unclear. In this review, we aim to report the current state of robotic-assisted knee arthroplasty by discussing (1) the different robotic-assisted knee arthroplasty systems that are available for UKA and TKA surgery, (2) studies that assessed the role of robotic-assisted knee arthroplasty in controlling the aforementioned surgical variables, (3) cadaveric and clinical comparative studies that compared how accurate robotic-assisted and conventional knee surgery control these surgical variables, and (4) studies that assessed the cost-effectiveness of robotic-assisted knee arthroplasty surgery.

Robotic-Assisted Knee Arthroplasty Systems

Several systems have been developed over the years for knee arthroplasty, and these are usually defined as active, semi-active, or passive.⁵⁹ Active systems are capable of performing tasks or processes autonomously under the watchful eye of the surgeon, while passive systems do not perform actions independently but provide the surgeon with information. In semi-active systems, the surgical action is physically constrained in order to follow a predefined strategy.

In the United States, 3 robotic systems are FDA-approved for knee arthroplasty. The Stryker/Mako haptic guided robot (Mako Surgical Corp.) was introduced in 2005 and has been used for over 50,000 UKA procedures (Figure 1). There are nearly 300 robotic systems used nationally, as it has 20% of the market share for UKA in the United States. The Mako system is a semi-active tactile robotic system that requires preoperative imaging, after which a preoperative planning is performed. Intraoperatively, the robotic arm is under direct surgeon control and gives real-time tactile feedback during the procedure (Figure 2).

Furthermore, the surgeon can intraoperatively virtually adjust component positioning and alignment and move the knee through the range of motion, after which the system can provide information on alignment, component position, and balance of the soft tissue (eg, if the knee is overtight or lax through the flexion-arch).⁶⁰ This system has a burr that resects the bone and when the surgeon directs the burr outside the preplanned area, the burr stops and prevents unnecessary and unwanted resections (Figure 3).

The Navio Precision Free-Hand Sculptor (PFS) system (Blue Belt Technologies) has been used for 1500 UKA procedures, with 50 robots in use in the United States (Figure 4). This system is an image-free semi-active robotic system and has the same characteristics as the aforementioned Mako system.⁶¹ Finally, the OmniBotic robotic system (Omnilife Science) has been released for TKA and has been used for over 7300 procedures (Figure 5). This system has an automated cutting-guide technique in which the surgeon designs a virtual plan on the computer system. After this, the cutting-guides are placed by the robotic system at the planned location for all 5 femoral cuts (ie, distal, anterior chamfer, anterior, posterior chamfer, and posterior) and the surgeon then makes the final cuts.^57,62

Three robotic systems for knee arthroplasty surgery have been used in Europe. The Caspar system (URS Ortho) is an active robotic system in which a computed tomography (CT) scan is performed preoperatively, after which a virtual implantation is performed on the screen. The surgeon can then obtain information on lower leg alignment, gap balancing, and component positioning, and after an operative plan is made, the surgical resections are performed by the robot. Reflective markers are attached to the leg and all robotic movements are monitored using an infrared camera system. Any undesired motion will be detected by this camera system and will stop all movements.⁶³ A second and more frequently reported system in the literature is the active Robodoc surgical system (Curexo Technology Corporation). This system is designed for TKA and total hip arthroplasty (THA) surgery. Although initial studies reported a high incidence of system-related complications in THA,⁶⁴ the use of this system for TKA has frequently been reported in the literature.^56,63,65-69 A third robotic system that has been used in Europe is the Acrobot surgical system (Acrobot Company Ltd), which is an image-based semi-active robotic system⁷⁰ used for both UKA and TKA surgery.^70,71

Accuracy of Controlling Surgical Variables in Robotic-Assisted Knee Arthroplasty

Several studies have assessed the accuracy of robotic-assisted surgery in UKA surgery with regard to control of the aforementioned surgical variables. Pearle and colleagues⁷² assessed the mechanical axis accuracy of the Mako system in 10 patients undergoing medial UKA robotic-assisted surgery. They reported that the intraoperative registration lasted 7.5 minutes and the duration of time needed for robotic-assisted burring was 34.8 minutes. They compared the actual postoperative alignment at 6 weeks follow-up with the planned lower leg alignment and found that all measurements were within 1.6° of the planned lower leg alignment. Dunbar and colleagues⁷³ assessed the accuracy of component positioning of the Mako system in 20 patients undergoing medial UKA surgery by comparing preoperative and postoperative 3-dimensional CT scans. They found that the femoral component was within 0.8 mm and 0.9° in all directions and that the tibial component was within 0.9 mm and 1.7° in all directions. They concluded that the accuracy of component positioning with the Mako system was excellent. Finally, Plate and colleagues¹⁷ assessed the accuracy of soft tissue balancing in the Mako system in 52 patients undergoing medial UKA surgery. They compared the balance plan with the soft tissue balance after implantation and the Mako system quantified soft tissue balance as the amount of mm of the knee being tight or loose at 0°, 30°, 60°, 90°, and 110° of flexion. They found that at all flexion angles the ligament balancing was accurate up to 0.53 mm of the original plan. Furthermore, they noted that in 83% of cases the accuracy was within 1 mm at all flexion angles.

For the Navio system, Smith and colleagues⁷⁴ assessed the accuracy of component positioning using 20 synthetic femurs and tibia. They reported a maximum rotational error of 3.2°, an angular error of 1.46° in all orientations, and a maximum translational error of 1.18 mm for both the tibial and femoral implants. Lonner and colleagues⁷⁵ assessed the accuracy of component positioning in 25 cadaveric specimens. They found similar results as were found in the study of Smith and colleagues⁷⁴ and concluded that these results were similar to other semi-active robotic systems designed for UKA.

For TKA surgery, Ponder and colleagues⁷⁶ assessed the accuracy of the OmniBotic system and found that the average error in the anterior-posterior dimension between the targeted and measured cuts was -0.14 mm, and that the standard deviation in guide positioning for the distal, anterior chamfer, and posterior chamfer resections was 0.03° and 0.17 mm. Koenig and colleagues⁶² assessed the accuracy of the OmniBotic system in the first 100 cases and found that 98% of the cases were within 3° of the neutral mechanical axis. Furthermore, they found a learning curve with regard to tourniquet time between the first and second 10 patients in which they performed robotic-assisted TKA surgery. Siebert and colleagues⁶³ assessed the accuracy of mechanical alignment in the Caspar system in 70 patients treated with the robotic system. They found that the difference between preoperatively planned and postoperatively achieved mechanical alignment was 0.8°. Similarly, Bellemans and colleagues⁷⁷ assessed mechanical alignment and the positioning and rotation of the tibial and femoral components in a clinical study of 25 cases using the Caspar system. They noted that none of the patients had mechanical alignment, tibial or femoral component positioning, or rotation beyond 1° of the neutral axis. Liow and colleagues⁵⁶ assessed the accuracy of mechanical axis alignment and component sizing accuracy using the Robodoc system in 25 patients. They reported that the mean postoperative alignment was 0.4° valgus and that all cases were within 3° of the neutral mechanical axis. Furthermore, they reported a mean surgical time of 96 minutes and reported that preoperative planning yielded femoral and tibial component size accuracy of 100%.

These studies have shown that robotic systems for UKA and TKA are accurate in the surgical variables they aim to control. These studies validated tight control of mechanical axis alignment, decrease for outliers, and component positioning and rotation, and also found that the balancing of soft tissues was improved using robotic-assisted surgery.

Robotic-Assisted vs Conventional Knee Arthroplasty

Despite the fact that these systems are accurate in the variables they aim to control, these systems have to be compared to the gold standard of conventional knee arthroplasty. For UKA, Cobb and colleagues⁷⁰ performed a randomized clinical trial for patients treated undergoing UKA with robotic-assistance of the Acrobot systems compared to conventional UKA and assessed differences in mechanical accuracy. A total of 27 patients were randomly assigned to one of both treatments. They found that in the group of robotic-assisted surgery, 100% of the patients had a mechanical axis within 2° of neutral, while this was only 40% in the conventional UKA groups (difference P < .001). They also assessed the increase in functional outcomes and noted a trend towards improvement in performance with increasing accuracy at 6 weeks and 3 months postoperatively. Lonner and colleagues⁷⁸ also compared the tibial component positioning between robotic-assisted UKA surgery using the Mako system and conventional UKA surgery. The authors found that the variance in tibial slope, in coronal plane of the tibial component, and varus/valgus alignment were all larger with conventional UKA when compared to robotic-assisted UKA. Citak and colleagues⁷⁹ compared the accuracy of tibial and femoral implant positioning between robotic-assisted surgery using the Mako system and conventional UKA in a cadaveric study. They reported that the root mean square (RMS) error of femoral component was 1.9 mm and 3.7° in robotic-assisted surgery and 5.4 mm and 10.2° for conventional UKA, while the RMS error for tibial component were 1.4 mm and 5.0° for robotic-assisted surgery and 5.7 mm and 19.2° for conventional UKA surgery. MacCallum and colleagues⁸⁰ compared the tibial base plate position in a prospective clinical study of 177 patients treated with conventional UKA and 87 patients treated with robotic-assisted surgery using the Mako system. They found that surgery with robotic-assistance was more precise in the coronal and sagittal plane and was more accurate in coronal alignment when compared to conventional UKA. Finally, the first results of robotic-assisted UKA surgery have been presented. Coon and colleagues⁸¹ reported the preliminary results of a multicenter study of 854 patients and found a survivorship of 98.9% and satisfaction rate of 92% at minimum 2-year follow-up. Comparing these results to other large conventional UKA cohorts^82,83 suggests that robotic-assisted surgery may improve survivorship at short-term follow-up. However, comparative studies and studies with longer follow-up are necessary to assess the additional value of robotic-assisted UKA surgery. Due to the relatively new concept of robotic-assisted surgery, these studies have not been performed or published yet.

For TKA, several studies also have compared how these robotic-systems control the surgical variables compared to conventional TKA surgery. Siebert and colleagues⁶³ assessed mechanical axis accuracy and mechanical outliers following robotic-assisted TKA surgery using the Caspar system and conventional TKA surgery. They reported the difference between preoperative planned and postoperative achieved alignment was 0.8° for robotic-assisted surgery and 2.6° for conventional TKA surgery. Furthermore, they showed that 1 patient in the robotic-assisted group (1.4%) and 18 patients in the conventional TKA group (35%) had mechanical alignment greater than 3° from the neutral mechanical axis. Liow and colleagues⁵⁶ found similar differences in their prospective randomized study in which they reported that 0% outliers greater than 3° from the neutral mechanical axis were found in the robotic-assisted group while 19.4% of the patients in the conventional TKA group had mechanical axis outliers. They also assessed the joint-line outliers in both procedures and found that 3.2% had joint-line outliers greater than 5 mm in the robotic-assisted group compared to 20.6% in the conventional TKA group. Kim and colleagues⁶⁵ assessed implant accuracy in robotic-assisted surgery using the ROBODOC system and in conventional surgery and reported higher implant accuracy and fewer outliers using robotic-assisted surgery. Moon and colleagues⁶⁶ compared robotic-assisted TKA surgery using the Robodoc system with conventional TKA surgery in 10 cadavers. They found that robotic-assisted surgery had excellent precision in all planes and had better accuracy in femoral rotation alignment compared to conventional TKA surgery. Park and Lee⁶⁷ compared Robodoc robotic-assisted TKA surgery with conventional TKA surgery in a randomized clinical trial of 72 patients. They found that robotic-assisted surgery had definitive advantages in preoperative planning, accuracy of the procedure, and postoperative follow-up regarding femoral and tibial component flexion angles. Finally, Song and colleagues^68,69 performed 2 randomized clinical trials in which they compared mechanical axis alignment, component positioning, soft tissue balancing, and patient preference between conventional TKA surgery and robotic-assisted surgery using the Robodoc system. In the first study,⁶⁸ they simultaneously performed robotic-assisted surgery in one leg and conventional TKA surgery in the other leg. They found that robotic-assisted surgery resulted in less outlier in mechanical axis and component positioning. Furthermore, they found at latest follow-up of 2 years that 12 patients preferred the leg treated with robotic-assisted surgery while 6 preferred the conventional leg. Despite this finding, no significant differences in functional outcome scores were detected between both treatment options. Furthermore, they found that flexion-extension balance was achieved in 92% of patients treated with robotic-assisted TKA surgery and in 77% of patients treated with conventional TKA surgery. In the other study,⁶⁹ the authors found that more patients treated with robotic-assisted surgery had <2 mm flexion-extension gap and more satisfactory posterior cruciate ligament tension when compared to conventional surgery.

These studies have shown that robotic-assisted surgery is accurate in controlling surgical variables, such as mechanical lower leg alignment, maintaining joint-line, implant positioning, and soft tissue balancing. Furthermore, these studies have shown that controlling these variables is better than the current gold standard of manual knee arthroplasty. Until now, not many studies have assessed survivorship of robotic-assisted surgery. Furthermore, no studies have, to our knowledge, compared survivorship of robotic-assisted with conventional knee replacement surgery. Finally, studies comparing functional outcomes following robotic-assisted surgery and conventional knee arthroplasty surgery are frequently underpowered due to their small sample sizes.^68,70 Since many studies have shown that the surgical variables are more tightly controlled using robotic-assisted surgery when compared to conventional surgery, large comparative studies are necessary to assess the role of robotic-assisted surgery in functional outcomes and survivorship of UKA and TKA.

Cost-Effectiveness of Robotic-Assisted Surgery

High initial capital costs of robotic-assisted surgery is one of the factors that constitute a barrier to the widespread implementation of this technique. Multiple authors have suggested that improved implant survivorship afforded by robotic-assisted surgery may justify the expenditure from both societal and provider perspective.^84-86 Two studies have performed a cost-effectiveness analysis for UKA surgery. Swank and colleagues⁸⁴ reviewed the hospital expenditures and profits associated with robot-assisted knee arthroplasty, citing upfront costs of approximately $800,000. The authors estimated a mean per-case contribution profit of $5790 for robotic-assisted UKA, assuming an inpatient-to-outpatient ratio of 1 to 3. Based on this data, Swank and colleagues84 proposed that the capital costs of robotic-assisted UKA may be recovered in as little as 2 years when in the first 3 consecutive years 50, 70, and 90 cases were performed using robotic-assisted UKA. Moschetti and colleagues⁸⁵ recently published the first formal cost-effectiveness analysis of robotic-assisted compared to manual UKA. The authors used an annual revision risk of 0.55% for the first 2 years following robot-assisted UKA, based on the aforementioned presented data by Coon and colleagues.⁸¹ They based their data on the Mako system and assumed an initial capital expenditure of $934,728 with annual servicing costs of 10% (discounted annually) for 4 years thereafter, resulting in a total cost of the robotic system of $1.362 million. These costs were divided by the number of patients estimated to undergo robotic-assisted UKA per year, which was varied to estimate the effect of case volume on cost-effectiveness. The authors reported that robotic-assisted UKA was associated with higher lifetime costs and net utilities compared to manual UKA, at an incremental cost-effectiveness ratio of $47,180 per quality-adjusted life year (QALY) in a high-volume center. This falls well within the societal willingness-to-pay threshold of $100,000/QALY. Sensitivity analysis showed that robotic-assisted UKA is cost-effective under the following conditions: (1) centers performing at least 94 cases annually, (2) in patients younger than age 67 years, and (3) 2-year revision rate does not exceed 1.2%. While the results of this initial analysis are promising, follow-up cost-effectiveness analysis studies will be required as long-term survivorship data become available.

Conclusion

Tighter control of intraoperative surgical variables, such as lower leg alignment, soft tissue balance, joint-line maintenance, and component alignment and positioning, have been associated with improved survivorship and functional outcomes. Upon reviewing the available literature on robotic-assisted surgery, it becomes clear that this technique can improve the accuracy of these surgical variables and is superior to conventional manual UKA and TKA. Although larger and comparative survivorship studies are necessary to compare robotic-assisted knee arthroplasty to conventional techniques, the early results and cost-effectiveness analysis seem promising.

Unicompartmental knee arthroplasty (UKA) and total knee arthroplasty (TKA) are 2 reliable treatment options for patients with primary osteoarthritis. Recently published systematic reviews of cohort studies have shown that 10-year survivorship of medial and lateral UKA is 92% and 91%, respectively,¹ while 10-year survivorship of TKA in cohort studies is 95%.² National and annual registries show a similar trend, although the reported survivorship is lower.^1,3-7

In order to improve these survivorship rates, the surgical variables that can intraoperatively be controlled by the orthopedic surgeon have been evaluated. These variables include lower leg alignment, soft tissue balance, joint line maintenance, and alignment, size, and fixation of the tibial and femoral component. Several studies have shown that tight control of lower leg alignment,^8-14 balancing of the soft tissues,^15-19 joint line maintenance,^20-23 component alignment,^24-28 component size,^29-34 and component fixation^35-40 can improve the outcomes of UKA and TKA. As a result, over the past 2 decades, several computer-assisted surgery systems have been developed with the goal of more accurate and reliable control of these factors, and thus improved outcomes of knee arthroplasty.

These systems differ with regard to the number and type of variables they control. Computer navigation systems aim to control one or more of these surgical variables, and several meta-analyses have shown that these systems, when compared to conventional surgery, improve mechanical axis accuracy, decrease the risk for mechanical axis outliers, and improve component positioning in TKA^41-49 and UKA surgery.^50,51 Interestingly, however, meta-analyses have failed to show the expected superiority in clinical outcomes following computer navigation compared to conventional knee arthroplasty.^48,52-55 Furthermore, authors have shown that, despite the fact that computer-navigated surgery increases the accuracy of mechanical alignment and surgical cutting, there is still room for improvement.⁵⁶ As a consequence, robotic-assisted systems have been developed.

Similar to computer navigation, these robotic-assisted systems aim to control the surgical variables; in addition, they aim to improve the surgical precision of the procedure. Interestingly, 2 recent studies have shown that robotic-assisted systems are superior to computer navigation systems with regard to less cutting time and less resection deviations in coronal and sagittal plane in a cadaveric study,⁵⁷ and shorter total surgery time, more accurate mechanical axis, and shorter hospital stay in a clinical study.⁵⁸ Although these results are promising, the exact role of robotic surgery in knee arthroplasty remains unclear. In this review, we aim to report the current state of robotic-assisted knee arthroplasty by discussing (1) the different robotic-assisted knee arthroplasty systems that are available for UKA and TKA surgery, (2) studies that assessed the role of robotic-assisted knee arthroplasty in controlling the aforementioned surgical variables, (3) cadaveric and clinical comparative studies that compared how accurate robotic-assisted and conventional knee surgery control these surgical variables, and (4) studies that assessed the cost-effectiveness of robotic-assisted knee arthroplasty surgery.

Robotic-Assisted Knee Arthroplasty Systems

Several systems have been developed over the years for knee arthroplasty, and these are usually defined as active, semi-active, or passive.⁵⁹ Active systems are capable of performing tasks or processes autonomously under the watchful eye of the surgeon, while passive systems do not perform actions independently but provide the surgeon with information. In semi-active systems, the surgical action is physically constrained in order to follow a predefined strategy.

In the United States, 3 robotic systems are FDA-approved for knee arthroplasty. The Stryker/Mako haptic guided robot (Mako Surgical Corp.) was introduced in 2005 and has been used for over 50,000 UKA procedures (Figure 1). There are nearly 300 robotic systems used nationally, as it has 20% of the market share for UKA in the United States. The Mako system is a semi-active tactile robotic system that requires preoperative imaging, after which a preoperative planning is performed. Intraoperatively, the robotic arm is under direct surgeon control and gives real-time tactile feedback during the procedure (Figure 2).

Furthermore, the surgeon can intraoperatively virtually adjust component positioning and alignment and move the knee through the range of motion, after which the system can provide information on alignment, component position, and balance of the soft tissue (eg, if the knee is overtight or lax through the flexion-arch).⁶⁰ This system has a burr that resects the bone and when the surgeon directs the burr outside the preplanned area, the burr stops and prevents unnecessary and unwanted resections (Figure 3).

The Navio Precision Free-Hand Sculptor (PFS) system (Blue Belt Technologies) has been used for 1500 UKA procedures, with 50 robots in use in the United States (Figure 4). This system is an image-free semi-active robotic system and has the same characteristics as the aforementioned Mako system.⁶¹ Finally, the OmniBotic robotic system (Omnilife Science) has been released for TKA and has been used for over 7300 procedures (Figure 5). This system has an automated cutting-guide technique in which the surgeon designs a virtual plan on the computer system. After this, the cutting-guides are placed by the robotic system at the planned location for all 5 femoral cuts (ie, distal, anterior chamfer, anterior, posterior chamfer, and posterior) and the surgeon then makes the final cuts.^57,62

Three robotic systems for knee arthroplasty surgery have been used in Europe. The Caspar system (URS Ortho) is an active robotic system in which a computed tomography (CT) scan is performed preoperatively, after which a virtual implantation is performed on the screen. The surgeon can then obtain information on lower leg alignment, gap balancing, and component positioning, and after an operative plan is made, the surgical resections are performed by the robot. Reflective markers are attached to the leg and all robotic movements are monitored using an infrared camera system. Any undesired motion will be detected by this camera system and will stop all movements.⁶³ A second and more frequently reported system in the literature is the active Robodoc surgical system (Curexo Technology Corporation). This system is designed for TKA and total hip arthroplasty (THA) surgery. Although initial studies reported a high incidence of system-related complications in THA,⁶⁴ the use of this system for TKA has frequently been reported in the literature.^56,63,65-69 A third robotic system that has been used in Europe is the Acrobot surgical system (Acrobot Company Ltd), which is an image-based semi-active robotic system⁷⁰ used for both UKA and TKA surgery.^70,71

Accuracy of Controlling Surgical Variables in Robotic-Assisted Knee Arthroplasty

Several studies have assessed the accuracy of robotic-assisted surgery in UKA surgery with regard to control of the aforementioned surgical variables. Pearle and colleagues⁷² assessed the mechanical axis accuracy of the Mako system in 10 patients undergoing medial UKA robotic-assisted surgery. They reported that the intraoperative registration lasted 7.5 minutes and the duration of time needed for robotic-assisted burring was 34.8 minutes. They compared the actual postoperative alignment at 6 weeks follow-up with the planned lower leg alignment and found that all measurements were within 1.6° of the planned lower leg alignment. Dunbar and colleagues⁷³ assessed the accuracy of component positioning of the Mako system in 20 patients undergoing medial UKA surgery by comparing preoperative and postoperative 3-dimensional CT scans. They found that the femoral component was within 0.8 mm and 0.9° in all directions and that the tibial component was within 0.9 mm and 1.7° in all directions. They concluded that the accuracy of component positioning with the Mako system was excellent. Finally, Plate and colleagues¹⁷ assessed the accuracy of soft tissue balancing in the Mako system in 52 patients undergoing medial UKA surgery. They compared the balance plan with the soft tissue balance after implantation and the Mako system quantified soft tissue balance as the amount of mm of the knee being tight or loose at 0°, 30°, 60°, 90°, and 110° of flexion. They found that at all flexion angles the ligament balancing was accurate up to 0.53 mm of the original plan. Furthermore, they noted that in 83% of cases the accuracy was within 1 mm at all flexion angles.

For the Navio system, Smith and colleagues⁷⁴ assessed the accuracy of component positioning using 20 synthetic femurs and tibia. They reported a maximum rotational error of 3.2°, an angular error of 1.46° in all orientations, and a maximum translational error of 1.18 mm for both the tibial and femoral implants. Lonner and colleagues⁷⁵ assessed the accuracy of component positioning in 25 cadaveric specimens. They found similar results as were found in the study of Smith and colleagues⁷⁴ and concluded that these results were similar to other semi-active robotic systems designed for UKA.

For TKA surgery, Ponder and colleagues⁷⁶ assessed the accuracy of the OmniBotic system and found that the average error in the anterior-posterior dimension between the targeted and measured cuts was -0.14 mm, and that the standard deviation in guide positioning for the distal, anterior chamfer, and posterior chamfer resections was 0.03° and 0.17 mm. Koenig and colleagues⁶² assessed the accuracy of the OmniBotic system in the first 100 cases and found that 98% of the cases were within 3° of the neutral mechanical axis. Furthermore, they found a learning curve with regard to tourniquet time between the first and second 10 patients in which they performed robotic-assisted TKA surgery. Siebert and colleagues⁶³ assessed the accuracy of mechanical alignment in the Caspar system in 70 patients treated with the robotic system. They found that the difference between preoperatively planned and postoperatively achieved mechanical alignment was 0.8°. Similarly, Bellemans and colleagues⁷⁷ assessed mechanical alignment and the positioning and rotation of the tibial and femoral components in a clinical study of 25 cases using the Caspar system. They noted that none of the patients had mechanical alignment, tibial or femoral component positioning, or rotation beyond 1° of the neutral axis. Liow and colleagues⁵⁶ assessed the accuracy of mechanical axis alignment and component sizing accuracy using the Robodoc system in 25 patients. They reported that the mean postoperative alignment was 0.4° valgus and that all cases were within 3° of the neutral mechanical axis. Furthermore, they reported a mean surgical time of 96 minutes and reported that preoperative planning yielded femoral and tibial component size accuracy of 100%.

These studies have shown that robotic systems for UKA and TKA are accurate in the surgical variables they aim to control. These studies validated tight control of mechanical axis alignment, decrease for outliers, and component positioning and rotation, and also found that the balancing of soft tissues was improved using robotic-assisted surgery.

Robotic-Assisted vs Conventional Knee Arthroplasty

Despite the fact that these systems are accurate in the variables they aim to control, these systems have to be compared to the gold standard of conventional knee arthroplasty. For UKA, Cobb and colleagues⁷⁰ performed a randomized clinical trial for patients treated undergoing UKA with robotic-assistance of the Acrobot systems compared to conventional UKA and assessed differences in mechanical accuracy. A total of 27 patients were randomly assigned to one of both treatments. They found that in the group of robotic-assisted surgery, 100% of the patients had a mechanical axis within 2° of neutral, while this was only 40% in the conventional UKA groups (difference P < .001). They also assessed the increase in functional outcomes and noted a trend towards improvement in performance with increasing accuracy at 6 weeks and 3 months postoperatively. Lonner and colleagues⁷⁸ also compared the tibial component positioning between robotic-assisted UKA surgery using the Mako system and conventional UKA surgery. The authors found that the variance in tibial slope, in coronal plane of the tibial component, and varus/valgus alignment were all larger with conventional UKA when compared to robotic-assisted UKA. Citak and colleagues⁷⁹ compared the accuracy of tibial and femoral implant positioning between robotic-assisted surgery using the Mako system and conventional UKA in a cadaveric study. They reported that the root mean square (RMS) error of femoral component was 1.9 mm and 3.7° in robotic-assisted surgery and 5.4 mm and 10.2° for conventional UKA, while the RMS error for tibial component were 1.4 mm and 5.0° for robotic-assisted surgery and 5.7 mm and 19.2° for conventional UKA surgery. MacCallum and colleagues⁸⁰ compared the tibial base plate position in a prospective clinical study of 177 patients treated with conventional UKA and 87 patients treated with robotic-assisted surgery using the Mako system. They found that surgery with robotic-assistance was more precise in the coronal and sagittal plane and was more accurate in coronal alignment when compared to conventional UKA. Finally, the first results of robotic-assisted UKA surgery have been presented. Coon and colleagues⁸¹ reported the preliminary results of a multicenter study of 854 patients and found a survivorship of 98.9% and satisfaction rate of 92% at minimum 2-year follow-up. Comparing these results to other large conventional UKA cohorts^82,83 suggests that robotic-assisted surgery may improve survivorship at short-term follow-up. However, comparative studies and studies with longer follow-up are necessary to assess the additional value of robotic-assisted UKA surgery. Due to the relatively new concept of robotic-assisted surgery, these studies have not been performed or published yet.

For TKA, several studies also have compared how these robotic-systems control the surgical variables compared to conventional TKA surgery. Siebert and colleagues⁶³ assessed mechanical axis accuracy and mechanical outliers following robotic-assisted TKA surgery using the Caspar system and conventional TKA surgery. They reported the difference between preoperative planned and postoperative achieved alignment was 0.8° for robotic-assisted surgery and 2.6° for conventional TKA surgery. Furthermore, they showed that 1 patient in the robotic-assisted group (1.4%) and 18 patients in the conventional TKA group (35%) had mechanical alignment greater than 3° from the neutral mechanical axis. Liow and colleagues⁵⁶ found similar differences in their prospective randomized study in which they reported that 0% outliers greater than 3° from the neutral mechanical axis were found in the robotic-assisted group while 19.4% of the patients in the conventional TKA group had mechanical axis outliers. They also assessed the joint-line outliers in both procedures and found that 3.2% had joint-line outliers greater than 5 mm in the robotic-assisted group compared to 20.6% in the conventional TKA group. Kim and colleagues⁶⁵ assessed implant accuracy in robotic-assisted surgery using the ROBODOC system and in conventional surgery and reported higher implant accuracy and fewer outliers using robotic-assisted surgery. Moon and colleagues⁶⁶ compared robotic-assisted TKA surgery using the Robodoc system with conventional TKA surgery in 10 cadavers. They found that robotic-assisted surgery had excellent precision in all planes and had better accuracy in femoral rotation alignment compared to conventional TKA surgery. Park and Lee⁶⁷ compared Robodoc robotic-assisted TKA surgery with conventional TKA surgery in a randomized clinical trial of 72 patients. They found that robotic-assisted surgery had definitive advantages in preoperative planning, accuracy of the procedure, and postoperative follow-up regarding femoral and tibial component flexion angles. Finally, Song and colleagues^68,69 performed 2 randomized clinical trials in which they compared mechanical axis alignment, component positioning, soft tissue balancing, and patient preference between conventional TKA surgery and robotic-assisted surgery using the Robodoc system. In the first study,⁶⁸ they simultaneously performed robotic-assisted surgery in one leg and conventional TKA surgery in the other leg. They found that robotic-assisted surgery resulted in less outlier in mechanical axis and component positioning. Furthermore, they found at latest follow-up of 2 years that 12 patients preferred the leg treated with robotic-assisted surgery while 6 preferred the conventional leg. Despite this finding, no significant differences in functional outcome scores were detected between both treatment options. Furthermore, they found that flexion-extension balance was achieved in 92% of patients treated with robotic-assisted TKA surgery and in 77% of patients treated with conventional TKA surgery. In the other study,⁶⁹ the authors found that more patients treated with robotic-assisted surgery had <2 mm flexion-extension gap and more satisfactory posterior cruciate ligament tension when compared to conventional surgery.

These studies have shown that robotic-assisted surgery is accurate in controlling surgical variables, such as mechanical lower leg alignment, maintaining joint-line, implant positioning, and soft tissue balancing. Furthermore, these studies have shown that controlling these variables is better than the current gold standard of manual knee arthroplasty. Until now, not many studies have assessed survivorship of robotic-assisted surgery. Furthermore, no studies have, to our knowledge, compared survivorship of robotic-assisted with conventional knee replacement surgery. Finally, studies comparing functional outcomes following robotic-assisted surgery and conventional knee arthroplasty surgery are frequently underpowered due to their small sample sizes.^68,70 Since many studies have shown that the surgical variables are more tightly controlled using robotic-assisted surgery when compared to conventional surgery, large comparative studies are necessary to assess the role of robotic-assisted surgery in functional outcomes and survivorship of UKA and TKA.

Cost-Effectiveness of Robotic-Assisted Surgery

High initial capital costs of robotic-assisted surgery is one of the factors that constitute a barrier to the widespread implementation of this technique. Multiple authors have suggested that improved implant survivorship afforded by robotic-assisted surgery may justify the expenditure from both societal and provider perspective.^84-86 Two studies have performed a cost-effectiveness analysis for UKA surgery. Swank and colleagues⁸⁴ reviewed the hospital expenditures and profits associated with robot-assisted knee arthroplasty, citing upfront costs of approximately $800,000. The authors estimated a mean per-case contribution profit of $5790 for robotic-assisted UKA, assuming an inpatient-to-outpatient ratio of 1 to 3. Based on this data, Swank and colleagues84 proposed that the capital costs of robotic-assisted UKA may be recovered in as little as 2 years when in the first 3 consecutive years 50, 70, and 90 cases were performed using robotic-assisted UKA. Moschetti and colleagues⁸⁵ recently published the first formal cost-effectiveness analysis of robotic-assisted compared to manual UKA. The authors used an annual revision risk of 0.55% for the first 2 years following robot-assisted UKA, based on the aforementioned presented data by Coon and colleagues.⁸¹ They based their data on the Mako system and assumed an initial capital expenditure of $934,728 with annual servicing costs of 10% (discounted annually) for 4 years thereafter, resulting in a total cost of the robotic system of $1.362 million. These costs were divided by the number of patients estimated to undergo robotic-assisted UKA per year, which was varied to estimate the effect of case volume on cost-effectiveness. The authors reported that robotic-assisted UKA was associated with higher lifetime costs and net utilities compared to manual UKA, at an incremental cost-effectiveness ratio of $47,180 per quality-adjusted life year (QALY) in a high-volume center. This falls well within the societal willingness-to-pay threshold of $100,000/QALY. Sensitivity analysis showed that robotic-assisted UKA is cost-effective under the following conditions: (1) centers performing at least 94 cases annually, (2) in patients younger than age 67 years, and (3) 2-year revision rate does not exceed 1.2%. While the results of this initial analysis are promising, follow-up cost-effectiveness analysis studies will be required as long-term survivorship data become available.

Conclusion

Tighter control of intraoperative surgical variables, such as lower leg alignment, soft tissue balance, joint-line maintenance, and component alignment and positioning, have been associated with improved survivorship and functional outcomes. Upon reviewing the available literature on robotic-assisted surgery, it becomes clear that this technique can improve the accuracy of these surgical variables and is superior to conventional manual UKA and TKA. Although larger and comparative survivorship studies are necessary to compare robotic-assisted knee arthroplasty to conventional techniques, the early results and cost-effectiveness analysis seem promising.

Unicompartmental knee arthroplasty (UKA) and total knee arthroplasty (TKA) are 2 reliable treatment options for patients with primary osteoarthritis. Recently published systematic reviews of cohort studies have shown that 10-year survivorship of medial and lateral UKA is 92% and 91%, respectively,¹ while 10-year survivorship of TKA in cohort studies is 95%.² National and annual registries show a similar trend, although the reported survivorship is lower.^1,3-7

In order to improve these survivorship rates, the surgical variables that can intraoperatively be controlled by the orthopedic surgeon have been evaluated. These variables include lower leg alignment, soft tissue balance, joint line maintenance, and alignment, size, and fixation of the tibial and femoral component. Several studies have shown that tight control of lower leg alignment,^8-14 balancing of the soft tissues,^15-19 joint line maintenance,^20-23 component alignment,^24-28 component size,^29-34 and component fixation^35-40 can improve the outcomes of UKA and TKA. As a result, over the past 2 decades, several computer-assisted surgery systems have been developed with the goal of more accurate and reliable control of these factors, and thus improved outcomes of knee arthroplasty.

These systems differ with regard to the number and type of variables they control. Computer navigation systems aim to control one or more of these surgical variables, and several meta-analyses have shown that these systems, when compared to conventional surgery, improve mechanical axis accuracy, decrease the risk for mechanical axis outliers, and improve component positioning in TKA^41-49 and UKA surgery.^50,51 Interestingly, however, meta-analyses have failed to show the expected superiority in clinical outcomes following computer navigation compared to conventional knee arthroplasty.^48,52-55 Furthermore, authors have shown that, despite the fact that computer-navigated surgery increases the accuracy of mechanical alignment and surgical cutting, there is still room for improvement.⁵⁶ As a consequence, robotic-assisted systems have been developed.

Similar to computer navigation, these robotic-assisted systems aim to control the surgical variables; in addition, they aim to improve the surgical precision of the procedure. Interestingly, 2 recent studies have shown that robotic-assisted systems are superior to computer navigation systems with regard to less cutting time and less resection deviations in coronal and sagittal plane in a cadaveric study,⁵⁷ and shorter total surgery time, more accurate mechanical axis, and shorter hospital stay in a clinical study.⁵⁸ Although these results are promising, the exact role of robotic surgery in knee arthroplasty remains unclear. In this review, we aim to report the current state of robotic-assisted knee arthroplasty by discussing (1) the different robotic-assisted knee arthroplasty systems that are available for UKA and TKA surgery, (2) studies that assessed the role of robotic-assisted knee arthroplasty in controlling the aforementioned surgical variables, (3) cadaveric and clinical comparative studies that compared how accurate robotic-assisted and conventional knee surgery control these surgical variables, and (4) studies that assessed the cost-effectiveness of robotic-assisted knee arthroplasty surgery.

Robotic-Assisted Knee Arthroplasty Systems

Several systems have been developed over the years for knee arthroplasty, and these are usually defined as active, semi-active, or passive.⁵⁹ Active systems are capable of performing tasks or processes autonomously under the watchful eye of the surgeon, while passive systems do not perform actions independently but provide the surgeon with information. In semi-active systems, the surgical action is physically constrained in order to follow a predefined strategy.

In the United States, 3 robotic systems are FDA-approved for knee arthroplasty. The Stryker/Mako haptic guided robot (Mako Surgical Corp.) was introduced in 2005 and has been used for over 50,000 UKA procedures (Figure 1). There are nearly 300 robotic systems used nationally, as it has 20% of the market share for UKA in the United States. The Mako system is a semi-active tactile robotic system that requires preoperative imaging, after which a preoperative planning is performed. Intraoperatively, the robotic arm is under direct surgeon control and gives real-time tactile feedback during the procedure (Figure 2).

Furthermore, the surgeon can intraoperatively virtually adjust component positioning and alignment and move the knee through the range of motion, after which the system can provide information on alignment, component position, and balance of the soft tissue (eg, if the knee is overtight or lax through the flexion-arch).⁶⁰ This system has a burr that resects the bone and when the surgeon directs the burr outside the preplanned area, the burr stops and prevents unnecessary and unwanted resections (Figure 3).

The Navio Precision Free-Hand Sculptor (PFS) system (Blue Belt Technologies) has been used for 1500 UKA procedures, with 50 robots in use in the United States (Figure 4). This system is an image-free semi-active robotic system and has the same characteristics as the aforementioned Mako system.⁶¹ Finally, the OmniBotic robotic system (Omnilife Science) has been released for TKA and has been used for over 7300 procedures (Figure 5). This system has an automated cutting-guide technique in which the surgeon designs a virtual plan on the computer system. After this, the cutting-guides are placed by the robotic system at the planned location for all 5 femoral cuts (ie, distal, anterior chamfer, anterior, posterior chamfer, and posterior) and the surgeon then makes the final cuts.^57,62

Three robotic systems for knee arthroplasty surgery have been used in Europe. The Caspar system (URS Ortho) is an active robotic system in which a computed tomography (CT) scan is performed preoperatively, after which a virtual implantation is performed on the screen. The surgeon can then obtain information on lower leg alignment, gap balancing, and component positioning, and after an operative plan is made, the surgical resections are performed by the robot. Reflective markers are attached to the leg and all robotic movements are monitored using an infrared camera system. Any undesired motion will be detected by this camera system and will stop all movements.⁶³ A second and more frequently reported system in the literature is the active Robodoc surgical system (Curexo Technology Corporation). This system is designed for TKA and total hip arthroplasty (THA) surgery. Although initial studies reported a high incidence of system-related complications in THA,⁶⁴ the use of this system for TKA has frequently been reported in the literature.^56,63,65-69 A third robotic system that has been used in Europe is the Acrobot surgical system (Acrobot Company Ltd), which is an image-based semi-active robotic system⁷⁰ used for both UKA and TKA surgery.^70,71

Accuracy of Controlling Surgical Variables in Robotic-Assisted Knee Arthroplasty

Several studies have assessed the accuracy of robotic-assisted surgery in UKA surgery with regard to control of the aforementioned surgical variables. Pearle and colleagues⁷² assessed the mechanical axis accuracy of the Mako system in 10 patients undergoing medial UKA robotic-assisted surgery. They reported that the intraoperative registration lasted 7.5 minutes and the duration of time needed for robotic-assisted burring was 34.8 minutes. They compared the actual postoperative alignment at 6 weeks follow-up with the planned lower leg alignment and found that all measurements were within 1.6° of the planned lower leg alignment. Dunbar and colleagues⁷³ assessed the accuracy of component positioning of the Mako system in 20 patients undergoing medial UKA surgery by comparing preoperative and postoperative 3-dimensional CT scans. They found that the femoral component was within 0.8 mm and 0.9° in all directions and that the tibial component was within 0.9 mm and 1.7° in all directions. They concluded that the accuracy of component positioning with the Mako system was excellent. Finally, Plate and colleagues¹⁷ assessed the accuracy of soft tissue balancing in the Mako system in 52 patients undergoing medial UKA surgery. They compared the balance plan with the soft tissue balance after implantation and the Mako system quantified soft tissue balance as the amount of mm of the knee being tight or loose at 0°, 30°, 60°, 90°, and 110° of flexion. They found that at all flexion angles the ligament balancing was accurate up to 0.53 mm of the original plan. Furthermore, they noted that in 83% of cases the accuracy was within 1 mm at all flexion angles.

For the Navio system, Smith and colleagues⁷⁴ assessed the accuracy of component positioning using 20 synthetic femurs and tibia. They reported a maximum rotational error of 3.2°, an angular error of 1.46° in all orientations, and a maximum translational error of 1.18 mm for both the tibial and femoral implants. Lonner and colleagues⁷⁵ assessed the accuracy of component positioning in 25 cadaveric specimens. They found similar results as were found in the study of Smith and colleagues⁷⁴ and concluded that these results were similar to other semi-active robotic systems designed for UKA.

For TKA surgery, Ponder and colleagues⁷⁶ assessed the accuracy of the OmniBotic system and found that the average error in the anterior-posterior dimension between the targeted and measured cuts was -0.14 mm, and that the standard deviation in guide positioning for the distal, anterior chamfer, and posterior chamfer resections was 0.03° and 0.17 mm. Koenig and colleagues⁶² assessed the accuracy of the OmniBotic system in the first 100 cases and found that 98% of the cases were within 3° of the neutral mechanical axis. Furthermore, they found a learning curve with regard to tourniquet time between the first and second 10 patients in which they performed robotic-assisted TKA surgery. Siebert and colleagues⁶³ assessed the accuracy of mechanical alignment in the Caspar system in 70 patients treated with the robotic system. They found that the difference between preoperatively planned and postoperatively achieved mechanical alignment was 0.8°. Similarly, Bellemans and colleagues⁷⁷ assessed mechanical alignment and the positioning and rotation of the tibial and femoral components in a clinical study of 25 cases using the Caspar system. They noted that none of the patients had mechanical alignment, tibial or femoral component positioning, or rotation beyond 1° of the neutral axis. Liow and colleagues⁵⁶ assessed the accuracy of mechanical axis alignment and component sizing accuracy using the Robodoc system in 25 patients. They reported that the mean postoperative alignment was 0.4° valgus and that all cases were within 3° of the neutral mechanical axis. Furthermore, they reported a mean surgical time of 96 minutes and reported that preoperative planning yielded femoral and tibial component size accuracy of 100%.

These studies have shown that robotic systems for UKA and TKA are accurate in the surgical variables they aim to control. These studies validated tight control of mechanical axis alignment, decrease for outliers, and component positioning and rotation, and also found that the balancing of soft tissues was improved using robotic-assisted surgery.

Robotic-Assisted vs Conventional Knee Arthroplasty

Despite the fact that these systems are accurate in the variables they aim to control, these systems have to be compared to the gold standard of conventional knee arthroplasty. For UKA, Cobb and colleagues⁷⁰ performed a randomized clinical trial for patients treated undergoing UKA with robotic-assistance of the Acrobot systems compared to conventional UKA and assessed differences in mechanical accuracy. A total of 27 patients were randomly assigned to one of both treatments. They found that in the group of robotic-assisted surgery, 100% of the patients had a mechanical axis within 2° of neutral, while this was only 40% in the conventional UKA groups (difference P < .001). They also assessed the increase in functional outcomes and noted a trend towards improvement in performance with increasing accuracy at 6 weeks and 3 months postoperatively. Lonner and colleagues⁷⁸ also compared the tibial component positioning between robotic-assisted UKA surgery using the Mako system and conventional UKA surgery. The authors found that the variance in tibial slope, in coronal plane of the tibial component, and varus/valgus alignment were all larger with conventional UKA when compared to robotic-assisted UKA. Citak and colleagues⁷⁹ compared the accuracy of tibial and femoral implant positioning between robotic-assisted surgery using the Mako system and conventional UKA in a cadaveric study. They reported that the root mean square (RMS) error of femoral component was 1.9 mm and 3.7° in robotic-assisted surgery and 5.4 mm and 10.2° for conventional UKA, while the RMS error for tibial component were 1.4 mm and 5.0° for robotic-assisted surgery and 5.7 mm and 19.2° for conventional UKA surgery. MacCallum and colleagues⁸⁰ compared the tibial base plate position in a prospective clinical study of 177 patients treated with conventional UKA and 87 patients treated with robotic-assisted surgery using the Mako system. They found that surgery with robotic-assistance was more precise in the coronal and sagittal plane and was more accurate in coronal alignment when compared to conventional UKA. Finally, the first results of robotic-assisted UKA surgery have been presented. Coon and colleagues⁸¹ reported the preliminary results of a multicenter study of 854 patients and found a survivorship of 98.9% and satisfaction rate of 92% at minimum 2-year follow-up. Comparing these results to other large conventional UKA cohorts^82,83 suggests that robotic-assisted surgery may improve survivorship at short-term follow-up. However, comparative studies and studies with longer follow-up are necessary to assess the additional value of robotic-assisted UKA surgery. Due to the relatively new concept of robotic-assisted surgery, these studies have not been performed or published yet.

For TKA, several studies also have compared how these robotic-systems control the surgical variables compared to conventional TKA surgery. Siebert and colleagues⁶³ assessed mechanical axis accuracy and mechanical outliers following robotic-assisted TKA surgery using the Caspar system and conventional TKA surgery. They reported the difference between preoperative planned and postoperative achieved alignment was 0.8° for robotic-assisted surgery and 2.6° for conventional TKA surgery. Furthermore, they showed that 1 patient in the robotic-assisted group (1.4%) and 18 patients in the conventional TKA group (35%) had mechanical alignment greater than 3° from the neutral mechanical axis. Liow and colleagues⁵⁶ found similar differences in their prospective randomized study in which they reported that 0% outliers greater than 3° from the neutral mechanical axis were found in the robotic-assisted group while 19.4% of the patients in the conventional TKA group had mechanical axis outliers. They also assessed the joint-line outliers in both procedures and found that 3.2% had joint-line outliers greater than 5 mm in the robotic-assisted group compared to 20.6% in the conventional TKA group. Kim and colleagues⁶⁵ assessed implant accuracy in robotic-assisted surgery using the ROBODOC system and in conventional surgery and reported higher implant accuracy and fewer outliers using robotic-assisted surgery. Moon and colleagues⁶⁶ compared robotic-assisted TKA surgery using the Robodoc system with conventional TKA surgery in 10 cadavers. They found that robotic-assisted surgery had excellent precision in all planes and had better accuracy in femoral rotation alignment compared to conventional TKA surgery. Park and Lee⁶⁷ compared Robodoc robotic-assisted TKA surgery with conventional TKA surgery in a randomized clinical trial of 72 patients. They found that robotic-assisted surgery had definitive advantages in preoperative planning, accuracy of the procedure, and postoperative follow-up regarding femoral and tibial component flexion angles. Finally, Song and colleagues^68,69 performed 2 randomized clinical trials in which they compared mechanical axis alignment, component positioning, soft tissue balancing, and patient preference between conventional TKA surgery and robotic-assisted surgery using the Robodoc system. In the first study,⁶⁸ they simultaneously performed robotic-assisted surgery in one leg and conventional TKA surgery in the other leg. They found that robotic-assisted surgery resulted in less outlier in mechanical axis and component positioning. Furthermore, they found at latest follow-up of 2 years that 12 patients preferred the leg treated with robotic-assisted surgery while 6 preferred the conventional leg. Despite this finding, no significant differences in functional outcome scores were detected between both treatment options. Furthermore, they found that flexion-extension balance was achieved in 92% of patients treated with robotic-assisted TKA surgery and in 77% of patients treated with conventional TKA surgery. In the other study,⁶⁹ the authors found that more patients treated with robotic-assisted surgery had <2 mm flexion-extension gap and more satisfactory posterior cruciate ligament tension when compared to conventional surgery.

These studies have shown that robotic-assisted surgery is accurate in controlling surgical variables, such as mechanical lower leg alignment, maintaining joint-line, implant positioning, and soft tissue balancing. Furthermore, these studies have shown that controlling these variables is better than the current gold standard of manual knee arthroplasty. Until now, not many studies have assessed survivorship of robotic-assisted surgery. Furthermore, no studies have, to our knowledge, compared survivorship of robotic-assisted with conventional knee replacement surgery. Finally, studies comparing functional outcomes following robotic-assisted surgery and conventional knee arthroplasty surgery are frequently underpowered due to their small sample sizes.^68,70 Since many studies have shown that the surgical variables are more tightly controlled using robotic-assisted surgery when compared to conventional surgery, large comparative studies are necessary to assess the role of robotic-assisted surgery in functional outcomes and survivorship of UKA and TKA.

Cost-Effectiveness of Robotic-Assisted Surgery

High initial capital costs of robotic-assisted surgery is one of the factors that constitute a barrier to the widespread implementation of this technique. Multiple authors have suggested that improved implant survivorship afforded by robotic-assisted surgery may justify the expenditure from both societal and provider perspective.^84-86 Two studies have performed a cost-effectiveness analysis for UKA surgery. Swank and colleagues⁸⁴ reviewed the hospital expenditures and profits associated with robot-assisted knee arthroplasty, citing upfront costs of approximately $800,000. The authors estimated a mean per-case contribution profit of $5790 for robotic-assisted UKA, assuming an inpatient-to-outpatient ratio of 1 to 3. Based on this data, Swank and colleagues84 proposed that the capital costs of robotic-assisted UKA may be recovered in as little as 2 years when in the first 3 consecutive years 50, 70, and 90 cases were performed using robotic-assisted UKA. Moschetti and colleagues⁸⁵ recently published the first formal cost-effectiveness analysis of robotic-assisted compared to manual UKA. The authors used an annual revision risk of 0.55% for the first 2 years following robot-assisted UKA, based on the aforementioned presented data by Coon and colleagues.⁸¹ They based their data on the Mako system and assumed an initial capital expenditure of $934,728 with annual servicing costs of 10% (discounted annually) for 4 years thereafter, resulting in a total cost of the robotic system of $1.362 million. These costs were divided by the number of patients estimated to undergo robotic-assisted UKA per year, which was varied to estimate the effect of case volume on cost-effectiveness. The authors reported that robotic-assisted UKA was associated with higher lifetime costs and net utilities compared to manual UKA, at an incremental cost-effectiveness ratio of $47,180 per quality-adjusted life year (QALY) in a high-volume center. This falls well within the societal willingness-to-pay threshold of $100,000/QALY. Sensitivity analysis showed that robotic-assisted UKA is cost-effective under the following conditions: (1) centers performing at least 94 cases annually, (2) in patients younger than age 67 years, and (3) 2-year revision rate does not exceed 1.2%. While the results of this initial analysis are promising, follow-up cost-effectiveness analysis studies will be required as long-term survivorship data become available.

Conclusion

Tighter control of intraoperative surgical variables, such as lower leg alignment, soft tissue balance, joint-line maintenance, and component alignment and positioning, have been associated with improved survivorship and functional outcomes. Upon reviewing the available literature on robotic-assisted surgery, it becomes clear that this technique can improve the accuracy of these surgical variables and is superior to conventional manual UKA and TKA. Although larger and comparative survivorship studies are necessary to compare robotic-assisted knee arthroplasty to conventional techniques, the early results and cost-effectiveness analysis seem promising.

AMSTERDAM – Further evidence that acetaminophen has limited benefits in patients with osteoarthritis was presented at the World Congress on Osteoarthritis, with authors of a systematic review calling for reconsideration of guidelines recommending the common analgesic as a first-line option.

“[Acetaminophen] provides minimal short-term benefits for people with hip or knee OA,” said presenting author and rheumatologist Dr. David J. Hunter of the University of Sydney. The treatment effects for both pain relief and for improving physical function were smallest in people with knee OA, he said. “In general, the small effect sizes are unlikely to be clinically relevant,” Dr. Hunter observed.

“These are mean differences across large populations in the clinical trials, and there may be certain individuals with knee or hip osteoarthritis that this may not necessarily apply to,” he conceded during a discussion following his presentation, “but I think from the perspective of the recommendations that come from guidelines, we have got to think about what would be do-able in the general population.”

The findings come shortly after the publication of a large meta-analysis of 74 trials evaluating pain-relieving medications that highlighted the ineffectiveness of acetaminophen for OA pain, particularly when compared against diclofenac and other nonsteroidal anti-inflammatory drugs (Lancet. 2016 Mar 17. doi: 10.1016/S0140-6736(16)30002-2).

Dr. Hunter and coworkers searched clinical trial and medical databases from inception to September 2015 for records relating to acetaminophen use in patients with hip or knee OA. Only placebo-controlled, randomized trials were included, and nine records were found that reported 10 trials involving 3,541 patients. Part of the analysis was published in the BMJ last year (BMJ. 2015;350:h1225. doi: 10.1136/bmj.h1225). The last prior systematic review on the topic was published in 2004 (Ann Rheum Dis. 2004;Aug;63[8]:901–7).

Pain scores were converted to a common 0-100 scale with 0 signifying no pain or disability and 100 the worst possible pain or disability and then expressed as a mean difference between the acetaminophen and placebo groups. Physical function scores were pooled to give a standardized mean difference.

There was high-quality evidence that acetaminophen given at a dose of 3-4 g per day had a significant effect on pain and physical function during a short period of more than 2 weeks to less than 3 months and a more immediate time frame of 2 weeks or less, but it was unlikely to be clinically significant, with a mean difference of just –3.14 for pain and a standardized mean difference of –0.12 to –0.15 for physical function. Differences would need to be at least 9 points for pain and greater than 0.2 for physical function to be clinically significant, Dr. Hunter explained.

Four of the trials considered knee OA only. The mean and standardized mean differences between the acetaminophen and placebo groups in those trials was just –1.09 for pain and –0.06 for physical function.

Similar numbers of patients reported being adherent to their assigned treatment group, with less rescue analgesic use in the acetaminophen-treated patients. Although no differences in adverse events, serious adverse events, or withdrawals because of adverse events were seen, there was a higher risk of liver function test (LFT) abnormalities in the acetaminophen-treated patients. The relative risk for abnormal LFTs was 3.79, but the clinical significance of this is uncertain according to the review’s authors.

“Current guidelines consistently recommend [acetaminophen] as the first line of analgesic medication for this condition,” Dr. Hunter said at the meeting, sponsored by the Osteoarthritis Research Society International. “But these results call for reconsideration of these recommendations.”

The results highlight the importance of using other, nonpharmacologic means to manage pain and physical function, the authors conclude, such as lifestyle changes, weight control, and regular physical exercise.

Dr. Hunter had no disclosures relevant to his comments.

AMSTERDAM – Further evidence that acetaminophen has limited benefits in patients with osteoarthritis was presented at the World Congress on Osteoarthritis, with authors of a systematic review calling for reconsideration of guidelines recommending the common analgesic as a first-line option.

“[Acetaminophen] provides minimal short-term benefits for people with hip or knee OA,” said presenting author and rheumatologist Dr. David J. Hunter of the University of Sydney. The treatment effects for both pain relief and for improving physical function were smallest in people with knee OA, he said. “In general, the small effect sizes are unlikely to be clinically relevant,” Dr. Hunter observed.

“These are mean differences across large populations in the clinical trials, and there may be certain individuals with knee or hip osteoarthritis that this may not necessarily apply to,” he conceded during a discussion following his presentation, “but I think from the perspective of the recommendations that come from guidelines, we have got to think about what would be do-able in the general population.”

The findings come shortly after the publication of a large meta-analysis of 74 trials evaluating pain-relieving medications that highlighted the ineffectiveness of acetaminophen for OA pain, particularly when compared against diclofenac and other nonsteroidal anti-inflammatory drugs (Lancet. 2016 Mar 17. doi: 10.1016/S0140-6736(16)30002-2).

Dr. Hunter and coworkers searched clinical trial and medical databases from inception to September 2015 for records relating to acetaminophen use in patients with hip or knee OA. Only placebo-controlled, randomized trials were included, and nine records were found that reported 10 trials involving 3,541 patients. Part of the analysis was published in the BMJ last year (BMJ. 2015;350:h1225. doi: 10.1136/bmj.h1225). The last prior systematic review on the topic was published in 2004 (Ann Rheum Dis. 2004;Aug;63[8]:901–7).

Pain scores were converted to a common 0-100 scale with 0 signifying no pain or disability and 100 the worst possible pain or disability and then expressed as a mean difference between the acetaminophen and placebo groups. Physical function scores were pooled to give a standardized mean difference.

There was high-quality evidence that acetaminophen given at a dose of 3-4 g per day had a significant effect on pain and physical function during a short period of more than 2 weeks to less than 3 months and a more immediate time frame of 2 weeks or less, but it was unlikely to be clinically significant, with a mean difference of just –3.14 for pain and a standardized mean difference of –0.12 to –0.15 for physical function. Differences would need to be at least 9 points for pain and greater than 0.2 for physical function to be clinically significant, Dr. Hunter explained.

Four of the trials considered knee OA only. The mean and standardized mean differences between the acetaminophen and placebo groups in those trials was just –1.09 for pain and –0.06 for physical function.

Similar numbers of patients reported being adherent to their assigned treatment group, with less rescue analgesic use in the acetaminophen-treated patients. Although no differences in adverse events, serious adverse events, or withdrawals because of adverse events were seen, there was a higher risk of liver function test (LFT) abnormalities in the acetaminophen-treated patients. The relative risk for abnormal LFTs was 3.79, but the clinical significance of this is uncertain according to the review’s authors.

“Current guidelines consistently recommend [acetaminophen] as the first line of analgesic medication for this condition,” Dr. Hunter said at the meeting, sponsored by the Osteoarthritis Research Society International. “But these results call for reconsideration of these recommendations.”

The results highlight the importance of using other, nonpharmacologic means to manage pain and physical function, the authors conclude, such as lifestyle changes, weight control, and regular physical exercise.

Dr. Hunter had no disclosures relevant to his comments.

AMSTERDAM – Further evidence that acetaminophen has limited benefits in patients with osteoarthritis was presented at the World Congress on Osteoarthritis, with authors of a systematic review calling for reconsideration of guidelines recommending the common analgesic as a first-line option.

“[Acetaminophen] provides minimal short-term benefits for people with hip or knee OA,” said presenting author and rheumatologist Dr. David J. Hunter of the University of Sydney. The treatment effects for both pain relief and for improving physical function were smallest in people with knee OA, he said. “In general, the small effect sizes are unlikely to be clinically relevant,” Dr. Hunter observed.

“These are mean differences across large populations in the clinical trials, and there may be certain individuals with knee or hip osteoarthritis that this may not necessarily apply to,” he conceded during a discussion following his presentation, “but I think from the perspective of the recommendations that come from guidelines, we have got to think about what would be do-able in the general population.”

The findings come shortly after the publication of a large meta-analysis of 74 trials evaluating pain-relieving medications that highlighted the ineffectiveness of acetaminophen for OA pain, particularly when compared against diclofenac and other nonsteroidal anti-inflammatory drugs (Lancet. 2016 Mar 17. doi: 10.1016/S0140-6736(16)30002-2).

Dr. Hunter and coworkers searched clinical trial and medical databases from inception to September 2015 for records relating to acetaminophen use in patients with hip or knee OA. Only placebo-controlled, randomized trials were included, and nine records were found that reported 10 trials involving 3,541 patients. Part of the analysis was published in the BMJ last year (BMJ. 2015;350:h1225. doi: 10.1136/bmj.h1225). The last prior systematic review on the topic was published in 2004 (Ann Rheum Dis. 2004;Aug;63[8]:901–7).

Pain scores were converted to a common 0-100 scale with 0 signifying no pain or disability and 100 the worst possible pain or disability and then expressed as a mean difference between the acetaminophen and placebo groups. Physical function scores were pooled to give a standardized mean difference.

There was high-quality evidence that acetaminophen given at a dose of 3-4 g per day had a significant effect on pain and physical function during a short period of more than 2 weeks to less than 3 months and a more immediate time frame of 2 weeks or less, but it was unlikely to be clinically significant, with a mean difference of just –3.14 for pain and a standardized mean difference of –0.12 to –0.15 for physical function. Differences would need to be at least 9 points for pain and greater than 0.2 for physical function to be clinically significant, Dr. Hunter explained.

Four of the trials considered knee OA only. The mean and standardized mean differences between the acetaminophen and placebo groups in those trials was just –1.09 for pain and –0.06 for physical function.

Similar numbers of patients reported being adherent to their assigned treatment group, with less rescue analgesic use in the acetaminophen-treated patients. Although no differences in adverse events, serious adverse events, or withdrawals because of adverse events were seen, there was a higher risk of liver function test (LFT) abnormalities in the acetaminophen-treated patients. The relative risk for abnormal LFTs was 3.79, but the clinical significance of this is uncertain according to the review’s authors.

“Current guidelines consistently recommend [acetaminophen] as the first line of analgesic medication for this condition,” Dr. Hunter said at the meeting, sponsored by the Osteoarthritis Research Society International. “But these results call for reconsideration of these recommendations.”

The results highlight the importance of using other, nonpharmacologic means to manage pain and physical function, the authors conclude, such as lifestyle changes, weight control, and regular physical exercise.

Dr. Hunter had no disclosures relevant to his comments.

AMSTERDAM – Patients with milder knee osteoarthritis symptoms or better quality of life before undergoing total knee replacement surgery gained less benefit from the surgery than did those who had more severe symptoms in two separate analyses of British and U.S. patients.

Additional evidence from total knee replacements (TKRs) performed on U.S. participants of the Osteoarthritis Initiative also suggest that as the use of TKR has increased to include less symptomatic patients, the overall cost-effectiveness of the procedure has declined.

©pixologicstudio/ thinkstockphotos.com

“Knee replacements are one of those interventions that are known to be very effective and very cost-effective,” Rafael Pinedo-Villanueva, Ph.D., of the University of Oxford (England) said during his presentation of National Health Service data from England at the World Congress on Osteoarthritis. Indeed, knee replacements are associated with significant improvements in pain, function, and quality of life, he said, but that is if you look at the mean values.

As the deciles for baseline knee pain and function decrease in severity, there are diminishing mean improvements and an increasing proportion of patients who do worse after the operation, he reported. Up to 17% of patients had unchanged or improved knee pain scores and up to 27% had lower quality of life scores. If minimally important differences were considered, these percentages rose to 40% and 48% of patients being worse off, respectively.

“The significant improvements seem to be overshadowing what happens to those patients who are doing worse,” Dr. Pinedo-Villanueva suggested. “So essentially cost-effectiveness is being driven by the magnitude of the change in those who do improve, and we don’t really see much about what is happening to those who are doing worse.”

Of over 215,000 records of knee replacement collected from all patients undergoing TKR in England during 2008-2012, Dr. Pinedo-Villanueva and his study coauthors found 117,844 had data on pre- and post-operative knee pain assessed using the Oxford Knee Score (OKS) and quality of life measured with the EQ-5D instrument. The majority of replacements were in women (55%) and almost three quarters of patients had one or no comorbidities. Overall, the mean change in OKS was 15 points, improving from 19 to 34 (the higher the score the lesser the knee pain). EQ-5D scores also improved by a mean difference of 0.30 (from 0.41 to 0.70 where 1.0 is perfect health). Although the vast majority of patients had improved OKS and EQ-5D scores after surgery, unchanged or decreased scores were seen in 8% and 22% of patients, respectively.

“As we breakdown these data by deciles of baseline pain and function we see clearly that those starting at the lower decile improved the most, and that’s to be expected; they’ve a lot more to improve than the ones that came into the operation at the higher decile,” Dr. Pinedo-Villanueva said at the Congress, sponsored by the Osteoarthritis Research Society International. But there were patients who fared worse at every decile, he noted.

Dr. Pinedo-Villanueva concluded that outcome prediction models were needed to try to reduce the number of patients who are apparently worse off after knee replacement and improve the efficiency of resource allocation.

The value of TKR in a contemporary U.S. population was the focus of a separate presentation by Dr. Bart Ferket of Mount Sinai Hospital in New York. Dr. Ferket reported the results of a study looking at the impact of TKR on patients’ quality of life, lifetime costs, and quality-adjusted life years (QALYs) while varying the use of TKR by patients’ functional status at baseline.

“In the United States, the rate at which total knee replacement is performed has doubled in the last two decades,” Dr. Ferket observed. This “disproportionate” increase has been attributed to expanding the eligibility criteria to include less symptomatic patients.

Using data collected over an 8-year period on 1,327 participants from the Osteoarthritis Initiative, Dr. Ferket and his associates at Mount Sinai and Erasmus University Medical Center in Rotterdam (The Netherlands) discovered that the increased uptake of TKR might have affected the likely benefit and reduced the overall cost-effectiveness of the procedure.

At baseline, 17% of the participants, who all had knee osteoarthritis, had had a prior knee replacement.

Quality of life measured on the physical component scores (PCS) of the 12-item Short Form (SF-12) were generally improved after TKR but decreased in those who did not have a knee replaced. The effect on the mental component of the SF-12 was less clear, with possibly a decrease seen in some patients. Changes on the Western Ontario and McMaster Universities Arthritis Index (WOMAC) and Knee injury and Osteoarthritis Outcome Score (KOOS) showed a considerable benefit for knee replacement and there was a general decrease in pain medication over time in those who had surgery. The overall effect was more pronounced if patients with greater baseline symptoms were considered.

Cost-effectiveness modeling showed that reserving TKR for more seriously affected patients may make it more economically attractive. The QALYs gained from TKR was about 11 but as the number of QALYs increased, so did the relative lifetime cost, with increasing incremental cost-effectiveness ratios (ICERs) as SF-12 PCS rose. ICERs were around $143,000, $160,000, $217,000, $385,000, and $1,175,000 considering patients with SF-12 PCS of less than 30, 35, 40, 45, and 50, respectively.

“The more lenient the eligibility criteria are, the higher the effectiveness, but also the higher the costs,” Dr. Ferket said. “The most cost-effective scenarios are actually more restrictive that what is currently seen in current practice in the U.S.”

Dr. Pinedo-Villanueva and Dr. Ferket reported having no financial disclosures.

AMSTERDAM – Patients with milder knee osteoarthritis symptoms or better quality of life before undergoing total knee replacement surgery gained less benefit from the surgery than did those who had more severe symptoms in two separate analyses of British and U.S. patients.

Additional evidence from total knee replacements (TKRs) performed on U.S. participants of the Osteoarthritis Initiative also suggest that as the use of TKR has increased to include less symptomatic patients, the overall cost-effectiveness of the procedure has declined.

©pixologicstudio/ thinkstockphotos.com

“Knee replacements are one of those interventions that are known to be very effective and very cost-effective,” Rafael Pinedo-Villanueva, Ph.D., of the University of Oxford (England) said during his presentation of National Health Service data from England at the World Congress on Osteoarthritis. Indeed, knee replacements are associated with significant improvements in pain, function, and quality of life, he said, but that is if you look at the mean values.

As the deciles for baseline knee pain and function decrease in severity, there are diminishing mean improvements and an increasing proportion of patients who do worse after the operation, he reported. Up to 17% of patients had unchanged or improved knee pain scores and up to 27% had lower quality of life scores. If minimally important differences were considered, these percentages rose to 40% and 48% of patients being worse off, respectively.

“The significant improvements seem to be overshadowing what happens to those patients who are doing worse,” Dr. Pinedo-Villanueva suggested. “So essentially cost-effectiveness is being driven by the magnitude of the change in those who do improve, and we don’t really see much about what is happening to those who are doing worse.”

Of over 215,000 records of knee replacement collected from all patients undergoing TKR in England during 2008-2012, Dr. Pinedo-Villanueva and his study coauthors found 117,844 had data on pre- and post-operative knee pain assessed using the Oxford Knee Score (OKS) and quality of life measured with the EQ-5D instrument. The majority of replacements were in women (55%) and almost three quarters of patients had one or no comorbidities. Overall, the mean change in OKS was 15 points, improving from 19 to 34 (the higher the score the lesser the knee pain). EQ-5D scores also improved by a mean difference of 0.30 (from 0.41 to 0.70 where 1.0 is perfect health). Although the vast majority of patients had improved OKS and EQ-5D scores after surgery, unchanged or decreased scores were seen in 8% and 22% of patients, respectively.

“As we breakdown these data by deciles of baseline pain and function we see clearly that those starting at the lower decile improved the most, and that’s to be expected; they’ve a lot more to improve than the ones that came into the operation at the higher decile,” Dr. Pinedo-Villanueva said at the Congress, sponsored by the Osteoarthritis Research Society International. But there were patients who fared worse at every decile, he noted.

Dr. Pinedo-Villanueva concluded that outcome prediction models were needed to try to reduce the number of patients who are apparently worse off after knee replacement and improve the efficiency of resource allocation.

The value of TKR in a contemporary U.S. population was the focus of a separate presentation by Dr. Bart Ferket of Mount Sinai Hospital in New York. Dr. Ferket reported the results of a study looking at the impact of TKR on patients’ quality of life, lifetime costs, and quality-adjusted life years (QALYs) while varying the use of TKR by patients’ functional status at baseline.

“In the United States, the rate at which total knee replacement is performed has doubled in the last two decades,” Dr. Ferket observed. This “disproportionate” increase has been attributed to expanding the eligibility criteria to include less symptomatic patients.

Using data collected over an 8-year period on 1,327 participants from the Osteoarthritis Initiative, Dr. Ferket and his associates at Mount Sinai and Erasmus University Medical Center in Rotterdam (The Netherlands) discovered that the increased uptake of TKR might have affected the likely benefit and reduced the overall cost-effectiveness of the procedure.

At baseline, 17% of the participants, who all had knee osteoarthritis, had had a prior knee replacement.

Quality of life measured on the physical component scores (PCS) of the 12-item Short Form (SF-12) were generally improved after TKR but decreased in those who did not have a knee replaced. The effect on the mental component of the SF-12 was less clear, with possibly a decrease seen in some patients. Changes on the Western Ontario and McMaster Universities Arthritis Index (WOMAC) and Knee injury and Osteoarthritis Outcome Score (KOOS) showed a considerable benefit for knee replacement and there was a general decrease in pain medication over time in those who had surgery. The overall effect was more pronounced if patients with greater baseline symptoms were considered.

Cost-effectiveness modeling showed that reserving TKR for more seriously affected patients may make it more economically attractive. The QALYs gained from TKR was about 11 but as the number of QALYs increased, so did the relative lifetime cost, with increasing incremental cost-effectiveness ratios (ICERs) as SF-12 PCS rose. ICERs were around $143,000, $160,000, $217,000, $385,000, and $1,175,000 considering patients with SF-12 PCS of less than 30, 35, 40, 45, and 50, respectively.

“The more lenient the eligibility criteria are, the higher the effectiveness, but also the higher the costs,” Dr. Ferket said. “The most cost-effective scenarios are actually more restrictive that what is currently seen in current practice in the U.S.”

Dr. Pinedo-Villanueva and Dr. Ferket reported having no financial disclosures.

AMSTERDAM – Patients with milder knee osteoarthritis symptoms or better quality of life before undergoing total knee replacement surgery gained less benefit from the surgery than did those who had more severe symptoms in two separate analyses of British and U.S. patients.

Additional evidence from total knee replacements (TKRs) performed on U.S. participants of the Osteoarthritis Initiative also suggest that as the use of TKR has increased to include less symptomatic patients, the overall cost-effectiveness of the procedure has declined.

©pixologicstudio/ thinkstockphotos.com

“Knee replacements are one of those interventions that are known to be very effective and very cost-effective,” Rafael Pinedo-Villanueva, Ph.D., of the University of Oxford (England) said during his presentation of National Health Service data from England at the World Congress on Osteoarthritis. Indeed, knee replacements are associated with significant improvements in pain, function, and quality of life, he said, but that is if you look at the mean values.

As the deciles for baseline knee pain and function decrease in severity, there are diminishing mean improvements and an increasing proportion of patients who do worse after the operation, he reported. Up to 17% of patients had unchanged or improved knee pain scores and up to 27% had lower quality of life scores. If minimally important differences were considered, these percentages rose to 40% and 48% of patients being worse off, respectively.

“The significant improvements seem to be overshadowing what happens to those patients who are doing worse,” Dr. Pinedo-Villanueva suggested. “So essentially cost-effectiveness is being driven by the magnitude of the change in those who do improve, and we don’t really see much about what is happening to those who are doing worse.”

Of over 215,000 records of knee replacement collected from all patients undergoing TKR in England during 2008-2012, Dr. Pinedo-Villanueva and his study coauthors found 117,844 had data on pre- and post-operative knee pain assessed using the Oxford Knee Score (OKS) and quality of life measured with the EQ-5D instrument. The majority of replacements were in women (55%) and almost three quarters of patients had one or no comorbidities. Overall, the mean change in OKS was 15 points, improving from 19 to 34 (the higher the score the lesser the knee pain). EQ-5D scores also improved by a mean difference of 0.30 (from 0.41 to 0.70 where 1.0 is perfect health). Although the vast majority of patients had improved OKS and EQ-5D scores after surgery, unchanged or decreased scores were seen in 8% and 22% of patients, respectively.

“As we breakdown these data by deciles of baseline pain and function we see clearly that those starting at the lower decile improved the most, and that’s to be expected; they’ve a lot more to improve than the ones that came into the operation at the higher decile,” Dr. Pinedo-Villanueva said at the Congress, sponsored by the Osteoarthritis Research Society International. But there were patients who fared worse at every decile, he noted.

Dr. Pinedo-Villanueva concluded that outcome prediction models were needed to try to reduce the number of patients who are apparently worse off after knee replacement and improve the efficiency of resource allocation.

The value of TKR in a contemporary U.S. population was the focus of a separate presentation by Dr. Bart Ferket of Mount Sinai Hospital in New York. Dr. Ferket reported the results of a study looking at the impact of TKR on patients’ quality of life, lifetime costs, and quality-adjusted life years (QALYs) while varying the use of TKR by patients’ functional status at baseline.

“In the United States, the rate at which total knee replacement is performed has doubled in the last two decades,” Dr. Ferket observed. This “disproportionate” increase has been attributed to expanding the eligibility criteria to include less symptomatic patients.

Using data collected over an 8-year period on 1,327 participants from the Osteoarthritis Initiative, Dr. Ferket and his associates at Mount Sinai and Erasmus University Medical Center in Rotterdam (The Netherlands) discovered that the increased uptake of TKR might have affected the likely benefit and reduced the overall cost-effectiveness of the procedure.

At baseline, 17% of the participants, who all had knee osteoarthritis, had had a prior knee replacement.

Quality of life measured on the physical component scores (PCS) of the 12-item Short Form (SF-12) were generally improved after TKR but decreased in those who did not have a knee replaced. The effect on the mental component of the SF-12 was less clear, with possibly a decrease seen in some patients. Changes on the Western Ontario and McMaster Universities Arthritis Index (WOMAC) and Knee injury and Osteoarthritis Outcome Score (KOOS) showed a considerable benefit for knee replacement and there was a general decrease in pain medication over time in those who had surgery. The overall effect was more pronounced if patients with greater baseline symptoms were considered.

Cost-effectiveness modeling showed that reserving TKR for more seriously affected patients may make it more economically attractive. The QALYs gained from TKR was about 11 but as the number of QALYs increased, so did the relative lifetime cost, with increasing incremental cost-effectiveness ratios (ICERs) as SF-12 PCS rose. ICERs were around $143,000, $160,000, $217,000, $385,000, and $1,175,000 considering patients with SF-12 PCS of less than 30, 35, 40, 45, and 50, respectively.

“The more lenient the eligibility criteria are, the higher the effectiveness, but also the higher the costs,” Dr. Ferket said. “The most cost-effective scenarios are actually more restrictive that what is currently seen in current practice in the U.S.”

Dr. Pinedo-Villanueva and Dr. Ferket reported having no financial disclosures.

Injuries among professional baseball players have been on the rise for several years.^1,2 From 1989 to 1999, the number of disabled list (DL) reports increased 38% (266 to 367 annual reports),¹ and a similar increase in injury rates was noted from the 2002 to the 2008 seasons (37%).² These injuries have important implications for future injury risk and time away from play. Identifying these injuries and determining correlates and risk factors is important for targeted prevention efforts.

Several studies have explored the prevalence of upper extremity injuries in professional and collegiate baseball players;^2-4 however, detailed epidemiology of knee injuries in Major League Baseball (MLB) and Minor League Baseball (MiLB) players is lacking. Much more is known about the prevalence, treatment, and outcomes of knee injuries in other professional sporting organizations, such as the National Basketball Association (NBA), National Football League (NFL), and National Hockey League (NHL).^4-12 A recent meta-analysis exploring injuries in professional athletes found that studies on lower extremity injuries comprised approximately 12% of the literature reporting injuries in MLB players.⁴ In other professional leagues, publications on lower extremity injuries comprise approximately 56% of the sports medicine literature in the NFL, 54% in the NBA, and 62% in the NHL.⁴ Since few studies have investigated lower extremity injuries among professional baseball players, there is an opportunity for additional research to guide evidence-based prevention strategies.

A better understanding of the nature of these injuries is one of the first steps towards developing targeted injury prevention programs and treatment algorithms. The study of injury epidemiology among professional baseball players has been aided by the creation of an injury tracking system initiated by the MLB, its minor league affiliates, and the Major League Baseball Players Association.^5,13,14 This surveillance system allows for the tracking of medical histories and injuries to players as they move across major and minor league organizations. Similar systems have been utilized in the National Collegiate Athletic Association and other professional sports organizations.^3,15-17 A unique advantage of the MLB surveillance system is the required participation of all major and minor league teams, which allows for investigation of the entire population of players rather than simply a sample of players from select teams. This system has propelled an effort to identify injury patterns as a means of developing appropriate targets for potential preventative measures.⁵

The purpose of this descriptive epidemiologic study is to better understand the distribution and characteristics of knee injuries in these elite athletes by reporting on all knee injuries occurring over a span of 4 seasons (2011-2014). Additionally, this study seeks to characterize the impact of these injuries by analyzing the time required for return to play and the treatments rendered (surgical and nonsurgical).

Materials and Methods

After approval from the Johns Hopkins Bloomberg School of Public Health Institutional Review Board, detailed data regarding knee injuries in both MLB and MiLB baseball players were extracted from the de-identified MLB Health and Injury Tracking System (HITS). The HITS database is a centralized database that contains data on injuries from an electronic medical record (EMR). All players provided consent to have their data included in this EMR. HITS system captures injuries reported by the athletic trainers for all professional baseball players from 30 MLB clubs and their 230 minor league affiliates. Additional details on this population of professional baseball players have been published elsewhere.⁵ Only injuries that result in time out of play (≥1 day missed) are included in the database, and they are logged with basic information such as region of the body, diagnosis, date, player position, activity leading to injury, and general treatment. Any injury that affects participation in any aspect of baseball-related activity (eg, game, practice, warm-up, conditioning, weight training) is captured in HITS.

All baseball-related knee injuries occurring during the 2011-2014 seasons that resulted in time out of sport were included in the study. These injuries were identified based on the Sports Medicine Diagnostic Coding System (SMDCS) to capture injuries by diagnostic groups.¹⁸ Knee injuries were included if they occurred during spring training, regular season, or postseason play. Offseason injuries were not included. Injury events that were classified as “season-ending” were not included in the analysis of days missed because many of these players may not have been cleared to play until the beginning of the following season. To determine the proportion of knee injuries during the study period, all injuries were included for comparative purposes (subdivided based on 30 anatomic regions or types).

For each knee injury, a number of variables were analyzed, including diagnosis, level of play (MLB vs. MiLB), age, player position at the time of injury (pitcher, catcher, infield, outfield, base runner, or batter), field location where the injury occurred (home plate, pitcher’s mound, infield, outfield, foul territory or bullpen, or other), mechanism of injury, days missed, and treatment rendered (conservative vs surgical). The classification used to describe the mechanism of injury consisted of contact with ball, contact with ground, contact with another player, contact with another object, or noncontact.

Statistical Analysis
Epidemiologic data are presented with descriptive statistics such as mean, median, frequency, and percentage where appropriate. When comparing player age, days missed, and surgical vs nonsurgical treatment between MLB and MiLB players, t-tests and tests for difference in proportions were applied as appropriate. Statistical significance was established for P values < .05.

The distribution of days missed for the variables considered was often skewed to the right (ie, days missed mostly concentrated on the low to moderate number of days, with fewer values in the much higher days missed range), even after excluding the season-ending injuries; hence the mean (or average) days missed was often larger than the median days missed. Reporting the median would allow for a robust estimate of the expected number of days missed, but would down weight those instances when knee injuries result in much longer missed days, as reflected by the mean. Because of the importance of the days missed measure for professional baseball, both the mean and median are presented.

In order to estimate exposure, the average number of players per team per game was calculated based on analysis of regular season game participation via box scores. This average number over a season, multiplied by the number of team games at each professional level of baseball, was used as an estimate of athlete exposures in order to provide rates comparable to those of other injury surveillance systems. Injury rates were reported as injuries per 1000 athlete-exposures (AE) for those knee injuries that occurred during the regular season. It should be noted that the number of regular season knee injuries and the subsequent AE rates are based on injuries that were deemed work-related during the regular season. This does not necessarily only include injuries occurring during the course of a game, but injuries in game preparation as well. Due to the variations in spring training games and fluctuating rosters, an exposure rate could not be calculated for spring training knee injuries.

RESULTS

Overall Summary

Of the 30 general body regions/systems included in the HITS database, injuries to the knee were the fifth most common reason for days missed in all of professional baseball from 2011-2014 (Table 1). Injuries to the knee represented 6.5% of the nearly 34,000 injuries sustained during the study period. Knee injuries were the fifth most common reason for time out of play for players in both the MiLB and MLB.

A total of 2171 isolated knee injuries resulted in time out of sport for professional baseball players (Table 2). Of these, 410 (19%) occurred in MLB players and 1761 (81%) occurred in MiLB players. MLB players were older than MiLB players at the time of injury (29.5 vs 22.8 years, respectively). Overall mean number of days missed was 16.2 days per knee injury, with MLB players missing an approximately 7 days more per injury than MiLB athletes (21.8 vs. 14.9 days respectively; P = .001).Over the course of the 4 seasons, a total of 30,449 days were missed due to knee injuries in professional baseball, giving an average rate of 7612 days lost per season. Surgery was performed for 263 (12.1%) of the 2171 knee injuries, with a greater proportion of MLB players requiring surgery than MiLB players (17.3% vs 10.9%) (P < .001). With respect to number of days missed per injury, 26% of knee injuries in the minor leagues resulted in greater than 30 days missed, while this number rose to 32% for knee injuries in MLB players (Table 3).

For regular season games, it was estimated that there were 1,197,738 MiLB and 276,608 MLB AE, respectively, over the course of the 4 seasons (2011-2014). The overall knee injury rate across both the MiLB and MLB was 1.2 per 1000 AE, based on the subset of 308 and 1473 regular season knee injuries in MiLB and MLB, respectively. The rate of knee injury was similar and not significantly different between the MiLB and MLB (1.2 per 1000 AE in the MiLB and 1.1 per 1000 AE in the MLB).

Characteristics of Injuries

When considering the position of the player during injury, defensive players were most frequently injured (n = 742, 56.5%), with pitchers (n = 227, 17.3%), infielders (n =193, 14.7%), outfielders (n = 193, 14.7%), and catchers (n = 129, 9.8%) sustaining injuries in decreasing frequency. Injuries while on offense (n = 571, 43.5%) were most frequent in base runners (n = 320, 24.4%) followed by batters (n = 251, 19.1%) (Table 4). Injuries while on defense occurring in infielders and catchers resulted in the longest period of time away from play (average of 22.4 and 20.8 days missed, respectively), while those occurring in batters resulted in the least average days missed (8.9 days).

The most common field location for knee injuries to occur was the infield, which was responsible for n = 647 (29.8%) of the total knee injuries (Table 4). This was followed by home plate (n = 493, 22.7%), other locations outside those specified (n = 394, 18.1%), outfield (n = 320, 14.7%), pitcher’s mound (n = 210, 9.7%), and foul territory or the bullpen (n = 107, 4.9%). Of the knee injuries with a specified location, those occurring in foul territory or the bullpen resulted in the highest mean days missed (18.4), while those occurring at home plate resulted in the least mean days missed (13.4 days).

When analyzed by mechanism of injury, noncontact injuries (n = 953, 43.9%) were more common than being hit with the ball (n = 374, 17.2%), striking the ground (n = 409, 18.8%), other mechanisms not listed (n = 196, 9%), contact with another player (n = 176, 8.1%), or contact with other objects (n = 63, 2.9%) (Table 4). Noncontact injuries and player to player collisions resulted in the greatest number of missed days (21.6 and 17.1 days, respectively) while being struck by the ball resulted in the least mean days missed (5.1).

Of the n = 493 knee injuries occurring at home plate, n = 212 (43%) occurred to the batter, n = 100 (20%) to the catcher, n = 34 (6.9%) to base runners, and n = 7 (1.4%) to pitchers (Table 5). The majority of knee injuries in the infield occurred to base runners (n = 283, 43.7%). Player-to-player collisions at home plate were responsible for 51 (2.3%) knee injuries, while 163 (24%) were noncontact injuries and 376 (56%) were the result of a player being hit by the ball (Table 5).

Injury Diagnosis

By diagnosis, the most common knee injuries observed were contusions or hematomas (n = 662, 30.5%), other injuries (n = 415, 19.1%), sprains or ligament injuries (n = 380, 17.5%), tendinopathies or bursitis (n = 367, 16.9%), and meniscal or cartilage injury (n = 200, 9.2%) (Table 6). Injuries resulting in the greatest mean number of days missed included meniscal or cartilage injuries (44 days), sprains or ligament injuries (30 days), or dislocations (22 days).

Based on specific SMDCS descriptors, the most frequent knee injuries reported were contusion (n = 662, 30.5%), patella tendinopathy (n = 222, 10.2%), and meniscal tears (n = 200, 9.2%) (Table 6). Complete anterior cruciate ligament tears, although infrequent, were responsible for the greatest mean days missed (156.2 days). This was followed by lateral meniscus tears (47.5 days) and medial meniscus tears (41.2 days). Knee contusions, although very common, resulted in the least number of days missed (6.0 days).

Discussion

Although much is known about knee injuries in other professional athletic leagues, little is known about knee injuries in professional baseball players.^2-4 The majority of epidemiologic studies regarding baseball players at any level emphasizes the study of shoulder and elbow injuries.^3,4,19 Since the implementation of the electronic medical record and the HITS database in professional baseball, there has been increased effort to document injuries that have received less attention in the existing literature. Understanding the epidemiology of these injuries is important for the development of targeted prevention efforts.

Prior studies of injuries in professional baseball relied on data captured by the publicly available DL. Posner and colleagues² provide one of the most comprehensive reports on MLB injuries in a report utilizing DL assignment data over a period of 7 seasons.They demonstrated that knee injuries were responsible for 7.7% (12.5% for fielders and 3.7% for pitchers) of assignments to the DL. The current study utilized a comprehensive surveillance and builds on this existing knowledge. The present study found similar trends to Posner and colleagues² in that knee injuries were responsible for 6.5% of injuries in professional baseball players that resulted in missed games. From the 2002 season to the 2008 season, knee injuries were the fifth most common reason MLB players were placed on the DL,² and the current study indicates that they remain the fifth most common reason for missed time from play based on the HITS data. Since the prevalence of these injuries have remained constant since the 2002 season, efforts to better understand these injuries are warranted in order to identify strategies to prevent them. These analyses have generated important data towards achieving this understanding.

As with most injuries in professional sports, goals for treatment are aimed at maximizing patient function and performance while minimizing time out of play. For the 2011-2014 professional baseball seasons, a total of 2171 players sustained knee injuries and missed an average of 16.2 days per injury. Knee injuries were responsible for a total of 7612 days of missed work for MLB and MiLB players per season (30,449 days over the 4-season study period). This is equivalent to a total of 20.9 years of players’ time lost in professional baseball per season over the last 4 years. The implications of this amount of time away from sport are significant, and further study should be targeted at prevention of these injuries and optimizing return to play times.

When attempting to reduce the burden of knee injuries in professional baseball, it may prove beneficial to first understand how the injuries occur, where on the field, and who is at greatest risk. From 2011 to 2014, nearly 44% of knee injuries occurred by noncontact mechanisms. Among all locations on the field where knee injuries occurred, those occurring in the infield were responsible for the greatest mean days missed. The players who seem to be at greatest risk for knee injuries appear to be base runners. These data suggest the need for prevention efforts targeting base runners and infield players, as well as players in MiLB, where the largest number of injuries occurred.

Recently, playing rules implemented by MLB after consultation with players have focused on reducing the number of player-to-player collisions at home plate in an attempt to decrease the injury burden to catchers and base runners.²⁰ This present analysis suggests that this rule change may also reduce the occurrence of knee injuries, as player collisions at home plate were responsible for a total of 51 knee injuries during the study period. The impact of this rule change on injury rates should also be explored. Interestingly, of the 51 knees injuries occurring due to contact at home plate, 23 occurred in 2011, and only 2 occurred in 2014—the first year of the new rule. Additional areas that resulted in high numbers of knee injuries were player-to-player contact in the infield and player contact with the ground in the infield.

Attempting to reduce injury burden and time out of play related to knee injuries in professional baseball players will likely prove to be a difficult task. In order to generate meaningful improvement, a comprehensive approach that involves players, management, trainers, therapists, and physicians will likely be required. As the first report of the epidemiology of knee injuries in professional baseball players, this study is one important step in that process. The strengths of this study are its comprehensive nature that analyzes injuries from an entire population of players on more than 200 teams over a 3-year period. Also, this research is strengthened by its focus on one particular region of the body that has received limited attention in the empirical literature, but represents a significant source of lost time during the baseball season.

There are some limitations to this study. As with any injury surveillance system, there is the possibility that not all cases were captured. Additionally, since the surveillance system is based on data from multiple teams, data entry discrepancy is possible; however, the presence of dropdown boxes and systematic definitions for injuries reduces this risk. Finally, this study did not investigate the various treatments for knee injuries beyond whether or not the injury required surgery. Since this was the first comprehensive exploration of knee injuries in professional baseball, future studies are needed to explore additional facets including outcomes related to treatment, return to play, and performance.

Conclusion

Knee injuries represent 6.5% of all injuries in professional baseball, occurring at a rate of 1.3 per 1000 AE. The burden of these injuries is significant for professional baseball players. This study fills a critical gap in sports injury research by contributing to the knowledge about the effect of knee injuries in professional baseball. It also provides an important foundation for future epidemiologic inquiry to identify modifiable risk factors and interventions that may reduce the impact of these injuries in athletes.

Injuries among professional baseball players have been on the rise for several years.^1,2 From 1989 to 1999, the number of disabled list (DL) reports increased 38% (266 to 367 annual reports),¹ and a similar increase in injury rates was noted from the 2002 to the 2008 seasons (37%).² These injuries have important implications for future injury risk and time away from play. Identifying these injuries and determining correlates and risk factors is important for targeted prevention efforts.

Several studies have explored the prevalence of upper extremity injuries in professional and collegiate baseball players;^2-4 however, detailed epidemiology of knee injuries in Major League Baseball (MLB) and Minor League Baseball (MiLB) players is lacking. Much more is known about the prevalence, treatment, and outcomes of knee injuries in other professional sporting organizations, such as the National Basketball Association (NBA), National Football League (NFL), and National Hockey League (NHL).^4-12 A recent meta-analysis exploring injuries in professional athletes found that studies on lower extremity injuries comprised approximately 12% of the literature reporting injuries in MLB players.⁴ In other professional leagues, publications on lower extremity injuries comprise approximately 56% of the sports medicine literature in the NFL, 54% in the NBA, and 62% in the NHL.⁴ Since few studies have investigated lower extremity injuries among professional baseball players, there is an opportunity for additional research to guide evidence-based prevention strategies.

A better understanding of the nature of these injuries is one of the first steps towards developing targeted injury prevention programs and treatment algorithms. The study of injury epidemiology among professional baseball players has been aided by the creation of an injury tracking system initiated by the MLB, its minor league affiliates, and the Major League Baseball Players Association.^5,13,14 This surveillance system allows for the tracking of medical histories and injuries to players as they move across major and minor league organizations. Similar systems have been utilized in the National Collegiate Athletic Association and other professional sports organizations.^3,15-17 A unique advantage of the MLB surveillance system is the required participation of all major and minor league teams, which allows for investigation of the entire population of players rather than simply a sample of players from select teams. This system has propelled an effort to identify injury patterns as a means of developing appropriate targets for potential preventative measures.⁵

The purpose of this descriptive epidemiologic study is to better understand the distribution and characteristics of knee injuries in these elite athletes by reporting on all knee injuries occurring over a span of 4 seasons (2011-2014). Additionally, this study seeks to characterize the impact of these injuries by analyzing the time required for return to play and the treatments rendered (surgical and nonsurgical).

Materials and Methods

After approval from the Johns Hopkins Bloomberg School of Public Health Institutional Review Board, detailed data regarding knee injuries in both MLB and MiLB baseball players were extracted from the de-identified MLB Health and Injury Tracking System (HITS). The HITS database is a centralized database that contains data on injuries from an electronic medical record (EMR). All players provided consent to have their data included in this EMR. HITS system captures injuries reported by the athletic trainers for all professional baseball players from 30 MLB clubs and their 230 minor league affiliates. Additional details on this population of professional baseball players have been published elsewhere.⁵ Only injuries that result in time out of play (≥1 day missed) are included in the database, and they are logged with basic information such as region of the body, diagnosis, date, player position, activity leading to injury, and general treatment. Any injury that affects participation in any aspect of baseball-related activity (eg, game, practice, warm-up, conditioning, weight training) is captured in HITS.

All baseball-related knee injuries occurring during the 2011-2014 seasons that resulted in time out of sport were included in the study. These injuries were identified based on the Sports Medicine Diagnostic Coding System (SMDCS) to capture injuries by diagnostic groups.¹⁸ Knee injuries were included if they occurred during spring training, regular season, or postseason play. Offseason injuries were not included. Injury events that were classified as “season-ending” were not included in the analysis of days missed because many of these players may not have been cleared to play until the beginning of the following season. To determine the proportion of knee injuries during the study period, all injuries were included for comparative purposes (subdivided based on 30 anatomic regions or types).

For each knee injury, a number of variables were analyzed, including diagnosis, level of play (MLB vs. MiLB), age, player position at the time of injury (pitcher, catcher, infield, outfield, base runner, or batter), field location where the injury occurred (home plate, pitcher’s mound, infield, outfield, foul territory or bullpen, or other), mechanism of injury, days missed, and treatment rendered (conservative vs surgical). The classification used to describe the mechanism of injury consisted of contact with ball, contact with ground, contact with another player, contact with another object, or noncontact.

Statistical Analysis
Epidemiologic data are presented with descriptive statistics such as mean, median, frequency, and percentage where appropriate. When comparing player age, days missed, and surgical vs nonsurgical treatment between MLB and MiLB players, t-tests and tests for difference in proportions were applied as appropriate. Statistical significance was established for P values < .05.

The distribution of days missed for the variables considered was often skewed to the right (ie, days missed mostly concentrated on the low to moderate number of days, with fewer values in the much higher days missed range), even after excluding the season-ending injuries; hence the mean (or average) days missed was often larger than the median days missed. Reporting the median would allow for a robust estimate of the expected number of days missed, but would down weight those instances when knee injuries result in much longer missed days, as reflected by the mean. Because of the importance of the days missed measure for professional baseball, both the mean and median are presented.

In order to estimate exposure, the average number of players per team per game was calculated based on analysis of regular season game participation via box scores. This average number over a season, multiplied by the number of team games at each professional level of baseball, was used as an estimate of athlete exposures in order to provide rates comparable to those of other injury surveillance systems. Injury rates were reported as injuries per 1000 athlete-exposures (AE) for those knee injuries that occurred during the regular season. It should be noted that the number of regular season knee injuries and the subsequent AE rates are based on injuries that were deemed work-related during the regular season. This does not necessarily only include injuries occurring during the course of a game, but injuries in game preparation as well. Due to the variations in spring training games and fluctuating rosters, an exposure rate could not be calculated for spring training knee injuries.

RESULTS

Overall Summary

Of the 30 general body regions/systems included in the HITS database, injuries to the knee were the fifth most common reason for days missed in all of professional baseball from 2011-2014 (Table 1). Injuries to the knee represented 6.5% of the nearly 34,000 injuries sustained during the study period. Knee injuries were the fifth most common reason for time out of play for players in both the MiLB and MLB.

A total of 2171 isolated knee injuries resulted in time out of sport for professional baseball players (Table 2). Of these, 410 (19%) occurred in MLB players and 1761 (81%) occurred in MiLB players. MLB players were older than MiLB players at the time of injury (29.5 vs 22.8 years, respectively). Overall mean number of days missed was 16.2 days per knee injury, with MLB players missing an approximately 7 days more per injury than MiLB athletes (21.8 vs. 14.9 days respectively; P = .001).Over the course of the 4 seasons, a total of 30,449 days were missed due to knee injuries in professional baseball, giving an average rate of 7612 days lost per season. Surgery was performed for 263 (12.1%) of the 2171 knee injuries, with a greater proportion of MLB players requiring surgery than MiLB players (17.3% vs 10.9%) (P < .001). With respect to number of days missed per injury, 26% of knee injuries in the minor leagues resulted in greater than 30 days missed, while this number rose to 32% for knee injuries in MLB players (Table 3).

For regular season games, it was estimated that there were 1,197,738 MiLB and 276,608 MLB AE, respectively, over the course of the 4 seasons (2011-2014). The overall knee injury rate across both the MiLB and MLB was 1.2 per 1000 AE, based on the subset of 308 and 1473 regular season knee injuries in MiLB and MLB, respectively. The rate of knee injury was similar and not significantly different between the MiLB and MLB (1.2 per 1000 AE in the MiLB and 1.1 per 1000 AE in the MLB).

Characteristics of Injuries

When considering the position of the player during injury, defensive players were most frequently injured (n = 742, 56.5%), with pitchers (n = 227, 17.3%), infielders (n =193, 14.7%), outfielders (n = 193, 14.7%), and catchers (n = 129, 9.8%) sustaining injuries in decreasing frequency. Injuries while on offense (n = 571, 43.5%) were most frequent in base runners (n = 320, 24.4%) followed by batters (n = 251, 19.1%) (Table 4). Injuries while on defense occurring in infielders and catchers resulted in the longest period of time away from play (average of 22.4 and 20.8 days missed, respectively), while those occurring in batters resulted in the least average days missed (8.9 days).

The most common field location for knee injuries to occur was the infield, which was responsible for n = 647 (29.8%) of the total knee injuries (Table 4). This was followed by home plate (n = 493, 22.7%), other locations outside those specified (n = 394, 18.1%), outfield (n = 320, 14.7%), pitcher’s mound (n = 210, 9.7%), and foul territory or the bullpen (n = 107, 4.9%). Of the knee injuries with a specified location, those occurring in foul territory or the bullpen resulted in the highest mean days missed (18.4), while those occurring at home plate resulted in the least mean days missed (13.4 days).

When analyzed by mechanism of injury, noncontact injuries (n = 953, 43.9%) were more common than being hit with the ball (n = 374, 17.2%), striking the ground (n = 409, 18.8%), other mechanisms not listed (n = 196, 9%), contact with another player (n = 176, 8.1%), or contact with other objects (n = 63, 2.9%) (Table 4). Noncontact injuries and player to player collisions resulted in the greatest number of missed days (21.6 and 17.1 days, respectively) while being struck by the ball resulted in the least mean days missed (5.1).

Of the n = 493 knee injuries occurring at home plate, n = 212 (43%) occurred to the batter, n = 100 (20%) to the catcher, n = 34 (6.9%) to base runners, and n = 7 (1.4%) to pitchers (Table 5). The majority of knee injuries in the infield occurred to base runners (n = 283, 43.7%). Player-to-player collisions at home plate were responsible for 51 (2.3%) knee injuries, while 163 (24%) were noncontact injuries and 376 (56%) were the result of a player being hit by the ball (Table 5).

Injury Diagnosis

By diagnosis, the most common knee injuries observed were contusions or hematomas (n = 662, 30.5%), other injuries (n = 415, 19.1%), sprains or ligament injuries (n = 380, 17.5%), tendinopathies or bursitis (n = 367, 16.9%), and meniscal or cartilage injury (n = 200, 9.2%) (Table 6). Injuries resulting in the greatest mean number of days missed included meniscal or cartilage injuries (44 days), sprains or ligament injuries (30 days), or dislocations (22 days).

Based on specific SMDCS descriptors, the most frequent knee injuries reported were contusion (n = 662, 30.5%), patella tendinopathy (n = 222, 10.2%), and meniscal tears (n = 200, 9.2%) (Table 6). Complete anterior cruciate ligament tears, although infrequent, were responsible for the greatest mean days missed (156.2 days). This was followed by lateral meniscus tears (47.5 days) and medial meniscus tears (41.2 days). Knee contusions, although very common, resulted in the least number of days missed (6.0 days).

Discussion

Although much is known about knee injuries in other professional athletic leagues, little is known about knee injuries in professional baseball players.^2-4 The majority of epidemiologic studies regarding baseball players at any level emphasizes the study of shoulder and elbow injuries.^3,4,19 Since the implementation of the electronic medical record and the HITS database in professional baseball, there has been increased effort to document injuries that have received less attention in the existing literature. Understanding the epidemiology of these injuries is important for the development of targeted prevention efforts.

Prior studies of injuries in professional baseball relied on data captured by the publicly available DL. Posner and colleagues² provide one of the most comprehensive reports on MLB injuries in a report utilizing DL assignment data over a period of 7 seasons.They demonstrated that knee injuries were responsible for 7.7% (12.5% for fielders and 3.7% for pitchers) of assignments to the DL. The current study utilized a comprehensive surveillance and builds on this existing knowledge. The present study found similar trends to Posner and colleagues² in that knee injuries were responsible for 6.5% of injuries in professional baseball players that resulted in missed games. From the 2002 season to the 2008 season, knee injuries were the fifth most common reason MLB players were placed on the DL,² and the current study indicates that they remain the fifth most common reason for missed time from play based on the HITS data. Since the prevalence of these injuries have remained constant since the 2002 season, efforts to better understand these injuries are warranted in order to identify strategies to prevent them. These analyses have generated important data towards achieving this understanding.

As with most injuries in professional sports, goals for treatment are aimed at maximizing patient function and performance while minimizing time out of play. For the 2011-2014 professional baseball seasons, a total of 2171 players sustained knee injuries and missed an average of 16.2 days per injury. Knee injuries were responsible for a total of 7612 days of missed work for MLB and MiLB players per season (30,449 days over the 4-season study period). This is equivalent to a total of 20.9 years of players’ time lost in professional baseball per season over the last 4 years. The implications of this amount of time away from sport are significant, and further study should be targeted at prevention of these injuries and optimizing return to play times.

When attempting to reduce the burden of knee injuries in professional baseball, it may prove beneficial to first understand how the injuries occur, where on the field, and who is at greatest risk. From 2011 to 2014, nearly 44% of knee injuries occurred by noncontact mechanisms. Among all locations on the field where knee injuries occurred, those occurring in the infield were responsible for the greatest mean days missed. The players who seem to be at greatest risk for knee injuries appear to be base runners. These data suggest the need for prevention efforts targeting base runners and infield players, as well as players in MiLB, where the largest number of injuries occurred.

Recently, playing rules implemented by MLB after consultation with players have focused on reducing the number of player-to-player collisions at home plate in an attempt to decrease the injury burden to catchers and base runners.²⁰ This present analysis suggests that this rule change may also reduce the occurrence of knee injuries, as player collisions at home plate were responsible for a total of 51 knee injuries during the study period. The impact of this rule change on injury rates should also be explored. Interestingly, of the 51 knees injuries occurring due to contact at home plate, 23 occurred in 2011, and only 2 occurred in 2014—the first year of the new rule. Additional areas that resulted in high numbers of knee injuries were player-to-player contact in the infield and player contact with the ground in the infield.

Attempting to reduce injury burden and time out of play related to knee injuries in professional baseball players will likely prove to be a difficult task. In order to generate meaningful improvement, a comprehensive approach that involves players, management, trainers, therapists, and physicians will likely be required. As the first report of the epidemiology of knee injuries in professional baseball players, this study is one important step in that process. The strengths of this study are its comprehensive nature that analyzes injuries from an entire population of players on more than 200 teams over a 3-year period. Also, this research is strengthened by its focus on one particular region of the body that has received limited attention in the empirical literature, but represents a significant source of lost time during the baseball season.

There are some limitations to this study. As with any injury surveillance system, there is the possibility that not all cases were captured. Additionally, since the surveillance system is based on data from multiple teams, data entry discrepancy is possible; however, the presence of dropdown boxes and systematic definitions for injuries reduces this risk. Finally, this study did not investigate the various treatments for knee injuries beyond whether or not the injury required surgery. Since this was the first comprehensive exploration of knee injuries in professional baseball, future studies are needed to explore additional facets including outcomes related to treatment, return to play, and performance.

Conclusion

Knee injuries represent 6.5% of all injuries in professional baseball, occurring at a rate of 1.3 per 1000 AE. The burden of these injuries is significant for professional baseball players. This study fills a critical gap in sports injury research by contributing to the knowledge about the effect of knee injuries in professional baseball. It also provides an important foundation for future epidemiologic inquiry to identify modifiable risk factors and interventions that may reduce the impact of these injuries in athletes.

Injuries among professional baseball players have been on the rise for several years.^1,2 From 1989 to 1999, the number of disabled list (DL) reports increased 38% (266 to 367 annual reports),¹ and a similar increase in injury rates was noted from the 2002 to the 2008 seasons (37%).² These injuries have important implications for future injury risk and time away from play. Identifying these injuries and determining correlates and risk factors is important for targeted prevention efforts.

Several studies have explored the prevalence of upper extremity injuries in professional and collegiate baseball players;^2-4 however, detailed epidemiology of knee injuries in Major League Baseball (MLB) and Minor League Baseball (MiLB) players is lacking. Much more is known about the prevalence, treatment, and outcomes of knee injuries in other professional sporting organizations, such as the National Basketball Association (NBA), National Football League (NFL), and National Hockey League (NHL).^4-12 A recent meta-analysis exploring injuries in professional athletes found that studies on lower extremity injuries comprised approximately 12% of the literature reporting injuries in MLB players.⁴ In other professional leagues, publications on lower extremity injuries comprise approximately 56% of the sports medicine literature in the NFL, 54% in the NBA, and 62% in the NHL.⁴ Since few studies have investigated lower extremity injuries among professional baseball players, there is an opportunity for additional research to guide evidence-based prevention strategies.

A better understanding of the nature of these injuries is one of the first steps towards developing targeted injury prevention programs and treatment algorithms. The study of injury epidemiology among professional baseball players has been aided by the creation of an injury tracking system initiated by the MLB, its minor league affiliates, and the Major League Baseball Players Association.^5,13,14 This surveillance system allows for the tracking of medical histories and injuries to players as they move across major and minor league organizations. Similar systems have been utilized in the National Collegiate Athletic Association and other professional sports organizations.^3,15-17 A unique advantage of the MLB surveillance system is the required participation of all major and minor league teams, which allows for investigation of the entire population of players rather than simply a sample of players from select teams. This system has propelled an effort to identify injury patterns as a means of developing appropriate targets for potential preventative measures.⁵

The purpose of this descriptive epidemiologic study is to better understand the distribution and characteristics of knee injuries in these elite athletes by reporting on all knee injuries occurring over a span of 4 seasons (2011-2014). Additionally, this study seeks to characterize the impact of these injuries by analyzing the time required for return to play and the treatments rendered (surgical and nonsurgical).

Materials and Methods

After approval from the Johns Hopkins Bloomberg School of Public Health Institutional Review Board, detailed data regarding knee injuries in both MLB and MiLB baseball players were extracted from the de-identified MLB Health and Injury Tracking System (HITS). The HITS database is a centralized database that contains data on injuries from an electronic medical record (EMR). All players provided consent to have their data included in this EMR. HITS system captures injuries reported by the athletic trainers for all professional baseball players from 30 MLB clubs and their 230 minor league affiliates. Additional details on this population of professional baseball players have been published elsewhere.⁵ Only injuries that result in time out of play (≥1 day missed) are included in the database, and they are logged with basic information such as region of the body, diagnosis, date, player position, activity leading to injury, and general treatment. Any injury that affects participation in any aspect of baseball-related activity (eg, game, practice, warm-up, conditioning, weight training) is captured in HITS.

All baseball-related knee injuries occurring during the 2011-2014 seasons that resulted in time out of sport were included in the study. These injuries were identified based on the Sports Medicine Diagnostic Coding System (SMDCS) to capture injuries by diagnostic groups.¹⁸ Knee injuries were included if they occurred during spring training, regular season, or postseason play. Offseason injuries were not included. Injury events that were classified as “season-ending” were not included in the analysis of days missed because many of these players may not have been cleared to play until the beginning of the following season. To determine the proportion of knee injuries during the study period, all injuries were included for comparative purposes (subdivided based on 30 anatomic regions or types).

For each knee injury, a number of variables were analyzed, including diagnosis, level of play (MLB vs. MiLB), age, player position at the time of injury (pitcher, catcher, infield, outfield, base runner, or batter), field location where the injury occurred (home plate, pitcher’s mound, infield, outfield, foul territory or bullpen, or other), mechanism of injury, days missed, and treatment rendered (conservative vs surgical). The classification used to describe the mechanism of injury consisted of contact with ball, contact with ground, contact with another player, contact with another object, or noncontact.

Statistical Analysis
Epidemiologic data are presented with descriptive statistics such as mean, median, frequency, and percentage where appropriate. When comparing player age, days missed, and surgical vs nonsurgical treatment between MLB and MiLB players, t-tests and tests for difference in proportions were applied as appropriate. Statistical significance was established for P values < .05.

The distribution of days missed for the variables considered was often skewed to the right (ie, days missed mostly concentrated on the low to moderate number of days, with fewer values in the much higher days missed range), even after excluding the season-ending injuries; hence the mean (or average) days missed was often larger than the median days missed. Reporting the median would allow for a robust estimate of the expected number of days missed, but would down weight those instances when knee injuries result in much longer missed days, as reflected by the mean. Because of the importance of the days missed measure for professional baseball, both the mean and median are presented.

In order to estimate exposure, the average number of players per team per game was calculated based on analysis of regular season game participation via box scores. This average number over a season, multiplied by the number of team games at each professional level of baseball, was used as an estimate of athlete exposures in order to provide rates comparable to those of other injury surveillance systems. Injury rates were reported as injuries per 1000 athlete-exposures (AE) for those knee injuries that occurred during the regular season. It should be noted that the number of regular season knee injuries and the subsequent AE rates are based on injuries that were deemed work-related during the regular season. This does not necessarily only include injuries occurring during the course of a game, but injuries in game preparation as well. Due to the variations in spring training games and fluctuating rosters, an exposure rate could not be calculated for spring training knee injuries.

RESULTS

Overall Summary

Of the 30 general body regions/systems included in the HITS database, injuries to the knee were the fifth most common reason for days missed in all of professional baseball from 2011-2014 (Table 1). Injuries to the knee represented 6.5% of the nearly 34,000 injuries sustained during the study period. Knee injuries were the fifth most common reason for time out of play for players in both the MiLB and MLB.

A total of 2171 isolated knee injuries resulted in time out of sport for professional baseball players (Table 2). Of these, 410 (19%) occurred in MLB players and 1761 (81%) occurred in MiLB players. MLB players were older than MiLB players at the time of injury (29.5 vs 22.8 years, respectively). Overall mean number of days missed was 16.2 days per knee injury, with MLB players missing an approximately 7 days more per injury than MiLB athletes (21.8 vs. 14.9 days respectively; P = .001).Over the course of the 4 seasons, a total of 30,449 days were missed due to knee injuries in professional baseball, giving an average rate of 7612 days lost per season. Surgery was performed for 263 (12.1%) of the 2171 knee injuries, with a greater proportion of MLB players requiring surgery than MiLB players (17.3% vs 10.9%) (P < .001). With respect to number of days missed per injury, 26% of knee injuries in the minor leagues resulted in greater than 30 days missed, while this number rose to 32% for knee injuries in MLB players (Table 3).

For regular season games, it was estimated that there were 1,197,738 MiLB and 276,608 MLB AE, respectively, over the course of the 4 seasons (2011-2014). The overall knee injury rate across both the MiLB and MLB was 1.2 per 1000 AE, based on the subset of 308 and 1473 regular season knee injuries in MiLB and MLB, respectively. The rate of knee injury was similar and not significantly different between the MiLB and MLB (1.2 per 1000 AE in the MiLB and 1.1 per 1000 AE in the MLB).

Characteristics of Injuries

When considering the position of the player during injury, defensive players were most frequently injured (n = 742, 56.5%), with pitchers (n = 227, 17.3%), infielders (n =193, 14.7%), outfielders (n = 193, 14.7%), and catchers (n = 129, 9.8%) sustaining injuries in decreasing frequency. Injuries while on offense (n = 571, 43.5%) were most frequent in base runners (n = 320, 24.4%) followed by batters (n = 251, 19.1%) (Table 4). Injuries while on defense occurring in infielders and catchers resulted in the longest period of time away from play (average of 22.4 and 20.8 days missed, respectively), while those occurring in batters resulted in the least average days missed (8.9 days).

The most common field location for knee injuries to occur was the infield, which was responsible for n = 647 (29.8%) of the total knee injuries (Table 4). This was followed by home plate (n = 493, 22.7%), other locations outside those specified (n = 394, 18.1%), outfield (n = 320, 14.7%), pitcher’s mound (n = 210, 9.7%), and foul territory or the bullpen (n = 107, 4.9%). Of the knee injuries with a specified location, those occurring in foul territory or the bullpen resulted in the highest mean days missed (18.4), while those occurring at home plate resulted in the least mean days missed (13.4 days).

When analyzed by mechanism of injury, noncontact injuries (n = 953, 43.9%) were more common than being hit with the ball (n = 374, 17.2%), striking the ground (n = 409, 18.8%), other mechanisms not listed (n = 196, 9%), contact with another player (n = 176, 8.1%), or contact with other objects (n = 63, 2.9%) (Table 4). Noncontact injuries and player to player collisions resulted in the greatest number of missed days (21.6 and 17.1 days, respectively) while being struck by the ball resulted in the least mean days missed (5.1).

Of the n = 493 knee injuries occurring at home plate, n = 212 (43%) occurred to the batter, n = 100 (20%) to the catcher, n = 34 (6.9%) to base runners, and n = 7 (1.4%) to pitchers (Table 5). The majority of knee injuries in the infield occurred to base runners (n = 283, 43.7%). Player-to-player collisions at home plate were responsible for 51 (2.3%) knee injuries, while 163 (24%) were noncontact injuries and 376 (56%) were the result of a player being hit by the ball (Table 5).

Injury Diagnosis

By diagnosis, the most common knee injuries observed were contusions or hematomas (n = 662, 30.5%), other injuries (n = 415, 19.1%), sprains or ligament injuries (n = 380, 17.5%), tendinopathies or bursitis (n = 367, 16.9%), and meniscal or cartilage injury (n = 200, 9.2%) (Table 6). Injuries resulting in the greatest mean number of days missed included meniscal or cartilage injuries (44 days), sprains or ligament injuries (30 days), or dislocations (22 days).

Based on specific SMDCS descriptors, the most frequent knee injuries reported were contusion (n = 662, 30.5%), patella tendinopathy (n = 222, 10.2%), and meniscal tears (n = 200, 9.2%) (Table 6). Complete anterior cruciate ligament tears, although infrequent, were responsible for the greatest mean days missed (156.2 days). This was followed by lateral meniscus tears (47.5 days) and medial meniscus tears (41.2 days). Knee contusions, although very common, resulted in the least number of days missed (6.0 days).

Discussion

Although much is known about knee injuries in other professional athletic leagues, little is known about knee injuries in professional baseball players.^2-4 The majority of epidemiologic studies regarding baseball players at any level emphasizes the study of shoulder and elbow injuries.^3,4,19 Since the implementation of the electronic medical record and the HITS database in professional baseball, there has been increased effort to document injuries that have received less attention in the existing literature. Understanding the epidemiology of these injuries is important for the development of targeted prevention efforts.

Prior studies of injuries in professional baseball relied on data captured by the publicly available DL. Posner and colleagues² provide one of the most comprehensive reports on MLB injuries in a report utilizing DL assignment data over a period of 7 seasons.They demonstrated that knee injuries were responsible for 7.7% (12.5% for fielders and 3.7% for pitchers) of assignments to the DL. The current study utilized a comprehensive surveillance and builds on this existing knowledge. The present study found similar trends to Posner and colleagues² in that knee injuries were responsible for 6.5% of injuries in professional baseball players that resulted in missed games. From the 2002 season to the 2008 season, knee injuries were the fifth most common reason MLB players were placed on the DL,² and the current study indicates that they remain the fifth most common reason for missed time from play based on the HITS data. Since the prevalence of these injuries have remained constant since the 2002 season, efforts to better understand these injuries are warranted in order to identify strategies to prevent them. These analyses have generated important data towards achieving this understanding.

As with most injuries in professional sports, goals for treatment are aimed at maximizing patient function and performance while minimizing time out of play. For the 2011-2014 professional baseball seasons, a total of 2171 players sustained knee injuries and missed an average of 16.2 days per injury. Knee injuries were responsible for a total of 7612 days of missed work for MLB and MiLB players per season (30,449 days over the 4-season study period). This is equivalent to a total of 20.9 years of players’ time lost in professional baseball per season over the last 4 years. The implications of this amount of time away from sport are significant, and further study should be targeted at prevention of these injuries and optimizing return to play times.

When attempting to reduce the burden of knee injuries in professional baseball, it may prove beneficial to first understand how the injuries occur, where on the field, and who is at greatest risk. From 2011 to 2014, nearly 44% of knee injuries occurred by noncontact mechanisms. Among all locations on the field where knee injuries occurred, those occurring in the infield were responsible for the greatest mean days missed. The players who seem to be at greatest risk for knee injuries appear to be base runners. These data suggest the need for prevention efforts targeting base runners and infield players, as well as players in MiLB, where the largest number of injuries occurred.

Recently, playing rules implemented by MLB after consultation with players have focused on reducing the number of player-to-player collisions at home plate in an attempt to decrease the injury burden to catchers and base runners.²⁰ This present analysis suggests that this rule change may also reduce the occurrence of knee injuries, as player collisions at home plate were responsible for a total of 51 knee injuries during the study period. The impact of this rule change on injury rates should also be explored. Interestingly, of the 51 knees injuries occurring due to contact at home plate, 23 occurred in 2011, and only 2 occurred in 2014—the first year of the new rule. Additional areas that resulted in high numbers of knee injuries were player-to-player contact in the infield and player contact with the ground in the infield.

Attempting to reduce injury burden and time out of play related to knee injuries in professional baseball players will likely prove to be a difficult task. In order to generate meaningful improvement, a comprehensive approach that involves players, management, trainers, therapists, and physicians will likely be required. As the first report of the epidemiology of knee injuries in professional baseball players, this study is one important step in that process. The strengths of this study are its comprehensive nature that analyzes injuries from an entire population of players on more than 200 teams over a 3-year period. Also, this research is strengthened by its focus on one particular region of the body that has received limited attention in the empirical literature, but represents a significant source of lost time during the baseball season.

There are some limitations to this study. As with any injury surveillance system, there is the possibility that not all cases were captured. Additionally, since the surveillance system is based on data from multiple teams, data entry discrepancy is possible; however, the presence of dropdown boxes and systematic definitions for injuries reduces this risk. Finally, this study did not investigate the various treatments for knee injuries beyond whether or not the injury required surgery. Since this was the first comprehensive exploration of knee injuries in professional baseball, future studies are needed to explore additional facets including outcomes related to treatment, return to play, and performance.

Conclusion

Knee injuries represent 6.5% of all injuries in professional baseball, occurring at a rate of 1.3 per 1000 AE. The burden of these injuries is significant for professional baseball players. This study fills a critical gap in sports injury research by contributing to the knowledge about the effect of knee injuries in professional baseball. It also provides an important foundation for future epidemiologic inquiry to identify modifiable risk factors and interventions that may reduce the impact of these injuries in athletes.

Intact and well functioning menisci are essential for optimal knee function. Articular cartilage damage and rapid joint degeneration have been observed in knees after meniscectomy.^1-5 Meniscal root tears and avulsions are now increasingly recognized as a functional equivalent to total meniscectomy, and will follow a similar course if left untreated.^6-8

The menisci provide shock absorption and stability through their unique anatomy and physiology. Their essential role in dissipation of the axial load encountered during daily activities is accomplished via generation of circumferential hoop stress.^4,5,9 Tears of the horn or body may diminish this ability depending on the size and location, but a tear or an avulsion that renders the root incompetent will leave the meniscus unable to generate hoop stress.¹⁰ Likewise, as the menisci have been shown to be important secondary stabilizers for both translation and rotation, this function is lost or significantly diminished in the setting of a root tear.^6,11,12

Despite their clinical and biomechanical implications, meniscal root tears can be difficult to identify, particularly when they are not actively sought. The goal of this article is to highlight the current diagnostic workup and treatment in patients with suspected meniscal root pathology. We will also aim to emphasize important anatomic and biomechanical considerations when attempting a meniscal root repair.

Anatomy

The menisci are 2 fibrocartilage wedge-shaped structures that surround the medial and lateral tibial plateau’s weight-bearing surfaces. They are attached at many points along their periphery via coronary ligaments that comprise a continuous junction of the meniscus to the capsule to the tibial plateau. Each meniscus has an anterior and a posterior horn that are securely anchored to the tibial intercondylar region via strong ligaments known as the roots.

The anterior medial root attaches just anterior and medial to the medial tibial spine. The anterior lateral root attaches just anterior to the lateral tibial spine. The medial and lateral anterior horns of the menisci are also connected via the anterior intermeniscal ligament (AIML).^13-15 Recent cadaveric biomechanical studies have questioned the importance of the AIML, demonstrating no significant change in contact pressure or area before and after sectioning.¹⁶ Another important consideration with respect to the anterior root insertion of the lateral meniscus is its intimate relationship with the tibial insertion of the anterior cruciate ligament (ACL). The anterior lateral root and the ACL share over 60% of their tibial footprints.^13,17

When the menisci are competent, they absorb between 40% to 70% of the contact force generated between the femur and tibia.¹ By providing strong anchor points, the meniscal roots allow the horns and bodies of the menisci to maintain a stable position that maximizes congruency with the femoral condyles.

Pathology

The conversion of axial load to circumferential hoop stresses occur as the resilient, yet pliable, menisci are squeezed between the femoral condyle and tibial plateau. However, this function is dependent on secure attachment sites at the roots. In the setting of root tear, there is no restraint to the peripheral distortion of the menisci, and meniscal extrusion can occur.¹⁸

Clinical evidence and biomechanical evidence strongly show the consequences of meniscectomy. Multiple studies have shown similar findings and have proven that a meniscal root tear or avulsion is the biomechanical equivalent to total meniscectomy.³ With meniscectomy, not only do peak pressures within compartments increase significantly, it has been demonstrated that other compartments within the knee with intact menisci do not have increases in compartment pressures, lending more evidence to the menisci functioning as separate units.¹⁶ It has also been found that anterior/posterior translation is increased with medial meniscal root tears. When lateral meniscus root tears were studied with associated ACL tear, the pivot shift motion was found to be exaggerated.⁶

However, the finding of utmost importance in these biomechanical studies is that peak pressures and excessive tibiofemoral motion are restored to normal levels after meniscal root repair. Therefore, repair of meniscal root tears restores native knee biomechanics and will potentially prevent arthritic sequelae from developing.^3,4,7,19

Epidemiology

Tears of the posterior root of either menisci are more common than their anterior counterparts, and have been more extensively studied. However, there are situations that can lead to anterior root tears, specifically during ACL reconstruction and during medullary nailing of the tibia.^20,21 Barring iatrogenic injury, the anterior horn is less at risk for injury than the posterior horn given the biomechanical environment of the knee.³

Medial meniscus posterior root tears are more common than lateral tears. However, these are often more chronic in nature and not associated with an acute event. Risk factors for medial meniscus root tear include increased body mass index, varus mechanical axis, female gender, and low activity level.²²

Lateral meniscus root tears more commonly occur during trauma with sprains and/or tears of knee ligaments.²³ Along with increased recognition of meniscal root injuries associated with knee ligamentous injury comes the recognition that certain ligamentous reconstructions—namely the ACL—are more prone to failure and have higher stresses when a root tear is left untreated.^17,24

Diagnosis

The gold standard for diagnosis of a meniscal root lesion is under direct visualization during arthroscopy.¹⁸ The meniscal roots must be probed and stressed to assess their integrity regardless of the initial indication for knee arthroscopy. In most cases, however, the diagnosis of meniscal root tears should occur prior to proceeding to the operating room.

Magnetic resonance imaging (MRI) has been used to aid in diagnosis of meniscal root tears since the early 1990s.²⁵ Now, with the widespread use of MRI, understanding and diagnosis of meniscal root pathology has increased. All sequences should be reviewed, but T2 weighted coronal sections should provide the best visualization of the posterior roots (Figures 1A, 1B). Sagittal sections may also be helpful in this diagnosis. Increased signal within the root or horn may represent partial or full thickness tears, or may show a more degenerative process with fraying.^14,15,26,27

MRI does have limitations, however. When compared to arthroscopy, the sensitivity of 3T MRI to identify posterior root tears is 77%, and specificity is 73%. Medial root tears are more readily identified on MRI than lateral tears.²⁸ This further highlights the need for high suspicion during arthroscopy with the requisite equipment on standby should it be needed.

A concerning finding that may be observed on MRI includes meniscal extrusion (Figures 2A, 2B). Most often seen with the medial meniscus, extrusion is diagnosed when the meniscal body displaces greater than 3 mm past the tibial articular surface on a midcoronal image.^26,27 Over 50% of patients with medial meniscal extrusion on MRI will have medial meniscal root tears.^26,27 Conversely, meniscal extrusion is less common in lateral menisci for multiple reasons. The lateral compartment of the knee does not have as high contact pressure as the medial compartment, so the lateral meniscus is not as likely to be extruded from the joint. Additionally, the posterior lateral root has the added benefit of further stability from meniscofemoral ligaments.¹¹ They provide a restraint to meniscal extrusion, with a reported rate of 14% lateral meniscus extrusion when they are intact. If the meniscofemoral ligaments are not present or torn in the setting of posterior root tear, the lateral meniscus extrusion rate quadruples and approaches that of medial meniscal extrusion.¹⁵

Another finding indicative of meniscal root tear is the “ghost meniscus” (Figure 3). The posterior horn and anterior horn should both be visible in sagittal cuts on MRI. When the anterior horn is present, but the posterior horn is not visualized, it is termed a “ghost meniscus.” This MRI finding is highly associated with meniscal root tears, and will often be found along with meniscal extrusion on coronal sequencing.^27,28

Treatment

Historically, large meniscal tears, extruded menisci, or root avulsions have been treated with conservative observation if asymptomatic, or with meniscectomy when symptomatic. With a meniscal root tear, both forms of treatment will not provide lasting benefit and rapid joint degeneration ensues. Evidence now supports repair over meniscectomy when treating root tears.^7,8,19,29

Patients who have meniscal root tears that are likely sequelae of an arthritic process are not candidates for meniscal root repair. These patients will often have known arthritis with an intact meniscus and then progress to meniscal pathology, most often medially. Because arthritis is the cause of these meniscal tears, a repair will not reverse this process; such repairs will likely fail, and the patient will re-tear the meniscus. For this subset of patients, physical therapy and activity modification are appropriate treatment.

Repair is indicated for patients with acute tears, with or without associated soft tissue injury to the knee, and those with chronic or acute on chronic tears with minimal arthritis within the knee. The authors’ preferred method of repair is via suture fixation through transosseous tunnel (Figures 4A-4F).

Once a root tear has been identified during arthroscopy, it should be probed and/or grasped and pulled to confirm its integrity. A shaver is then used to debride any fraying of the meniscus and to debride the anatomic footprint of the root. Curettes and rasps are used to prepare the meniscal bed at the center of its insertion and the undersurface of the meniscal root. Once the attachment site of the root insertion has been prepared, an ACL tip-to-tip drill guide is placed over the prepared bed. For repair of a medial meniscus posterior root, a 2.4-mm drill tip guide pin is inserted through the guide via an incision made at the anteromedial tibia. For repair of the lateral meniscus posterior root, the pin is inserted through an incision at the anterolateral aspect of the tibia.

Once the guide pin has been inserted and is visualized at the center of the root footprint, it is held in place by a hemostat or grasper placed intra-articularly. Next, the guide pin is overreamed with a 4.5-mm cannulated drill bit. The transosseous tunnel is then further prepared using a shaver to remove excess soft tissue surrounding the tunnel entrance at the tibial plateau. Further rasping around the edges of the tunnel is performed to make final preparations.

Attention is then turned back to the meniscal root. Using a FastPass Scorpion (Arthrex), 2 or 3 size 0 fiber wire sutures are passed through the root, and a cinch stitch is then secured leaving four to six stands (2 from each Scorpion pass) in the root. A FiberStick is then introduced into the tibial bone tunnel and each strand of the 0 fiberwire is retrieved. Once the FiberWire attached to the meniscal root is in the tunnel, the meniscus should be directly visualized as the appropriate tension is toggled to reduce the meniscal root into its footprint. In order to securely fasten the meniscal root, an Arthrex SwiveLock 4.75-mm suture anchor is used. The meniscus is again probed to assess the integrity of the repair. Of note, an alternative method of fixation is accomplished by tying the fiberwire over an Arthrex suture button at the anterior tibia.

Postoperatively, weight bearing restriction is warranted, along with range of motion restrictions. During the first 2 weeks, patients will be counseled to be touch down weight bearing with the use of crutches or a walker. During this period, range of motion will be restricted by hinged knee brace to 30° of flexion and full extension. The next 2-week period will advance to progressive partial weight bearing, again with crutches or a walker. Range of motion will also be expanded to 60° of flexion. After a month, the patient will then be allowed to be full weight bearing as tolerated and be weaned from assistive ambulation devices. Range of motion will then be 90° of flexion. It is paramount that full extension be achieved and maintained in the early postoperative period. Quadriceps strengthening should also proceed with unlimited straight leg raises throughout this period as well.

Intact and well functioning menisci are essential for optimal knee function. Articular cartilage damage and rapid joint degeneration have been observed in knees after meniscectomy.^1-5 Meniscal root tears and avulsions are now increasingly recognized as a functional equivalent to total meniscectomy, and will follow a similar course if left untreated.^6-8

The menisci provide shock absorption and stability through their unique anatomy and physiology. Their essential role in dissipation of the axial load encountered during daily activities is accomplished via generation of circumferential hoop stress.^4,5,9 Tears of the horn or body may diminish this ability depending on the size and location, but a tear or an avulsion that renders the root incompetent will leave the meniscus unable to generate hoop stress.¹⁰ Likewise, as the menisci have been shown to be important secondary stabilizers for both translation and rotation, this function is lost or significantly diminished in the setting of a root tear.^6,11,12

Despite their clinical and biomechanical implications, meniscal root tears can be difficult to identify, particularly when they are not actively sought. The goal of this article is to highlight the current diagnostic workup and treatment in patients with suspected meniscal root pathology. We will also aim to emphasize important anatomic and biomechanical considerations when attempting a meniscal root repair.

Anatomy

The menisci are 2 fibrocartilage wedge-shaped structures that surround the medial and lateral tibial plateau’s weight-bearing surfaces. They are attached at many points along their periphery via coronary ligaments that comprise a continuous junction of the meniscus to the capsule to the tibial plateau. Each meniscus has an anterior and a posterior horn that are securely anchored to the tibial intercondylar region via strong ligaments known as the roots.

The anterior medial root attaches just anterior and medial to the medial tibial spine. The anterior lateral root attaches just anterior to the lateral tibial spine. The medial and lateral anterior horns of the menisci are also connected via the anterior intermeniscal ligament (AIML).^13-15 Recent cadaveric biomechanical studies have questioned the importance of the AIML, demonstrating no significant change in contact pressure or area before and after sectioning.¹⁶ Another important consideration with respect to the anterior root insertion of the lateral meniscus is its intimate relationship with the tibial insertion of the anterior cruciate ligament (ACL). The anterior lateral root and the ACL share over 60% of their tibial footprints.^13,17

When the menisci are competent, they absorb between 40% to 70% of the contact force generated between the femur and tibia.¹ By providing strong anchor points, the meniscal roots allow the horns and bodies of the menisci to maintain a stable position that maximizes congruency with the femoral condyles.

Pathology

The conversion of axial load to circumferential hoop stresses occur as the resilient, yet pliable, menisci are squeezed between the femoral condyle and tibial plateau. However, this function is dependent on secure attachment sites at the roots. In the setting of root tear, there is no restraint to the peripheral distortion of the menisci, and meniscal extrusion can occur.¹⁸

Clinical evidence and biomechanical evidence strongly show the consequences of meniscectomy. Multiple studies have shown similar findings and have proven that a meniscal root tear or avulsion is the biomechanical equivalent to total meniscectomy.³ With meniscectomy, not only do peak pressures within compartments increase significantly, it has been demonstrated that other compartments within the knee with intact menisci do not have increases in compartment pressures, lending more evidence to the menisci functioning as separate units.¹⁶ It has also been found that anterior/posterior translation is increased with medial meniscal root tears. When lateral meniscus root tears were studied with associated ACL tear, the pivot shift motion was found to be exaggerated.⁶

However, the finding of utmost importance in these biomechanical studies is that peak pressures and excessive tibiofemoral motion are restored to normal levels after meniscal root repair. Therefore, repair of meniscal root tears restores native knee biomechanics and will potentially prevent arthritic sequelae from developing.^3,4,7,19

Epidemiology

Tears of the posterior root of either menisci are more common than their anterior counterparts, and have been more extensively studied. However, there are situations that can lead to anterior root tears, specifically during ACL reconstruction and during medullary nailing of the tibia.^20,21 Barring iatrogenic injury, the anterior horn is less at risk for injury than the posterior horn given the biomechanical environment of the knee.³

Medial meniscus posterior root tears are more common than lateral tears. However, these are often more chronic in nature and not associated with an acute event. Risk factors for medial meniscus root tear include increased body mass index, varus mechanical axis, female gender, and low activity level.²²

Lateral meniscus root tears more commonly occur during trauma with sprains and/or tears of knee ligaments.²³ Along with increased recognition of meniscal root injuries associated with knee ligamentous injury comes the recognition that certain ligamentous reconstructions—namely the ACL—are more prone to failure and have higher stresses when a root tear is left untreated.^17,24

Diagnosis

The gold standard for diagnosis of a meniscal root lesion is under direct visualization during arthroscopy.¹⁸ The meniscal roots must be probed and stressed to assess their integrity regardless of the initial indication for knee arthroscopy. In most cases, however, the diagnosis of meniscal root tears should occur prior to proceeding to the operating room.

Magnetic resonance imaging (MRI) has been used to aid in diagnosis of meniscal root tears since the early 1990s.²⁵ Now, with the widespread use of MRI, understanding and diagnosis of meniscal root pathology has increased. All sequences should be reviewed, but T2 weighted coronal sections should provide the best visualization of the posterior roots (Figures 1A, 1B). Sagittal sections may also be helpful in this diagnosis. Increased signal within the root or horn may represent partial or full thickness tears, or may show a more degenerative process with fraying.^14,15,26,27

MRI does have limitations, however. When compared to arthroscopy, the sensitivity of 3T MRI to identify posterior root tears is 77%, and specificity is 73%. Medial root tears are more readily identified on MRI than lateral tears.²⁸ This further highlights the need for high suspicion during arthroscopy with the requisite equipment on standby should it be needed.

A concerning finding that may be observed on MRI includes meniscal extrusion (Figures 2A, 2B). Most often seen with the medial meniscus, extrusion is diagnosed when the meniscal body displaces greater than 3 mm past the tibial articular surface on a midcoronal image.^26,27 Over 50% of patients with medial meniscal extrusion on MRI will have medial meniscal root tears.^26,27 Conversely, meniscal extrusion is less common in lateral menisci for multiple reasons. The lateral compartment of the knee does not have as high contact pressure as the medial compartment, so the lateral meniscus is not as likely to be extruded from the joint. Additionally, the posterior lateral root has the added benefit of further stability from meniscofemoral ligaments.¹¹ They provide a restraint to meniscal extrusion, with a reported rate of 14% lateral meniscus extrusion when they are intact. If the meniscofemoral ligaments are not present or torn in the setting of posterior root tear, the lateral meniscus extrusion rate quadruples and approaches that of medial meniscal extrusion.¹⁵

Another finding indicative of meniscal root tear is the “ghost meniscus” (Figure 3). The posterior horn and anterior horn should both be visible in sagittal cuts on MRI. When the anterior horn is present, but the posterior horn is not visualized, it is termed a “ghost meniscus.” This MRI finding is highly associated with meniscal root tears, and will often be found along with meniscal extrusion on coronal sequencing.^27,28

Treatment

Historically, large meniscal tears, extruded menisci, or root avulsions have been treated with conservative observation if asymptomatic, or with meniscectomy when symptomatic. With a meniscal root tear, both forms of treatment will not provide lasting benefit and rapid joint degeneration ensues. Evidence now supports repair over meniscectomy when treating root tears.^7,8,19,29

Patients who have meniscal root tears that are likely sequelae of an arthritic process are not candidates for meniscal root repair. These patients will often have known arthritis with an intact meniscus and then progress to meniscal pathology, most often medially. Because arthritis is the cause of these meniscal tears, a repair will not reverse this process; such repairs will likely fail, and the patient will re-tear the meniscus. For this subset of patients, physical therapy and activity modification are appropriate treatment.

Repair is indicated for patients with acute tears, with or without associated soft tissue injury to the knee, and those with chronic or acute on chronic tears with minimal arthritis within the knee. The authors’ preferred method of repair is via suture fixation through transosseous tunnel (Figures 4A-4F).

Once a root tear has been identified during arthroscopy, it should be probed and/or grasped and pulled to confirm its integrity. A shaver is then used to debride any fraying of the meniscus and to debride the anatomic footprint of the root. Curettes and rasps are used to prepare the meniscal bed at the center of its insertion and the undersurface of the meniscal root. Once the attachment site of the root insertion has been prepared, an ACL tip-to-tip drill guide is placed over the prepared bed. For repair of a medial meniscus posterior root, a 2.4-mm drill tip guide pin is inserted through the guide via an incision made at the anteromedial tibia. For repair of the lateral meniscus posterior root, the pin is inserted through an incision at the anterolateral aspect of the tibia.

Once the guide pin has been inserted and is visualized at the center of the root footprint, it is held in place by a hemostat or grasper placed intra-articularly. Next, the guide pin is overreamed with a 4.5-mm cannulated drill bit. The transosseous tunnel is then further prepared using a shaver to remove excess soft tissue surrounding the tunnel entrance at the tibial plateau. Further rasping around the edges of the tunnel is performed to make final preparations.

Attention is then turned back to the meniscal root. Using a FastPass Scorpion (Arthrex), 2 or 3 size 0 fiber wire sutures are passed through the root, and a cinch stitch is then secured leaving four to six stands (2 from each Scorpion pass) in the root. A FiberStick is then introduced into the tibial bone tunnel and each strand of the 0 fiberwire is retrieved. Once the FiberWire attached to the meniscal root is in the tunnel, the meniscus should be directly visualized as the appropriate tension is toggled to reduce the meniscal root into its footprint. In order to securely fasten the meniscal root, an Arthrex SwiveLock 4.75-mm suture anchor is used. The meniscus is again probed to assess the integrity of the repair. Of note, an alternative method of fixation is accomplished by tying the fiberwire over an Arthrex suture button at the anterior tibia.

Postoperatively, weight bearing restriction is warranted, along with range of motion restrictions. During the first 2 weeks, patients will be counseled to be touch down weight bearing with the use of crutches or a walker. During this period, range of motion will be restricted by hinged knee brace to 30° of flexion and full extension. The next 2-week period will advance to progressive partial weight bearing, again with crutches or a walker. Range of motion will also be expanded to 60° of flexion. After a month, the patient will then be allowed to be full weight bearing as tolerated and be weaned from assistive ambulation devices. Range of motion will then be 90° of flexion. It is paramount that full extension be achieved and maintained in the early postoperative period. Quadriceps strengthening should also proceed with unlimited straight leg raises throughout this period as well.

Intact and well functioning menisci are essential for optimal knee function. Articular cartilage damage and rapid joint degeneration have been observed in knees after meniscectomy.^1-5 Meniscal root tears and avulsions are now increasingly recognized as a functional equivalent to total meniscectomy, and will follow a similar course if left untreated.^6-8

The menisci provide shock absorption and stability through their unique anatomy and physiology. Their essential role in dissipation of the axial load encountered during daily activities is accomplished via generation of circumferential hoop stress.^4,5,9 Tears of the horn or body may diminish this ability depending on the size and location, but a tear or an avulsion that renders the root incompetent will leave the meniscus unable to generate hoop stress.¹⁰ Likewise, as the menisci have been shown to be important secondary stabilizers for both translation and rotation, this function is lost or significantly diminished in the setting of a root tear.^6,11,12

Despite their clinical and biomechanical implications, meniscal root tears can be difficult to identify, particularly when they are not actively sought. The goal of this article is to highlight the current diagnostic workup and treatment in patients with suspected meniscal root pathology. We will also aim to emphasize important anatomic and biomechanical considerations when attempting a meniscal root repair.

Anatomy

The menisci are 2 fibrocartilage wedge-shaped structures that surround the medial and lateral tibial plateau’s weight-bearing surfaces. They are attached at many points along their periphery via coronary ligaments that comprise a continuous junction of the meniscus to the capsule to the tibial plateau. Each meniscus has an anterior and a posterior horn that are securely anchored to the tibial intercondylar region via strong ligaments known as the roots.

The anterior medial root attaches just anterior and medial to the medial tibial spine. The anterior lateral root attaches just anterior to the lateral tibial spine. The medial and lateral anterior horns of the menisci are also connected via the anterior intermeniscal ligament (AIML).^13-15 Recent cadaveric biomechanical studies have questioned the importance of the AIML, demonstrating no significant change in contact pressure or area before and after sectioning.¹⁶ Another important consideration with respect to the anterior root insertion of the lateral meniscus is its intimate relationship with the tibial insertion of the anterior cruciate ligament (ACL). The anterior lateral root and the ACL share over 60% of their tibial footprints.^13,17

When the menisci are competent, they absorb between 40% to 70% of the contact force generated between the femur and tibia.¹ By providing strong anchor points, the meniscal roots allow the horns and bodies of the menisci to maintain a stable position that maximizes congruency with the femoral condyles.

Pathology

The conversion of axial load to circumferential hoop stresses occur as the resilient, yet pliable, menisci are squeezed between the femoral condyle and tibial plateau. However, this function is dependent on secure attachment sites at the roots. In the setting of root tear, there is no restraint to the peripheral distortion of the menisci, and meniscal extrusion can occur.¹⁸

Clinical evidence and biomechanical evidence strongly show the consequences of meniscectomy. Multiple studies have shown similar findings and have proven that a meniscal root tear or avulsion is the biomechanical equivalent to total meniscectomy.³ With meniscectomy, not only do peak pressures within compartments increase significantly, it has been demonstrated that other compartments within the knee with intact menisci do not have increases in compartment pressures, lending more evidence to the menisci functioning as separate units.¹⁶ It has also been found that anterior/posterior translation is increased with medial meniscal root tears. When lateral meniscus root tears were studied with associated ACL tear, the pivot shift motion was found to be exaggerated.⁶

However, the finding of utmost importance in these biomechanical studies is that peak pressures and excessive tibiofemoral motion are restored to normal levels after meniscal root repair. Therefore, repair of meniscal root tears restores native knee biomechanics and will potentially prevent arthritic sequelae from developing.^3,4,7,19

Epidemiology

Tears of the posterior root of either menisci are more common than their anterior counterparts, and have been more extensively studied. However, there are situations that can lead to anterior root tears, specifically during ACL reconstruction and during medullary nailing of the tibia.^20,21 Barring iatrogenic injury, the anterior horn is less at risk for injury than the posterior horn given the biomechanical environment of the knee.³

Medial meniscus posterior root tears are more common than lateral tears. However, these are often more chronic in nature and not associated with an acute event. Risk factors for medial meniscus root tear include increased body mass index, varus mechanical axis, female gender, and low activity level.²²

Lateral meniscus root tears more commonly occur during trauma with sprains and/or tears of knee ligaments.²³ Along with increased recognition of meniscal root injuries associated with knee ligamentous injury comes the recognition that certain ligamentous reconstructions—namely the ACL—are more prone to failure and have higher stresses when a root tear is left untreated.^17,24

Diagnosis

The gold standard for diagnosis of a meniscal root lesion is under direct visualization during arthroscopy.¹⁸ The meniscal roots must be probed and stressed to assess their integrity regardless of the initial indication for knee arthroscopy. In most cases, however, the diagnosis of meniscal root tears should occur prior to proceeding to the operating room.

Magnetic resonance imaging (MRI) has been used to aid in diagnosis of meniscal root tears since the early 1990s.²⁵ Now, with the widespread use of MRI, understanding and diagnosis of meniscal root pathology has increased. All sequences should be reviewed, but T2 weighted coronal sections should provide the best visualization of the posterior roots (Figures 1A, 1B). Sagittal sections may also be helpful in this diagnosis. Increased signal within the root or horn may represent partial or full thickness tears, or may show a more degenerative process with fraying.^14,15,26,27

MRI does have limitations, however. When compared to arthroscopy, the sensitivity of 3T MRI to identify posterior root tears is 77%, and specificity is 73%. Medial root tears are more readily identified on MRI than lateral tears.²⁸ This further highlights the need for high suspicion during arthroscopy with the requisite equipment on standby should it be needed.

A concerning finding that may be observed on MRI includes meniscal extrusion (Figures 2A, 2B). Most often seen with the medial meniscus, extrusion is diagnosed when the meniscal body displaces greater than 3 mm past the tibial articular surface on a midcoronal image.^26,27 Over 50% of patients with medial meniscal extrusion on MRI will have medial meniscal root tears.^26,27 Conversely, meniscal extrusion is less common in lateral menisci for multiple reasons. The lateral compartment of the knee does not have as high contact pressure as the medial compartment, so the lateral meniscus is not as likely to be extruded from the joint. Additionally, the posterior lateral root has the added benefit of further stability from meniscofemoral ligaments.¹¹ They provide a restraint to meniscal extrusion, with a reported rate of 14% lateral meniscus extrusion when they are intact. If the meniscofemoral ligaments are not present or torn in the setting of posterior root tear, the lateral meniscus extrusion rate quadruples and approaches that of medial meniscal extrusion.¹⁵

Another finding indicative of meniscal root tear is the “ghost meniscus” (Figure 3). The posterior horn and anterior horn should both be visible in sagittal cuts on MRI. When the anterior horn is present, but the posterior horn is not visualized, it is termed a “ghost meniscus.” This MRI finding is highly associated with meniscal root tears, and will often be found along with meniscal extrusion on coronal sequencing.^27,28

Treatment

Historically, large meniscal tears, extruded menisci, or root avulsions have been treated with conservative observation if asymptomatic, or with meniscectomy when symptomatic. With a meniscal root tear, both forms of treatment will not provide lasting benefit and rapid joint degeneration ensues. Evidence now supports repair over meniscectomy when treating root tears.^7,8,19,29

Patients who have meniscal root tears that are likely sequelae of an arthritic process are not candidates for meniscal root repair. These patients will often have known arthritis with an intact meniscus and then progress to meniscal pathology, most often medially. Because arthritis is the cause of these meniscal tears, a repair will not reverse this process; such repairs will likely fail, and the patient will re-tear the meniscus. For this subset of patients, physical therapy and activity modification are appropriate treatment.

Repair is indicated for patients with acute tears, with or without associated soft tissue injury to the knee, and those with chronic or acute on chronic tears with minimal arthritis within the knee. The authors’ preferred method of repair is via suture fixation through transosseous tunnel (Figures 4A-4F).

Once a root tear has been identified during arthroscopy, it should be probed and/or grasped and pulled to confirm its integrity. A shaver is then used to debride any fraying of the meniscus and to debride the anatomic footprint of the root. Curettes and rasps are used to prepare the meniscal bed at the center of its insertion and the undersurface of the meniscal root. Once the attachment site of the root insertion has been prepared, an ACL tip-to-tip drill guide is placed over the prepared bed. For repair of a medial meniscus posterior root, a 2.4-mm drill tip guide pin is inserted through the guide via an incision made at the anteromedial tibia. For repair of the lateral meniscus posterior root, the pin is inserted through an incision at the anterolateral aspect of the tibia.

Once the guide pin has been inserted and is visualized at the center of the root footprint, it is held in place by a hemostat or grasper placed intra-articularly. Next, the guide pin is overreamed with a 4.5-mm cannulated drill bit. The transosseous tunnel is then further prepared using a shaver to remove excess soft tissue surrounding the tunnel entrance at the tibial plateau. Further rasping around the edges of the tunnel is performed to make final preparations.

Attention is then turned back to the meniscal root. Using a FastPass Scorpion (Arthrex), 2 or 3 size 0 fiber wire sutures are passed through the root, and a cinch stitch is then secured leaving four to six stands (2 from each Scorpion pass) in the root. A FiberStick is then introduced into the tibial bone tunnel and each strand of the 0 fiberwire is retrieved. Once the FiberWire attached to the meniscal root is in the tunnel, the meniscus should be directly visualized as the appropriate tension is toggled to reduce the meniscal root into its footprint. In order to securely fasten the meniscal root, an Arthrex SwiveLock 4.75-mm suture anchor is used. The meniscus is again probed to assess the integrity of the repair. Of note, an alternative method of fixation is accomplished by tying the fiberwire over an Arthrex suture button at the anterior tibia.

Postoperatively, weight bearing restriction is warranted, along with range of motion restrictions. During the first 2 weeks, patients will be counseled to be touch down weight bearing with the use of crutches or a walker. During this period, range of motion will be restricted by hinged knee brace to 30° of flexion and full extension. The next 2-week period will advance to progressive partial weight bearing, again with crutches or a walker. Range of motion will also be expanded to 60° of flexion. After a month, the patient will then be allowed to be full weight bearing as tolerated and be weaned from assistive ambulation devices. Range of motion will then be 90° of flexion. It is paramount that full extension be achieved and maintained in the early postoperative period. Quadriceps strengthening should also proceed with unlimited straight leg raises throughout this period as well.