More than 50 million US adults report experiencing chronic pain, with nearly 7% experiencing high-impact chronic pain.^1-3 Chronic pain negatively affects daily function, results in lost productivity, is a leading cause of disability, and is more prevalent among veterans compared with the general population.^1,2,4-6 Estimates from 2021 suggest the prevalence of chronic pain among veterans exceeds 30%; > 11% experienced high-impact chronic pain.¹

Primary care practitioners (PCPs) have a prominent role in chronic pain management. Pharmacologic options for treating pain, once a mainstay of therapy, present several challenges for patients and PCPs, including drug-drug interactions and adverse effects.⁷ The US opioid epidemic and shift to a biopsychosocial model of chronic pain care have increased emphasis on nonpharmacologic treatment options.^8,9 These include integrative modalities, which incorporate conventional approaches with an array of complementary health approaches.^10-12

Integrative therapy is a prominent feature in whole person care, which may be best exemplified by the US Department of Veterans Affairs (VA) Whole Health System of care.^13-14 Whole health empowers an individual to take charge of their health and well-being so they can “live their life to the fullest.”¹⁴ As implemented in the Veterans Health Administration (VHA), whole health includes the use of evidence-based complementary and integrative therapies, encompassing a multimodal pain management approach. Expanding the use of these therapies requires a better understanding of PCP and patient knowledge, interest, and use of integrative modalities for chronic pain.

METHODS

Using a cross-sectional survey design, PCPs and patients with chronic back pain affiliated with the VA Ann Arbor Healthcare System were invited to participate in separate but similar surveys to assess knowledge, interest, and use of nonpharmacologic integrative modalities for the treatment of chronic pain. In May, June, and July 2023, 78 PCPs received 3 email invitations to participate in an electronic (Qualtrics) survey. Patients were identified based on having an International Statistical Classification of Diseases, Tenth Revision code for low back pain (M54.5, M54.40, 41, 42, M54.89) on ≥ 2 outpatient encounters within 18 months (April 1, 2021, to March 31, 2023). A random sample of 200 patients was selected and sent a packet in September 2023 that included an introductory letter and a paper survey, along with a website link and QR code to complete the survey electronically if preferred. The introductory letter stated that participation is voluntary, had no impact on the health care currently received at the VA, and names are not attached to the survey, allowing them to remain anonymous. The packet also included a $10 gift card to encourage survey completion.

Both survey instruments are available upon request, were developed by the study team, and included a mix of yes/no questions, “select all that apply” items, Likert scale response items, and open-ended questions. For one question about which modalities they would like available, the respondent was instructed to select up to 5 modalities. The instruments were extensively pretested by members of the study team, which included 2 PCPs and a nonveteran with chronic back pain.

The list of integrative modalities included in the survey was derived from the tier 1 and tier 2 complementary and integrative health modalities identified in a VHA Directive on complementary and integrative health.^15,16 Tier 1 approaches are considered to have sufficient evidence and must be made available to veterans either within a VA medical facility or in the community. Tier 2 approaches are generally considered safe and may be made available but do not have sufficient evidence to mandate their provision. For participant ease, the integrative modalities were divided into 5 subgroups: manual therapies, energy/biofield therapies, mental health therapies, nutrition counseling, and movement therapies. The clinician survey assessed clinicians’ training and interest, clinical and personal use, and perceived barriers to providing integrative modalities for chronic pain. Professional and personal demographic data were also collected. Similarly, the patient survey assessed use of integrative therapies, perceptions of and interest in integrative modalities, and potential barriers to use. Demographic and health-related information was also collected.

Data analysis included descriptive statistics (eg, frequency counts, means, medians) and visual graphic displays. Separate analyses were conducted for clinicians and patients in addition to a comparative analysis of the use and potential interest in integrative modalities. Analysis were conducted using R software. This study was deemed nonresearch quality improvement by the VA Ann Arbor Healthcare System facility research oversight board and institutional review board approval was not solicited.

RESULTS

Twenty-eight clinicians completed the survey, yielding a participation rate of 36%. Participating clinicians had a median (IQR) age of 48 years (9.5), 15 self-identified as White (54%), 8 as Asian (29%), 15 as female (54%), 26 as non-Hispanic (93%), and 25 were medical doctors or doctors of osteopathy (89%). Nineteen (68%) worked at the main hospital outpatient clinic, and 9 practiced at community-based outpatient clinics (CBOCs). Thirteen respondents (46%) reported having no formal education or training in integrative approaches. Among those with prior training, 8 clinicians had nutrition counseling (29%) and 7 had psychologic therapy training (25%). Thirteen respondents (46%) also reported using integrative modalities for personal health needs: 8 used psychological therapies, 8 used movement therapies, 10 used integrative modalities for stress management or relaxation, and 8 used them for physical symptoms (Table 1).

Overall, 85 of 200 patients (43%) responded to the study survey. Two patients indicated they did not have chronic back pain and were excluded. Patients had a median (IQR) age of 66 (20) years, with 66 self-identifying as White (80%), 69 as male (83%), and 66 as non-Hispanic (80%). Forty-four patients (53%) received care at CBOCs. Forty-seven patients reported excellent, very good, or good overall health (57%), while 53 reported excellent, very good, or good mental health (64%). Fifty-nine patients reported back pain duration > 5 years (71%), and 67 (81%) indicated experiencing back pain flare-ups at least once per week over the previous 12 months. Sixty patients (72%) indicated they were somewhat or very interested in using integrative therapies as a back pain treatment; however, 40 patients (48%) indicated they had not received information about these therapies. Among those who indicated they had received information, the most frequently reported source was their PCP (41%). Most patients (72%) also reported feeling somewhat to very comfortable discussing integrative medicine therapies with their PCP.

Integrative Therapy Recommendations and Use

PCPs reported recommending multiple integrative modalities: 23 (82%) recommended cognitive-behavioral therapy, 22 (79%) recommended acupuncture, 21 (75%) recommended chiropractic, 19 (68%) recommended battlefield acupuncture, recommended massage 18 (64%), 17 (61%) recommended meditation or mindfulness, and 15 (54%) recommended movement therapies such as yoga or tai chi/qigong (Figure 1). The only therapies used by at least half of the patients were chiropractic used by 59 patients (71%) and acupuncture by 42 patients (51%). Thirty-eight patients (46%) reported massage use and 21 patients (25%) used cognitive-behavioral therapy (Table 2).

Integrative Therapies Desired

A majority of PCPs identified acupuncture (n = 20, 71%), chiropractic (n = 19, 68%), and massage (n = 19, 68%) as therapies they would most like to have available for patients with chronic pain (Figure 2). Similarly, patients identified massage (n = 42, 51%), chiropractic (n = 34, 41%), and acupuncture (n = 27, 33%) as most desired. Seventeen patients (21%) expressed interest in movement therapies.

Barriers to Integrative Therapies Use

When asked about barriers to use, 26 PCPs (93%) identified access to services as a somewhat or extremely likely barrier, and 22 identified time constraints (79%) (Table 3). However, 17 PCPs (61%) noted lack of familiarity, and 18 (64%) noted a lack of scientific evidence as barriers to recommending integrative modalities. Among patients, 33 (40%) indicated not knowing what services were available at their facility as a barrier, 32 (39%) were not familiar with specific therapies, and 21 (25%) indicated a lack of clarity about the benefits of a specific therapy. Only 14 patients (17%) indicated that there were no obstacles to use.

DISCUSSION

Use of integrative therapies, including complementary treatments, is an increasingly important part of chronic pain management. This survey study suggests VA PCPs are willing to recommend integrative therapies and patients with chronic back pain both desire and use several therapies. Moreover, both groups expressed interest in greater availability of similar therapies. The results also highlight key barriers, such as knowledge gaps, that should be addressed to increase the uptake of integrative modalities for managing chronic pain.

An increasing number of US adults are using complementary health approaches, an important component of integrative therapy.¹² This trend includes an increase in use for pain management, from 42.3% in 2002 to 49.2% in 2022; chiropractic care, acupuncture, and massage were most frequently used.¹² Similarly, chiropractic, acupuncture and massage were most often used by this sample of veterans with chronic back pain and were identified by the highest percentages of PCPs and patients as the therapies they would most like available.

There were areas where the opinions of patients and clinicians differed. As has been seen previously reported, clinicians largely recommended cognitive-behavioral therapy while patients showed less interest.¹⁷ Additionally, while patients expressed interest in the availability of movement therapies, such as yoga, PCPs expressed more interest in other strategies, such as trigger point injections. These differences may reflect true preference or a tendency for clinicians and patients to select therapies with which they are more familiar. Additional research is needed to better understand the acceptability and potential use of integrative health treatments across a broad array of therapeutic options.

Despite VHA policy requiring facilities to provide certain complementary and integrative health modalities, almost all PCPs identified access to services as a major obstacle.¹⁵ Based on evidence and a rigorous vetting process, services currently required on-site, via telehealth, or through community partners include acupuncture and battlefield acupuncture (battlefield auricular acupuncture), biofeedback, clinical hypnosis, guided imagery, medical massage therapy, medication, tai chi/qigong, and yoga. Optional approaches, which may be made available to veterans, include chiropractic and healing touch. Outside the VHA, some states have introduced or enacted legislation mandating insurance coverage of nonpharmacological pain treatments.¹⁸ However, these requirements and mandates do not help address challenges such as the availability of trained/qualified practitioners.^19,20 Ensuring access to complementary and integrative health treatments requires a more concerted effort to ensure that supply meets demand. It is also important to acknowledge the budgetary and physical space constraints that further limit access to services. Although expansion and integration of integrative medicine services remain a priority within the VA Whole Health program, implementation is contingent on available financial and infrastructure resources.

Time was also identified by PCPs as a barrier to recommending integrative therapies to patients. Developing and implementing time-efficient communication strategies for patient education such as concise talking points and informational handouts could help address this barrier. Furthermore, leveraging existing programs and engaging the entire health care team in patient education and referral could help increase integrative and complementary therapy uptake and use.

Although access and time were identified as major barriers, these findings also suggest that PCP and patient knowledge are another target area for enhancing the use of complementary and integrative therapies. Like prior research, most clinicians identified a lack of familiarity with certain services and a lack of scientific evidence as extremely or somewhat likely to affect their ability to offer integrative services to patients with chronic pain.²¹ Likewise, about 40% of patients identified being unfamiliar with a specific therapy as one of the major obstacles to receiving integrative therapies, with a similar number identifying PCPs as a source of information. The lack of familiarity may be due in part to the evolving nomenclature, with terms such as alternative, complementary, and integrative used to describe approaches outside what is often considered conventional medicine.¹⁰ On the other hand, there has also been considerable expansion in the number of therapies within this domain, along with an expanding evidence base. This suggests a need for targeted educational strategies for clinicians and patients, which can be rapidly deployed and continuously adapted as new therapies and evidence emerge.

Limitations

There are some inherent limitations with a survey-based approach, including sampling, non-response, and social desirability biases. In addition, this study only included PCPs and patients affiliated with a single VA medical center. Steps to mitigate these limitations included maintaining survey anonymity and reporting information about respondent characteristics to enhance transparency about the representativeness of the study findings.

CONCLUSIONS

Expanding the use of nonpharmacological pain treatments, including integrative modalities, is essential for safe and effective chronic pain management and reducing opioid use. Our findings show that VA PCPs and patients with chronic back pain are interested in and have some experience with certain integrative therapies. However, even within the context of a health care system that supports the use of integrative therapies for chronic pain as part of whole person care, increasing uptake will require addressing access and time-related constraints as well as ongoing clinician and patient education.

More than 50 million US adults report experiencing chronic pain, with nearly 7% experiencing high-impact chronic pain.^1-3 Chronic pain negatively affects daily function, results in lost productivity, is a leading cause of disability, and is more prevalent among veterans compared with the general population.^1,2,4-6 Estimates from 2021 suggest the prevalence of chronic pain among veterans exceeds 30%; > 11% experienced high-impact chronic pain.¹

Primary care practitioners (PCPs) have a prominent role in chronic pain management. Pharmacologic options for treating pain, once a mainstay of therapy, present several challenges for patients and PCPs, including drug-drug interactions and adverse effects.⁷ The US opioid epidemic and shift to a biopsychosocial model of chronic pain care have increased emphasis on nonpharmacologic treatment options.^8,9 These include integrative modalities, which incorporate conventional approaches with an array of complementary health approaches.^10-12

Integrative therapy is a prominent feature in whole person care, which may be best exemplified by the US Department of Veterans Affairs (VA) Whole Health System of care.^13-14 Whole health empowers an individual to take charge of their health and well-being so they can “live their life to the fullest.”¹⁴ As implemented in the Veterans Health Administration (VHA), whole health includes the use of evidence-based complementary and integrative therapies, encompassing a multimodal pain management approach. Expanding the use of these therapies requires a better understanding of PCP and patient knowledge, interest, and use of integrative modalities for chronic pain.

METHODS

Using a cross-sectional survey design, PCPs and patients with chronic back pain affiliated with the VA Ann Arbor Healthcare System were invited to participate in separate but similar surveys to assess knowledge, interest, and use of nonpharmacologic integrative modalities for the treatment of chronic pain. In May, June, and July 2023, 78 PCPs received 3 email invitations to participate in an electronic (Qualtrics) survey. Patients were identified based on having an International Statistical Classification of Diseases, Tenth Revision code for low back pain (M54.5, M54.40, 41, 42, M54.89) on ≥ 2 outpatient encounters within 18 months (April 1, 2021, to March 31, 2023). A random sample of 200 patients was selected and sent a packet in September 2023 that included an introductory letter and a paper survey, along with a website link and QR code to complete the survey electronically if preferred. The introductory letter stated that participation is voluntary, had no impact on the health care currently received at the VA, and names are not attached to the survey, allowing them to remain anonymous. The packet also included a $10 gift card to encourage survey completion.

Both survey instruments are available upon request, were developed by the study team, and included a mix of yes/no questions, “select all that apply” items, Likert scale response items, and open-ended questions. For one question about which modalities they would like available, the respondent was instructed to select up to 5 modalities. The instruments were extensively pretested by members of the study team, which included 2 PCPs and a nonveteran with chronic back pain.

The list of integrative modalities included in the survey was derived from the tier 1 and tier 2 complementary and integrative health modalities identified in a VHA Directive on complementary and integrative health.^15,16 Tier 1 approaches are considered to have sufficient evidence and must be made available to veterans either within a VA medical facility or in the community. Tier 2 approaches are generally considered safe and may be made available but do not have sufficient evidence to mandate their provision. For participant ease, the integrative modalities were divided into 5 subgroups: manual therapies, energy/biofield therapies, mental health therapies, nutrition counseling, and movement therapies. The clinician survey assessed clinicians’ training and interest, clinical and personal use, and perceived barriers to providing integrative modalities for chronic pain. Professional and personal demographic data were also collected. Similarly, the patient survey assessed use of integrative therapies, perceptions of and interest in integrative modalities, and potential barriers to use. Demographic and health-related information was also collected.

Data analysis included descriptive statistics (eg, frequency counts, means, medians) and visual graphic displays. Separate analyses were conducted for clinicians and patients in addition to a comparative analysis of the use and potential interest in integrative modalities. Analysis were conducted using R software. This study was deemed nonresearch quality improvement by the VA Ann Arbor Healthcare System facility research oversight board and institutional review board approval was not solicited.

RESULTS

Twenty-eight clinicians completed the survey, yielding a participation rate of 36%. Participating clinicians had a median (IQR) age of 48 years (9.5), 15 self-identified as White (54%), 8 as Asian (29%), 15 as female (54%), 26 as non-Hispanic (93%), and 25 were medical doctors or doctors of osteopathy (89%). Nineteen (68%) worked at the main hospital outpatient clinic, and 9 practiced at community-based outpatient clinics (CBOCs). Thirteen respondents (46%) reported having no formal education or training in integrative approaches. Among those with prior training, 8 clinicians had nutrition counseling (29%) and 7 had psychologic therapy training (25%). Thirteen respondents (46%) also reported using integrative modalities for personal health needs: 8 used psychological therapies, 8 used movement therapies, 10 used integrative modalities for stress management or relaxation, and 8 used them for physical symptoms (Table 1).

Overall, 85 of 200 patients (43%) responded to the study survey. Two patients indicated they did not have chronic back pain and were excluded. Patients had a median (IQR) age of 66 (20) years, with 66 self-identifying as White (80%), 69 as male (83%), and 66 as non-Hispanic (80%). Forty-four patients (53%) received care at CBOCs. Forty-seven patients reported excellent, very good, or good overall health (57%), while 53 reported excellent, very good, or good mental health (64%). Fifty-nine patients reported back pain duration > 5 years (71%), and 67 (81%) indicated experiencing back pain flare-ups at least once per week over the previous 12 months. Sixty patients (72%) indicated they were somewhat or very interested in using integrative therapies as a back pain treatment; however, 40 patients (48%) indicated they had not received information about these therapies. Among those who indicated they had received information, the most frequently reported source was their PCP (41%). Most patients (72%) also reported feeling somewhat to very comfortable discussing integrative medicine therapies with their PCP.

Integrative Therapy Recommendations and Use

PCPs reported recommending multiple integrative modalities: 23 (82%) recommended cognitive-behavioral therapy, 22 (79%) recommended acupuncture, 21 (75%) recommended chiropractic, 19 (68%) recommended battlefield acupuncture, recommended massage 18 (64%), 17 (61%) recommended meditation or mindfulness, and 15 (54%) recommended movement therapies such as yoga or tai chi/qigong (Figure 1). The only therapies used by at least half of the patients were chiropractic used by 59 patients (71%) and acupuncture by 42 patients (51%). Thirty-eight patients (46%) reported massage use and 21 patients (25%) used cognitive-behavioral therapy (Table 2).

Integrative Therapies Desired

A majority of PCPs identified acupuncture (n = 20, 71%), chiropractic (n = 19, 68%), and massage (n = 19, 68%) as therapies they would most like to have available for patients with chronic pain (Figure 2). Similarly, patients identified massage (n = 42, 51%), chiropractic (n = 34, 41%), and acupuncture (n = 27, 33%) as most desired. Seventeen patients (21%) expressed interest in movement therapies.

Barriers to Integrative Therapies Use

When asked about barriers to use, 26 PCPs (93%) identified access to services as a somewhat or extremely likely barrier, and 22 identified time constraints (79%) (Table 3). However, 17 PCPs (61%) noted lack of familiarity, and 18 (64%) noted a lack of scientific evidence as barriers to recommending integrative modalities. Among patients, 33 (40%) indicated not knowing what services were available at their facility as a barrier, 32 (39%) were not familiar with specific therapies, and 21 (25%) indicated a lack of clarity about the benefits of a specific therapy. Only 14 patients (17%) indicated that there were no obstacles to use.

DISCUSSION

Use of integrative therapies, including complementary treatments, is an increasingly important part of chronic pain management. This survey study suggests VA PCPs are willing to recommend integrative therapies and patients with chronic back pain both desire and use several therapies. Moreover, both groups expressed interest in greater availability of similar therapies. The results also highlight key barriers, such as knowledge gaps, that should be addressed to increase the uptake of integrative modalities for managing chronic pain.

An increasing number of US adults are using complementary health approaches, an important component of integrative therapy.¹² This trend includes an increase in use for pain management, from 42.3% in 2002 to 49.2% in 2022; chiropractic care, acupuncture, and massage were most frequently used.¹² Similarly, chiropractic, acupuncture and massage were most often used by this sample of veterans with chronic back pain and were identified by the highest percentages of PCPs and patients as the therapies they would most like available.

There were areas where the opinions of patients and clinicians differed. As has been seen previously reported, clinicians largely recommended cognitive-behavioral therapy while patients showed less interest.¹⁷ Additionally, while patients expressed interest in the availability of movement therapies, such as yoga, PCPs expressed more interest in other strategies, such as trigger point injections. These differences may reflect true preference or a tendency for clinicians and patients to select therapies with which they are more familiar. Additional research is needed to better understand the acceptability and potential use of integrative health treatments across a broad array of therapeutic options.

Despite VHA policy requiring facilities to provide certain complementary and integrative health modalities, almost all PCPs identified access to services as a major obstacle.¹⁵ Based on evidence and a rigorous vetting process, services currently required on-site, via telehealth, or through community partners include acupuncture and battlefield acupuncture (battlefield auricular acupuncture), biofeedback, clinical hypnosis, guided imagery, medical massage therapy, medication, tai chi/qigong, and yoga. Optional approaches, which may be made available to veterans, include chiropractic and healing touch. Outside the VHA, some states have introduced or enacted legislation mandating insurance coverage of nonpharmacological pain treatments.¹⁸ However, these requirements and mandates do not help address challenges such as the availability of trained/qualified practitioners.^19,20 Ensuring access to complementary and integrative health treatments requires a more concerted effort to ensure that supply meets demand. It is also important to acknowledge the budgetary and physical space constraints that further limit access to services. Although expansion and integration of integrative medicine services remain a priority within the VA Whole Health program, implementation is contingent on available financial and infrastructure resources.

Time was also identified by PCPs as a barrier to recommending integrative therapies to patients. Developing and implementing time-efficient communication strategies for patient education such as concise talking points and informational handouts could help address this barrier. Furthermore, leveraging existing programs and engaging the entire health care team in patient education and referral could help increase integrative and complementary therapy uptake and use.

Although access and time were identified as major barriers, these findings also suggest that PCP and patient knowledge are another target area for enhancing the use of complementary and integrative therapies. Like prior research, most clinicians identified a lack of familiarity with certain services and a lack of scientific evidence as extremely or somewhat likely to affect their ability to offer integrative services to patients with chronic pain.²¹ Likewise, about 40% of patients identified being unfamiliar with a specific therapy as one of the major obstacles to receiving integrative therapies, with a similar number identifying PCPs as a source of information. The lack of familiarity may be due in part to the evolving nomenclature, with terms such as alternative, complementary, and integrative used to describe approaches outside what is often considered conventional medicine.¹⁰ On the other hand, there has also been considerable expansion in the number of therapies within this domain, along with an expanding evidence base. This suggests a need for targeted educational strategies for clinicians and patients, which can be rapidly deployed and continuously adapted as new therapies and evidence emerge.

Limitations

There are some inherent limitations with a survey-based approach, including sampling, non-response, and social desirability biases. In addition, this study only included PCPs and patients affiliated with a single VA medical center. Steps to mitigate these limitations included maintaining survey anonymity and reporting information about respondent characteristics to enhance transparency about the representativeness of the study findings.

CONCLUSIONS

Expanding the use of nonpharmacological pain treatments, including integrative modalities, is essential for safe and effective chronic pain management and reducing opioid use. Our findings show that VA PCPs and patients with chronic back pain are interested in and have some experience with certain integrative therapies. However, even within the context of a health care system that supports the use of integrative therapies for chronic pain as part of whole person care, increasing uptake will require addressing access and time-related constraints as well as ongoing clinician and patient education.

More than 50 million US adults report experiencing chronic pain, with nearly 7% experiencing high-impact chronic pain.^1-3 Chronic pain negatively affects daily function, results in lost productivity, is a leading cause of disability, and is more prevalent among veterans compared with the general population.^1,2,4-6 Estimates from 2021 suggest the prevalence of chronic pain among veterans exceeds 30%; > 11% experienced high-impact chronic pain.¹

Primary care practitioners (PCPs) have a prominent role in chronic pain management. Pharmacologic options for treating pain, once a mainstay of therapy, present several challenges for patients and PCPs, including drug-drug interactions and adverse effects.⁷ The US opioid epidemic and shift to a biopsychosocial model of chronic pain care have increased emphasis on nonpharmacologic treatment options.^8,9 These include integrative modalities, which incorporate conventional approaches with an array of complementary health approaches.^10-12

Integrative therapy is a prominent feature in whole person care, which may be best exemplified by the US Department of Veterans Affairs (VA) Whole Health System of care.^13-14 Whole health empowers an individual to take charge of their health and well-being so they can “live their life to the fullest.”¹⁴ As implemented in the Veterans Health Administration (VHA), whole health includes the use of evidence-based complementary and integrative therapies, encompassing a multimodal pain management approach. Expanding the use of these therapies requires a better understanding of PCP and patient knowledge, interest, and use of integrative modalities for chronic pain.

METHODS

Using a cross-sectional survey design, PCPs and patients with chronic back pain affiliated with the VA Ann Arbor Healthcare System were invited to participate in separate but similar surveys to assess knowledge, interest, and use of nonpharmacologic integrative modalities for the treatment of chronic pain. In May, June, and July 2023, 78 PCPs received 3 email invitations to participate in an electronic (Qualtrics) survey. Patients were identified based on having an International Statistical Classification of Diseases, Tenth Revision code for low back pain (M54.5, M54.40, 41, 42, M54.89) on ≥ 2 outpatient encounters within 18 months (April 1, 2021, to March 31, 2023). A random sample of 200 patients was selected and sent a packet in September 2023 that included an introductory letter and a paper survey, along with a website link and QR code to complete the survey electronically if preferred. The introductory letter stated that participation is voluntary, had no impact on the health care currently received at the VA, and names are not attached to the survey, allowing them to remain anonymous. The packet also included a $10 gift card to encourage survey completion.

Both survey instruments are available upon request, were developed by the study team, and included a mix of yes/no questions, “select all that apply” items, Likert scale response items, and open-ended questions. For one question about which modalities they would like available, the respondent was instructed to select up to 5 modalities. The instruments were extensively pretested by members of the study team, which included 2 PCPs and a nonveteran with chronic back pain.

The list of integrative modalities included in the survey was derived from the tier 1 and tier 2 complementary and integrative health modalities identified in a VHA Directive on complementary and integrative health.^15,16 Tier 1 approaches are considered to have sufficient evidence and must be made available to veterans either within a VA medical facility or in the community. Tier 2 approaches are generally considered safe and may be made available but do not have sufficient evidence to mandate their provision. For participant ease, the integrative modalities were divided into 5 subgroups: manual therapies, energy/biofield therapies, mental health therapies, nutrition counseling, and movement therapies. The clinician survey assessed clinicians’ training and interest, clinical and personal use, and perceived barriers to providing integrative modalities for chronic pain. Professional and personal demographic data were also collected. Similarly, the patient survey assessed use of integrative therapies, perceptions of and interest in integrative modalities, and potential barriers to use. Demographic and health-related information was also collected.

Data analysis included descriptive statistics (eg, frequency counts, means, medians) and visual graphic displays. Separate analyses were conducted for clinicians and patients in addition to a comparative analysis of the use and potential interest in integrative modalities. Analysis were conducted using R software. This study was deemed nonresearch quality improvement by the VA Ann Arbor Healthcare System facility research oversight board and institutional review board approval was not solicited.

RESULTS

Twenty-eight clinicians completed the survey, yielding a participation rate of 36%. Participating clinicians had a median (IQR) age of 48 years (9.5), 15 self-identified as White (54%), 8 as Asian (29%), 15 as female (54%), 26 as non-Hispanic (93%), and 25 were medical doctors or doctors of osteopathy (89%). Nineteen (68%) worked at the main hospital outpatient clinic, and 9 practiced at community-based outpatient clinics (CBOCs). Thirteen respondents (46%) reported having no formal education or training in integrative approaches. Among those with prior training, 8 clinicians had nutrition counseling (29%) and 7 had psychologic therapy training (25%). Thirteen respondents (46%) also reported using integrative modalities for personal health needs: 8 used psychological therapies, 8 used movement therapies, 10 used integrative modalities for stress management or relaxation, and 8 used them for physical symptoms (Table 1).

Overall, 85 of 200 patients (43%) responded to the study survey. Two patients indicated they did not have chronic back pain and were excluded. Patients had a median (IQR) age of 66 (20) years, with 66 self-identifying as White (80%), 69 as male (83%), and 66 as non-Hispanic (80%). Forty-four patients (53%) received care at CBOCs. Forty-seven patients reported excellent, very good, or good overall health (57%), while 53 reported excellent, very good, or good mental health (64%). Fifty-nine patients reported back pain duration > 5 years (71%), and 67 (81%) indicated experiencing back pain flare-ups at least once per week over the previous 12 months. Sixty patients (72%) indicated they were somewhat or very interested in using integrative therapies as a back pain treatment; however, 40 patients (48%) indicated they had not received information about these therapies. Among those who indicated they had received information, the most frequently reported source was their PCP (41%). Most patients (72%) also reported feeling somewhat to very comfortable discussing integrative medicine therapies with their PCP.

Integrative Therapy Recommendations and Use

PCPs reported recommending multiple integrative modalities: 23 (82%) recommended cognitive-behavioral therapy, 22 (79%) recommended acupuncture, 21 (75%) recommended chiropractic, 19 (68%) recommended battlefield acupuncture, recommended massage 18 (64%), 17 (61%) recommended meditation or mindfulness, and 15 (54%) recommended movement therapies such as yoga or tai chi/qigong (Figure 1). The only therapies used by at least half of the patients were chiropractic used by 59 patients (71%) and acupuncture by 42 patients (51%). Thirty-eight patients (46%) reported massage use and 21 patients (25%) used cognitive-behavioral therapy (Table 2).

Integrative Therapies Desired

A majority of PCPs identified acupuncture (n = 20, 71%), chiropractic (n = 19, 68%), and massage (n = 19, 68%) as therapies they would most like to have available for patients with chronic pain (Figure 2). Similarly, patients identified massage (n = 42, 51%), chiropractic (n = 34, 41%), and acupuncture (n = 27, 33%) as most desired. Seventeen patients (21%) expressed interest in movement therapies.

Barriers to Integrative Therapies Use

When asked about barriers to use, 26 PCPs (93%) identified access to services as a somewhat or extremely likely barrier, and 22 identified time constraints (79%) (Table 3). However, 17 PCPs (61%) noted lack of familiarity, and 18 (64%) noted a lack of scientific evidence as barriers to recommending integrative modalities. Among patients, 33 (40%) indicated not knowing what services were available at their facility as a barrier, 32 (39%) were not familiar with specific therapies, and 21 (25%) indicated a lack of clarity about the benefits of a specific therapy. Only 14 patients (17%) indicated that there were no obstacles to use.

DISCUSSION

Use of integrative therapies, including complementary treatments, is an increasingly important part of chronic pain management. This survey study suggests VA PCPs are willing to recommend integrative therapies and patients with chronic back pain both desire and use several therapies. Moreover, both groups expressed interest in greater availability of similar therapies. The results also highlight key barriers, such as knowledge gaps, that should be addressed to increase the uptake of integrative modalities for managing chronic pain.

An increasing number of US adults are using complementary health approaches, an important component of integrative therapy.¹² This trend includes an increase in use for pain management, from 42.3% in 2002 to 49.2% in 2022; chiropractic care, acupuncture, and massage were most frequently used.¹² Similarly, chiropractic, acupuncture and massage were most often used by this sample of veterans with chronic back pain and were identified by the highest percentages of PCPs and patients as the therapies they would most like available.

There were areas where the opinions of patients and clinicians differed. As has been seen previously reported, clinicians largely recommended cognitive-behavioral therapy while patients showed less interest.¹⁷ Additionally, while patients expressed interest in the availability of movement therapies, such as yoga, PCPs expressed more interest in other strategies, such as trigger point injections. These differences may reflect true preference or a tendency for clinicians and patients to select therapies with which they are more familiar. Additional research is needed to better understand the acceptability and potential use of integrative health treatments across a broad array of therapeutic options.

Despite VHA policy requiring facilities to provide certain complementary and integrative health modalities, almost all PCPs identified access to services as a major obstacle.¹⁵ Based on evidence and a rigorous vetting process, services currently required on-site, via telehealth, or through community partners include acupuncture and battlefield acupuncture (battlefield auricular acupuncture), biofeedback, clinical hypnosis, guided imagery, medical massage therapy, medication, tai chi/qigong, and yoga. Optional approaches, which may be made available to veterans, include chiropractic and healing touch. Outside the VHA, some states have introduced or enacted legislation mandating insurance coverage of nonpharmacological pain treatments.¹⁸ However, these requirements and mandates do not help address challenges such as the availability of trained/qualified practitioners.^19,20 Ensuring access to complementary and integrative health treatments requires a more concerted effort to ensure that supply meets demand. It is also important to acknowledge the budgetary and physical space constraints that further limit access to services. Although expansion and integration of integrative medicine services remain a priority within the VA Whole Health program, implementation is contingent on available financial and infrastructure resources.

Time was also identified by PCPs as a barrier to recommending integrative therapies to patients. Developing and implementing time-efficient communication strategies for patient education such as concise talking points and informational handouts could help address this barrier. Furthermore, leveraging existing programs and engaging the entire health care team in patient education and referral could help increase integrative and complementary therapy uptake and use.

Although access and time were identified as major barriers, these findings also suggest that PCP and patient knowledge are another target area for enhancing the use of complementary and integrative therapies. Like prior research, most clinicians identified a lack of familiarity with certain services and a lack of scientific evidence as extremely or somewhat likely to affect their ability to offer integrative services to patients with chronic pain.²¹ Likewise, about 40% of patients identified being unfamiliar with a specific therapy as one of the major obstacles to receiving integrative therapies, with a similar number identifying PCPs as a source of information. The lack of familiarity may be due in part to the evolving nomenclature, with terms such as alternative, complementary, and integrative used to describe approaches outside what is often considered conventional medicine.¹⁰ On the other hand, there has also been considerable expansion in the number of therapies within this domain, along with an expanding evidence base. This suggests a need for targeted educational strategies for clinicians and patients, which can be rapidly deployed and continuously adapted as new therapies and evidence emerge.

Limitations

There are some inherent limitations with a survey-based approach, including sampling, non-response, and social desirability biases. In addition, this study only included PCPs and patients affiliated with a single VA medical center. Steps to mitigate these limitations included maintaining survey anonymity and reporting information about respondent characteristics to enhance transparency about the representativeness of the study findings.

CONCLUSIONS

Expanding the use of nonpharmacological pain treatments, including integrative modalities, is essential for safe and effective chronic pain management and reducing opioid use. Our findings show that VA PCPs and patients with chronic back pain are interested in and have some experience with certain integrative therapies. However, even within the context of a health care system that supports the use of integrative therapies for chronic pain as part of whole person care, increasing uptake will require addressing access and time-related constraints as well as ongoing clinician and patient education.

Epilepsy affects about 4.5 million people in the United States and 150,000 new individuals are diagnosed each year.^1,2 In 2019, epilepsy-attributable health care spending for noninstitutionalized people was around $5.4 billion and total epilepsy-attributable and epilepsy or seizure health care-related costs totaled $54 billion.³

Accurate surveillance of epilepsy in large health care systems can potentially improve health care delivery and resource allocation. A 2012 Institute of Medicine (IOM) report identified 13 recommendations to guide public health action on epilepsy, including validation of standard definitions for case ascertainment, identification of epilepsy through screening programs or protocols, and expansion of surveillance to better understand disease burden.⁴

A systematic review of validation studies concluded that it is reasonable to use administrative data to identify people with epilepsy in epidemiologic research. Combining The International Classification of Diseases (ICD) codes for epilepsy (ICD-10, G40-41; ICD-9, 345) with antiseizure medications (ASMs) could provide high positive predictive values (PPVs) and combining symptoms codes for convulsions (ICD-10, R56; ICD-9, 780.3, 780.39) with ASMs could lead to high sensitivity.⁵ However, identifying individuals with epilepsy from administrative data in large managed health care organizations is challenging.⁶ The IOM report noted that large managed health care organizations presented varying incidence and prevalence estimates due to differing methodology, geographic area, demographics, and definitions of epilepsy.

The Veterans Health Administration (VHA) is the largest integrated US health care system, providing care to > 9.1 million veterans.⁷ To improve the health and well-being of veterans with epilepsy (VWEs), a network of sites was established in 2008 called the US Department of Veterans Affairs (VA) Epilepsy Centers of Excellence (ECoE). Subsequent to the creation of the ECoE, efforts were made to identify VWEs within VHA databases.^8,9 Prior to fiscal year (FY) 2016, the ECoE adopted a modified version of a well-established epilepsy diagnostic algorithm developed by Holden et al for large managed care organizations.¹⁰ The original algorithm identified patients by cross-matching ASMs with ICD-9 codes for an index year. But it failed to capture a considerable number of stable patients with epilepsy in the VHA due to incomplete documentation, and had false positives due to inclusion of patients identified from diagnostic clinics. The modified algorithm the ECoE used prior to FY 2016 considered additional prior years and excluded encounters from diagnostic clinics. The result was an improvement in the sensitivity and specificity of the algorithm. Researchers evaluating 500 patients with epilepsy estimated that the modified algorithm had a PPV of 82.0% (95% CI, 78.6%-85.4%).¹¹

After implementation of ICD-10 codes in the VHA in FY 2016, the task of reliably and efficiently identifying VWE led to a 3-tier algorithm. This article presents a validation of the different tiers of this algorithm after the implementation of ICD-10 diagnosis codes and summarizes the surveillance data collected over the years within the VHA showing the trends of epilepsy.

Methods

The VHA National Neurology office commissioned a Neurology Cube dashboard in FY 2021 in collaboration with VHA Support Service Center (VSSC) for reporting and surveillance of VWEs as a quality improvement initiative. The Neurology Cube uses a 3-tier system for identifying VWE in the VHA databases. VSSC programmers extract data from the VHA Corporate Data Warehouse (CDW) and utilize Microsoft SQL Server and Microsoft Power BI for Neurology Cube reports. The 3-tier system identifies VWE and divides them into distinct groups. The first tier identifies VWE with the highest degree of confidence; Tiers 2 and 3 represent identification with successively lesser degrees of confidence (Figure 1).

Tier 1

Definition. For a given index year and the preceding 2 years, any of following diagnosis codes on ≥ 1 clinical encounter are considered: 345.xx (epilepsy in ICD-9), 780.3x (other convulsions in ICD-9), G40.xxx (epilepsy in ICD-10), R40.4 (transient alteration of awareness), R56.1 (posttraumatic seizures), or R56.9 (unspecified convulsions). To reduce false positive rates, EEG clinic visits, which may include long-term monitoring, are excluded. Patients identified with ICD codes are then evaluated for an ASM prescription for ≥ 30 days during the index year. ASMs are listed in Appendix 1.

Validation. The development and validation of ICD-9 diagnosis codes crossmatched with an ASM prescription in the VHA has been published elsewhere.¹¹ In FY 2017, after implementation of ICD-10 diagnostic codes, Tier 1 development and validation was performed in 2 phases. Even though Tier 1 study phases were conducted and completed during FY 2017, the patients for Tier 1 were identified from evaluation of FY 2016 data (October 1, 2015, to September 30, 2016). After the pilot analysis, the Tier 1 definition was implemented, and a chart review of 625 randomized patients was conducted at 5 sites for validation. Adequate preliminary data was not available to perform a sample size estimation for this study. Therefore, a practical target of 125 patients was set for Tier 1 from each site to obtain a final sample size of 625 patients. This second phase validated that the crossmatch of ICD-10 diagnosis codes with ASMs had a high PPV for identifying VWE.

Tiers 2 and 3

Definitions. For an index year, Tier 2 includes patients with ≥ 1 inpatient encounter documentation of either ICD-9 345.xx or ICD-10 G40.xxx, excluding EEG clinics. Tier 3 Includes patients who have had ≥ 2 outpatient encounters with diagnosis codes 345.xx or G40.xxx on 2 separate days, excluding EEG clinics. Tiers 2 and 3 do not require ASM prescriptions; this helps to identify VWEs who may be getting their medications outside of VHA or those who have received a new diagnosis.

Validations. Tiers 2 and 3 were included in the epilepsy identification algorithm in FY 2021 after validation was performed on a sample of 8 patients in each tier. Five patients were subsequently identified as having epilepsy in Tier 2 and 6 patients were identified in Tier 3. A more comprehensive validation of Tiers 2 and 3 was performed during FY 2022 that included patients at 5 sites seen during FY 2019 to FY 2022. Since yearly trends showed only about 8% of total patients were identified as having epilepsy through Tiers 2 and 3 we sought ≥ 20 patients per tier for the 5 sites for a total of 200 patients to ensure representation across the VHA. The final count was 126 patients for Tier 2 and 174 patients for Tier 3 (n = 300).

Gold Standard Criteria for Epilepsy Diagnosis

We used the International League Against Epilepsy (ILAE) definition of epilepsy for the validation of the 3 algorithm tiers. ILAE defines epilepsy as ≥ 2 unprovoked (or reflex) seizures occurring > 24 hours apart or 1 unprovoked (or reflex) seizure and a probability of further seizures similar to the general recurrence risk (≥ 60%) after 2 unprovoked seizures, occurring over the next 10 years.¹²

A standard protocol was provided to evaluators to identify patients using the VHA Computerized Patient Record System (Appendix 1). After review, evaluators categorized each patient in 1 of 4 ways: (1) Yes, definite: The patient’s health care practitioner (HCP) believes the patient has epilepsy and is treating with medication; (2) Yes, uncertain: The HCP has enough suspicion of epilepsy that a medication is prescribed, but uncertainty is expressed of the diagnosis; (3) No, definite: The HCP does not believe the patient has epilepsy and is therefore not treating with medication for seizure; (4) No, uncertain: The HCP is not treating with medication for epilepsy, because the diagnostic suspicion is not high enough, but there is suspicion for epilepsy.

As a quality improvement operational project, the Epilepsy National Program Office approved this validation project and determined that institutional review board approval was not required.

Statistical Analysis

Counts and percentages were computed for categories of epilepsy status. PPV of each tier was estimated with asymptotic 95% CIs.

Results

ICD-10 codes for 480 patients were evaluated in Tier 1 phase 1; 13.8% were documented with G40.xxx, 27.9% with R56.1, 34.4% with R56.9, and 24.0% with R40.4 (Appendix 2). In total, 68.1% fulfilled the criteria of epilepsy, 19.2% did not, and 12.7% were uncertain). From the validation of Tier 1 phase 2 (n = 625), the PPV of the algorithm for patients presumed to have epilepsy (definite and uncertain) was 85.1% (95% CI, 82.1%-87.8%) (Table).

Of 300 patients evaluated, 126 (42.0%) were evaluated for Tier 2 with a PPV of 61.9% (95% CI, 53.4%-70.4%), and 174 (58.0%) patients were evaluated for Tier 3 with a PPV of 59.8% (95% CI, 52.5%-67.1%. The PPV of the algorithm for patients presumed to have epilepsy (definite and uncertain) were combined to calculate the PPV. Estimates of VHA VWE counts were computed for each tier from FY 2014 to FY 2023 using the VSSC Neurology Cube (Figure 2). For all years, > 92% patients were classified using the Tier 1 definition.

Discussion

The development and validation of the 3-tier diagnostic algorithm represents an important advancement in the surveillance and management of epilepsy among veterans within the VHA. The validation of this algorithm also demonstrates its practical utility in a large, integrated health care system.

Specific challenges were encountered when attempting to use pre-existing algorithms; these challenges included differences in the usage patterns of diagnostic codes and the patterns of ASM use within the VHA. These challenges prompted the need for a tailored approach, which led to the development of this algorithm. The inclusion of additional ICD-10 codes led to further revisions and subsequent validation. While many of the basic concepts of the algorithm, including ICD codes and ASMs, could work in other institutions, it would be wise for health care organizations to develop their own algorithms because of certain variables, including organizational size, patient demographics, common comorbidities, and the specific configurations of electronic health records and administrative data systems.

Studies have shown that ICD-10 codes for epilepsy (G40.* and/or R56.9) perform well in identifying epilepsy whether they are assigned by neurologists (sensitivity, 97.7%; specificity, 44.1%; PPV, 96.2%; negative predictive value, 57.7%), or in emergency department or hospital discharges (PPV, 75.5%).^13,14 The pilot study of the algorithm’s Tier 1 development (phase 1) evaluated whether the selected ICD-10 diagnostic codes accurately included the VWE population within the VHA and revealed that while most codes (eg, epilepsy [G40.xxx]; posttraumatic seizures [R56.1]; and unspecified convulsions [R56.9]), had a low false positive rate (< 16%), the R40.4 code (transient alteration of awareness) had a higher false positivity of 42%. While this is not surprising given the broad spectrum of conditions that can manifest as transient alteration of awareness, it underscores the inherent challenges in diagnosing epilepsy using diagnosis codes.

In phase 2, the Tier 1 algorithm was validated as effective for identifying VWE in the VHA system, as its PPV was determined to be high (85%). In comparison, Tiers 2 and 3, whose criteria did not require data on VHA prescribed ASM use, had lower tiers of epilepsy predictability (PPV about 60% for both). This was thought to be acceptable because Tiers 2 and 3 represent a smaller population of the identified VWEs (about 8%). These VWEs may otherwise have been missed, partly because veterans are not required to get ASMs from the VHA.

Upon VHA implementation in FY 2021, this diagnostic algorithm exhibited significant clinical utility when integrated within the VSSC Neurology Cube. It facilitated an efficient approach to identifying VWEs using readily available databases. This led to better tracking of real-time epilepsy cases, which facilitated improving current resource allocation and targeted intervention strategies such as identification of drug-resistant epilepsy patients, optimizing strategies for telehealth and patient outreach for awareness of epilepsy care resources within VHA. Meanwhile, data acquired by the algorithm over the decade since its development (FY 2014 to FY 2023) contributed to more accurate epidemiologic information and identification of historic trends. Development of the algorithm represents one of the ways ECoEs have led to improved care for VWEs. ECoEs have been shown to improve health care for veterans in several metrics.¹⁵

A strength of this study is the rigorous multitiered validation process to confirm the diagnostic accuracy of ICD-10 codes against the gold standard ILAE definition of epilepsy to identify “definite” epilepsy cases within the VHA. The use of specific ICD codes further enhances the precision of epilepsy diagnoses. The inclusion of ASMs, which are sometimes prescribed for conditions other than epilepsy, could potentially inflate false positive rates.¹⁶

This study focused exclusively on the identification and validation of definite epilepsy cases within the VHA VSSC database, employing more stringent diagnostic criteria to ensure the highest level of certainty in ascertaining epilepsy. It is important to note there is a separate category of probable epilepsy, which involves a broader set of diagnostic criteria. While not covered in this study, probable epilepsy would be subject to future research and validation, which could provide insights into a wider spectrum of epilepsy diagnoses. Such future research could help refine the algorithm’s applicability and accuracy and potentially lead to more comprehensive surveillance and management strategies in clinical practice.

This study highlights the inherent challenges in leveraging administrative data for disease identification, particularly for conditions such as epilepsy, where diagnostic clarity can be complex. However, other conditions such as multiple sclerosis have noted similar success with the use of VHA administrative data for categorizing disease.¹⁷

Limitations

The algorithm discussed in this article is, in and of itself, generalizable. However, the validation process was unique to the VHA patient population, limiting the generalizability of the findings. Documentation practices and HCP attitudes within the VHA may differ from those in other health care settings. Identifying people with epilepsy can be challenging because of changing definitions of epilepsy over time. In addition to clinical evaluation, EEG and magnetic resonance imaging results, response to ASM treatment, and video-EEG monitoring of habitual events all can help establish the diagnosis. Therefore, studies may vary in how inclusive or exclusive the criteria are. ASMs such as gabapentin, pregabalin, carbamazepine, lamotrigine, topiramate, and valproate are used to treat other conditions, including headaches, generalized pain, and mood disorders. Consequently, including these ASMs in the Tier 1 definition may have increased the false positive rate. Additional research is needed to evaluate whether excluding these ASMs from the algorithm based on specific criteria (eg, dose of ASM used) can further refine the algorithm to identify patients with epilepsy.

Further refinement of this algorithm may also occur as technology changes. Future electronic health records may allow better tracking of different epilepsy factors, the integration of additional diagnostic criteria, and the use of natural language processing or other forms of artificial intelligence.

Conclusions

This study presents a significant step forward in epilepsy surveillance within the VHA. The algorithm offers a robust tool for identifying VWEs with good PPVs, facilitating better resource allocation and targeted care. Despite its limitations, this research lays a foundation for future advancements in the management and understanding of epilepsy within large health care systems. Since this VHA algorithm is based on ASMs and ICD diagnosis codes from patient records, other large managed health care systems also may be able to adapt this algorithm to their data specifications.

Epilepsy affects about 4.5 million people in the United States and 150,000 new individuals are diagnosed each year.^1,2 In 2019, epilepsy-attributable health care spending for noninstitutionalized people was around $5.4 billion and total epilepsy-attributable and epilepsy or seizure health care-related costs totaled $54 billion.³

Accurate surveillance of epilepsy in large health care systems can potentially improve health care delivery and resource allocation. A 2012 Institute of Medicine (IOM) report identified 13 recommendations to guide public health action on epilepsy, including validation of standard definitions for case ascertainment, identification of epilepsy through screening programs or protocols, and expansion of surveillance to better understand disease burden.⁴

A systematic review of validation studies concluded that it is reasonable to use administrative data to identify people with epilepsy in epidemiologic research. Combining The International Classification of Diseases (ICD) codes for epilepsy (ICD-10, G40-41; ICD-9, 345) with antiseizure medications (ASMs) could provide high positive predictive values (PPVs) and combining symptoms codes for convulsions (ICD-10, R56; ICD-9, 780.3, 780.39) with ASMs could lead to high sensitivity.⁵ However, identifying individuals with epilepsy from administrative data in large managed health care organizations is challenging.⁶ The IOM report noted that large managed health care organizations presented varying incidence and prevalence estimates due to differing methodology, geographic area, demographics, and definitions of epilepsy.

The Veterans Health Administration (VHA) is the largest integrated US health care system, providing care to > 9.1 million veterans.⁷ To improve the health and well-being of veterans with epilepsy (VWEs), a network of sites was established in 2008 called the US Department of Veterans Affairs (VA) Epilepsy Centers of Excellence (ECoE). Subsequent to the creation of the ECoE, efforts were made to identify VWEs within VHA databases.^8,9 Prior to fiscal year (FY) 2016, the ECoE adopted a modified version of a well-established epilepsy diagnostic algorithm developed by Holden et al for large managed care organizations.¹⁰ The original algorithm identified patients by cross-matching ASMs with ICD-9 codes for an index year. But it failed to capture a considerable number of stable patients with epilepsy in the VHA due to incomplete documentation, and had false positives due to inclusion of patients identified from diagnostic clinics. The modified algorithm the ECoE used prior to FY 2016 considered additional prior years and excluded encounters from diagnostic clinics. The result was an improvement in the sensitivity and specificity of the algorithm. Researchers evaluating 500 patients with epilepsy estimated that the modified algorithm had a PPV of 82.0% (95% CI, 78.6%-85.4%).¹¹

After implementation of ICD-10 codes in the VHA in FY 2016, the task of reliably and efficiently identifying VWE led to a 3-tier algorithm. This article presents a validation of the different tiers of this algorithm after the implementation of ICD-10 diagnosis codes and summarizes the surveillance data collected over the years within the VHA showing the trends of epilepsy.

Methods

The VHA National Neurology office commissioned a Neurology Cube dashboard in FY 2021 in collaboration with VHA Support Service Center (VSSC) for reporting and surveillance of VWEs as a quality improvement initiative. The Neurology Cube uses a 3-tier system for identifying VWE in the VHA databases. VSSC programmers extract data from the VHA Corporate Data Warehouse (CDW) and utilize Microsoft SQL Server and Microsoft Power BI for Neurology Cube reports. The 3-tier system identifies VWE and divides them into distinct groups. The first tier identifies VWE with the highest degree of confidence; Tiers 2 and 3 represent identification with successively lesser degrees of confidence (Figure 1).

Tier 1

Definition. For a given index year and the preceding 2 years, any of following diagnosis codes on ≥ 1 clinical encounter are considered: 345.xx (epilepsy in ICD-9), 780.3x (other convulsions in ICD-9), G40.xxx (epilepsy in ICD-10), R40.4 (transient alteration of awareness), R56.1 (posttraumatic seizures), or R56.9 (unspecified convulsions). To reduce false positive rates, EEG clinic visits, which may include long-term monitoring, are excluded. Patients identified with ICD codes are then evaluated for an ASM prescription for ≥ 30 days during the index year. ASMs are listed in Appendix 1.

Validation. The development and validation of ICD-9 diagnosis codes crossmatched with an ASM prescription in the VHA has been published elsewhere.¹¹ In FY 2017, after implementation of ICD-10 diagnostic codes, Tier 1 development and validation was performed in 2 phases. Even though Tier 1 study phases were conducted and completed during FY 2017, the patients for Tier 1 were identified from evaluation of FY 2016 data (October 1, 2015, to September 30, 2016). After the pilot analysis, the Tier 1 definition was implemented, and a chart review of 625 randomized patients was conducted at 5 sites for validation. Adequate preliminary data was not available to perform a sample size estimation for this study. Therefore, a practical target of 125 patients was set for Tier 1 from each site to obtain a final sample size of 625 patients. This second phase validated that the crossmatch of ICD-10 diagnosis codes with ASMs had a high PPV for identifying VWE.

Tiers 2 and 3

Definitions. For an index year, Tier 2 includes patients with ≥ 1 inpatient encounter documentation of either ICD-9 345.xx or ICD-10 G40.xxx, excluding EEG clinics. Tier 3 Includes patients who have had ≥ 2 outpatient encounters with diagnosis codes 345.xx or G40.xxx on 2 separate days, excluding EEG clinics. Tiers 2 and 3 do not require ASM prescriptions; this helps to identify VWEs who may be getting their medications outside of VHA or those who have received a new diagnosis.

Validations. Tiers 2 and 3 were included in the epilepsy identification algorithm in FY 2021 after validation was performed on a sample of 8 patients in each tier. Five patients were subsequently identified as having epilepsy in Tier 2 and 6 patients were identified in Tier 3. A more comprehensive validation of Tiers 2 and 3 was performed during FY 2022 that included patients at 5 sites seen during FY 2019 to FY 2022. Since yearly trends showed only about 8% of total patients were identified as having epilepsy through Tiers 2 and 3 we sought ≥ 20 patients per tier for the 5 sites for a total of 200 patients to ensure representation across the VHA. The final count was 126 patients for Tier 2 and 174 patients for Tier 3 (n = 300).

Gold Standard Criteria for Epilepsy Diagnosis

We used the International League Against Epilepsy (ILAE) definition of epilepsy for the validation of the 3 algorithm tiers. ILAE defines epilepsy as ≥ 2 unprovoked (or reflex) seizures occurring > 24 hours apart or 1 unprovoked (or reflex) seizure and a probability of further seizures similar to the general recurrence risk (≥ 60%) after 2 unprovoked seizures, occurring over the next 10 years.¹²

A standard protocol was provided to evaluators to identify patients using the VHA Computerized Patient Record System (Appendix 1). After review, evaluators categorized each patient in 1 of 4 ways: (1) Yes, definite: The patient’s health care practitioner (HCP) believes the patient has epilepsy and is treating with medication; (2) Yes, uncertain: The HCP has enough suspicion of epilepsy that a medication is prescribed, but uncertainty is expressed of the diagnosis; (3) No, definite: The HCP does not believe the patient has epilepsy and is therefore not treating with medication for seizure; (4) No, uncertain: The HCP is not treating with medication for epilepsy, because the diagnostic suspicion is not high enough, but there is suspicion for epilepsy.

As a quality improvement operational project, the Epilepsy National Program Office approved this validation project and determined that institutional review board approval was not required.

Statistical Analysis

Counts and percentages were computed for categories of epilepsy status. PPV of each tier was estimated with asymptotic 95% CIs.

Results

ICD-10 codes for 480 patients were evaluated in Tier 1 phase 1; 13.8% were documented with G40.xxx, 27.9% with R56.1, 34.4% with R56.9, and 24.0% with R40.4 (Appendix 2). In total, 68.1% fulfilled the criteria of epilepsy, 19.2% did not, and 12.7% were uncertain). From the validation of Tier 1 phase 2 (n = 625), the PPV of the algorithm for patients presumed to have epilepsy (definite and uncertain) was 85.1% (95% CI, 82.1%-87.8%) (Table).

Of 300 patients evaluated, 126 (42.0%) were evaluated for Tier 2 with a PPV of 61.9% (95% CI, 53.4%-70.4%), and 174 (58.0%) patients were evaluated for Tier 3 with a PPV of 59.8% (95% CI, 52.5%-67.1%. The PPV of the algorithm for patients presumed to have epilepsy (definite and uncertain) were combined to calculate the PPV. Estimates of VHA VWE counts were computed for each tier from FY 2014 to FY 2023 using the VSSC Neurology Cube (Figure 2). For all years, > 92% patients were classified using the Tier 1 definition.

Discussion

The development and validation of the 3-tier diagnostic algorithm represents an important advancement in the surveillance and management of epilepsy among veterans within the VHA. The validation of this algorithm also demonstrates its practical utility in a large, integrated health care system.

Specific challenges were encountered when attempting to use pre-existing algorithms; these challenges included differences in the usage patterns of diagnostic codes and the patterns of ASM use within the VHA. These challenges prompted the need for a tailored approach, which led to the development of this algorithm. The inclusion of additional ICD-10 codes led to further revisions and subsequent validation. While many of the basic concepts of the algorithm, including ICD codes and ASMs, could work in other institutions, it would be wise for health care organizations to develop their own algorithms because of certain variables, including organizational size, patient demographics, common comorbidities, and the specific configurations of electronic health records and administrative data systems.

Studies have shown that ICD-10 codes for epilepsy (G40.* and/or R56.9) perform well in identifying epilepsy whether they are assigned by neurologists (sensitivity, 97.7%; specificity, 44.1%; PPV, 96.2%; negative predictive value, 57.7%), or in emergency department or hospital discharges (PPV, 75.5%).^13,14 The pilot study of the algorithm’s Tier 1 development (phase 1) evaluated whether the selected ICD-10 diagnostic codes accurately included the VWE population within the VHA and revealed that while most codes (eg, epilepsy [G40.xxx]; posttraumatic seizures [R56.1]; and unspecified convulsions [R56.9]), had a low false positive rate (< 16%), the R40.4 code (transient alteration of awareness) had a higher false positivity of 42%. While this is not surprising given the broad spectrum of conditions that can manifest as transient alteration of awareness, it underscores the inherent challenges in diagnosing epilepsy using diagnosis codes.

In phase 2, the Tier 1 algorithm was validated as effective for identifying VWE in the VHA system, as its PPV was determined to be high (85%). In comparison, Tiers 2 and 3, whose criteria did not require data on VHA prescribed ASM use, had lower tiers of epilepsy predictability (PPV about 60% for both). This was thought to be acceptable because Tiers 2 and 3 represent a smaller population of the identified VWEs (about 8%). These VWEs may otherwise have been missed, partly because veterans are not required to get ASMs from the VHA.

Upon VHA implementation in FY 2021, this diagnostic algorithm exhibited significant clinical utility when integrated within the VSSC Neurology Cube. It facilitated an efficient approach to identifying VWEs using readily available databases. This led to better tracking of real-time epilepsy cases, which facilitated improving current resource allocation and targeted intervention strategies such as identification of drug-resistant epilepsy patients, optimizing strategies for telehealth and patient outreach for awareness of epilepsy care resources within VHA. Meanwhile, data acquired by the algorithm over the decade since its development (FY 2014 to FY 2023) contributed to more accurate epidemiologic information and identification of historic trends. Development of the algorithm represents one of the ways ECoEs have led to improved care for VWEs. ECoEs have been shown to improve health care for veterans in several metrics.¹⁵

A strength of this study is the rigorous multitiered validation process to confirm the diagnostic accuracy of ICD-10 codes against the gold standard ILAE definition of epilepsy to identify “definite” epilepsy cases within the VHA. The use of specific ICD codes further enhances the precision of epilepsy diagnoses. The inclusion of ASMs, which are sometimes prescribed for conditions other than epilepsy, could potentially inflate false positive rates.¹⁶

This study focused exclusively on the identification and validation of definite epilepsy cases within the VHA VSSC database, employing more stringent diagnostic criteria to ensure the highest level of certainty in ascertaining epilepsy. It is important to note there is a separate category of probable epilepsy, which involves a broader set of diagnostic criteria. While not covered in this study, probable epilepsy would be subject to future research and validation, which could provide insights into a wider spectrum of epilepsy diagnoses. Such future research could help refine the algorithm’s applicability and accuracy and potentially lead to more comprehensive surveillance and management strategies in clinical practice.

This study highlights the inherent challenges in leveraging administrative data for disease identification, particularly for conditions such as epilepsy, where diagnostic clarity can be complex. However, other conditions such as multiple sclerosis have noted similar success with the use of VHA administrative data for categorizing disease.¹⁷

Limitations

The algorithm discussed in this article is, in and of itself, generalizable. However, the validation process was unique to the VHA patient population, limiting the generalizability of the findings. Documentation practices and HCP attitudes within the VHA may differ from those in other health care settings. Identifying people with epilepsy can be challenging because of changing definitions of epilepsy over time. In addition to clinical evaluation, EEG and magnetic resonance imaging results, response to ASM treatment, and video-EEG monitoring of habitual events all can help establish the diagnosis. Therefore, studies may vary in how inclusive or exclusive the criteria are. ASMs such as gabapentin, pregabalin, carbamazepine, lamotrigine, topiramate, and valproate are used to treat other conditions, including headaches, generalized pain, and mood disorders. Consequently, including these ASMs in the Tier 1 definition may have increased the false positive rate. Additional research is needed to evaluate whether excluding these ASMs from the algorithm based on specific criteria (eg, dose of ASM used) can further refine the algorithm to identify patients with epilepsy.

Further refinement of this algorithm may also occur as technology changes. Future electronic health records may allow better tracking of different epilepsy factors, the integration of additional diagnostic criteria, and the use of natural language processing or other forms of artificial intelligence.

Conclusions

This study presents a significant step forward in epilepsy surveillance within the VHA. The algorithm offers a robust tool for identifying VWEs with good PPVs, facilitating better resource allocation and targeted care. Despite its limitations, this research lays a foundation for future advancements in the management and understanding of epilepsy within large health care systems. Since this VHA algorithm is based on ASMs and ICD diagnosis codes from patient records, other large managed health care systems also may be able to adapt this algorithm to their data specifications.

Epilepsy affects about 4.5 million people in the United States and 150,000 new individuals are diagnosed each year.^1,2 In 2019, epilepsy-attributable health care spending for noninstitutionalized people was around $5.4 billion and total epilepsy-attributable and epilepsy or seizure health care-related costs totaled $54 billion.³

Accurate surveillance of epilepsy in large health care systems can potentially improve health care delivery and resource allocation. A 2012 Institute of Medicine (IOM) report identified 13 recommendations to guide public health action on epilepsy, including validation of standard definitions for case ascertainment, identification of epilepsy through screening programs or protocols, and expansion of surveillance to better understand disease burden.⁴

A systematic review of validation studies concluded that it is reasonable to use administrative data to identify people with epilepsy in epidemiologic research. Combining The International Classification of Diseases (ICD) codes for epilepsy (ICD-10, G40-41; ICD-9, 345) with antiseizure medications (ASMs) could provide high positive predictive values (PPVs) and combining symptoms codes for convulsions (ICD-10, R56; ICD-9, 780.3, 780.39) with ASMs could lead to high sensitivity.⁵ However, identifying individuals with epilepsy from administrative data in large managed health care organizations is challenging.⁶ The IOM report noted that large managed health care organizations presented varying incidence and prevalence estimates due to differing methodology, geographic area, demographics, and definitions of epilepsy.

The Veterans Health Administration (VHA) is the largest integrated US health care system, providing care to > 9.1 million veterans.⁷ To improve the health and well-being of veterans with epilepsy (VWEs), a network of sites was established in 2008 called the US Department of Veterans Affairs (VA) Epilepsy Centers of Excellence (ECoE). Subsequent to the creation of the ECoE, efforts were made to identify VWEs within VHA databases.^8,9 Prior to fiscal year (FY) 2016, the ECoE adopted a modified version of a well-established epilepsy diagnostic algorithm developed by Holden et al for large managed care organizations.¹⁰ The original algorithm identified patients by cross-matching ASMs with ICD-9 codes for an index year. But it failed to capture a considerable number of stable patients with epilepsy in the VHA due to incomplete documentation, and had false positives due to inclusion of patients identified from diagnostic clinics. The modified algorithm the ECoE used prior to FY 2016 considered additional prior years and excluded encounters from diagnostic clinics. The result was an improvement in the sensitivity and specificity of the algorithm. Researchers evaluating 500 patients with epilepsy estimated that the modified algorithm had a PPV of 82.0% (95% CI, 78.6%-85.4%).¹¹

After implementation of ICD-10 codes in the VHA in FY 2016, the task of reliably and efficiently identifying VWE led to a 3-tier algorithm. This article presents a validation of the different tiers of this algorithm after the implementation of ICD-10 diagnosis codes and summarizes the surveillance data collected over the years within the VHA showing the trends of epilepsy.

Methods

The VHA National Neurology office commissioned a Neurology Cube dashboard in FY 2021 in collaboration with VHA Support Service Center (VSSC) for reporting and surveillance of VWEs as a quality improvement initiative. The Neurology Cube uses a 3-tier system for identifying VWE in the VHA databases. VSSC programmers extract data from the VHA Corporate Data Warehouse (CDW) and utilize Microsoft SQL Server and Microsoft Power BI for Neurology Cube reports. The 3-tier system identifies VWE and divides them into distinct groups. The first tier identifies VWE with the highest degree of confidence; Tiers 2 and 3 represent identification with successively lesser degrees of confidence (Figure 1).

Tier 1

Definition. For a given index year and the preceding 2 years, any of following diagnosis codes on ≥ 1 clinical encounter are considered: 345.xx (epilepsy in ICD-9), 780.3x (other convulsions in ICD-9), G40.xxx (epilepsy in ICD-10), R40.4 (transient alteration of awareness), R56.1 (posttraumatic seizures), or R56.9 (unspecified convulsions). To reduce false positive rates, EEG clinic visits, which may include long-term monitoring, are excluded. Patients identified with ICD codes are then evaluated for an ASM prescription for ≥ 30 days during the index year. ASMs are listed in Appendix 1.

Validation. The development and validation of ICD-9 diagnosis codes crossmatched with an ASM prescription in the VHA has been published elsewhere.¹¹ In FY 2017, after implementation of ICD-10 diagnostic codes, Tier 1 development and validation was performed in 2 phases. Even though Tier 1 study phases were conducted and completed during FY 2017, the patients for Tier 1 were identified from evaluation of FY 2016 data (October 1, 2015, to September 30, 2016). After the pilot analysis, the Tier 1 definition was implemented, and a chart review of 625 randomized patients was conducted at 5 sites for validation. Adequate preliminary data was not available to perform a sample size estimation for this study. Therefore, a practical target of 125 patients was set for Tier 1 from each site to obtain a final sample size of 625 patients. This second phase validated that the crossmatch of ICD-10 diagnosis codes with ASMs had a high PPV for identifying VWE.

Tiers 2 and 3

Definitions. For an index year, Tier 2 includes patients with ≥ 1 inpatient encounter documentation of either ICD-9 345.xx or ICD-10 G40.xxx, excluding EEG clinics. Tier 3 Includes patients who have had ≥ 2 outpatient encounters with diagnosis codes 345.xx or G40.xxx on 2 separate days, excluding EEG clinics. Tiers 2 and 3 do not require ASM prescriptions; this helps to identify VWEs who may be getting their medications outside of VHA or those who have received a new diagnosis.

Validations. Tiers 2 and 3 were included in the epilepsy identification algorithm in FY 2021 after validation was performed on a sample of 8 patients in each tier. Five patients were subsequently identified as having epilepsy in Tier 2 and 6 patients were identified in Tier 3. A more comprehensive validation of Tiers 2 and 3 was performed during FY 2022 that included patients at 5 sites seen during FY 2019 to FY 2022. Since yearly trends showed only about 8% of total patients were identified as having epilepsy through Tiers 2 and 3 we sought ≥ 20 patients per tier for the 5 sites for a total of 200 patients to ensure representation across the VHA. The final count was 126 patients for Tier 2 and 174 patients for Tier 3 (n = 300).

Gold Standard Criteria for Epilepsy Diagnosis

We used the International League Against Epilepsy (ILAE) definition of epilepsy for the validation of the 3 algorithm tiers. ILAE defines epilepsy as ≥ 2 unprovoked (or reflex) seizures occurring > 24 hours apart or 1 unprovoked (or reflex) seizure and a probability of further seizures similar to the general recurrence risk (≥ 60%) after 2 unprovoked seizures, occurring over the next 10 years.¹²

A standard protocol was provided to evaluators to identify patients using the VHA Computerized Patient Record System (Appendix 1). After review, evaluators categorized each patient in 1 of 4 ways: (1) Yes, definite: The patient’s health care practitioner (HCP) believes the patient has epilepsy and is treating with medication; (2) Yes, uncertain: The HCP has enough suspicion of epilepsy that a medication is prescribed, but uncertainty is expressed of the diagnosis; (3) No, definite: The HCP does not believe the patient has epilepsy and is therefore not treating with medication for seizure; (4) No, uncertain: The HCP is not treating with medication for epilepsy, because the diagnostic suspicion is not high enough, but there is suspicion for epilepsy.

As a quality improvement operational project, the Epilepsy National Program Office approved this validation project and determined that institutional review board approval was not required.

Statistical Analysis

Counts and percentages were computed for categories of epilepsy status. PPV of each tier was estimated with asymptotic 95% CIs.

Results

ICD-10 codes for 480 patients were evaluated in Tier 1 phase 1; 13.8% were documented with G40.xxx, 27.9% with R56.1, 34.4% with R56.9, and 24.0% with R40.4 (Appendix 2). In total, 68.1% fulfilled the criteria of epilepsy, 19.2% did not, and 12.7% were uncertain). From the validation of Tier 1 phase 2 (n = 625), the PPV of the algorithm for patients presumed to have epilepsy (definite and uncertain) was 85.1% (95% CI, 82.1%-87.8%) (Table).

Of 300 patients evaluated, 126 (42.0%) were evaluated for Tier 2 with a PPV of 61.9% (95% CI, 53.4%-70.4%), and 174 (58.0%) patients were evaluated for Tier 3 with a PPV of 59.8% (95% CI, 52.5%-67.1%. The PPV of the algorithm for patients presumed to have epilepsy (definite and uncertain) were combined to calculate the PPV. Estimates of VHA VWE counts were computed for each tier from FY 2014 to FY 2023 using the VSSC Neurology Cube (Figure 2). For all years, > 92% patients were classified using the Tier 1 definition.

Discussion

The development and validation of the 3-tier diagnostic algorithm represents an important advancement in the surveillance and management of epilepsy among veterans within the VHA. The validation of this algorithm also demonstrates its practical utility in a large, integrated health care system.

Specific challenges were encountered when attempting to use pre-existing algorithms; these challenges included differences in the usage patterns of diagnostic codes and the patterns of ASM use within the VHA. These challenges prompted the need for a tailored approach, which led to the development of this algorithm. The inclusion of additional ICD-10 codes led to further revisions and subsequent validation. While many of the basic concepts of the algorithm, including ICD codes and ASMs, could work in other institutions, it would be wise for health care organizations to develop their own algorithms because of certain variables, including organizational size, patient demographics, common comorbidities, and the specific configurations of electronic health records and administrative data systems.

Studies have shown that ICD-10 codes for epilepsy (G40.* and/or R56.9) perform well in identifying epilepsy whether they are assigned by neurologists (sensitivity, 97.7%; specificity, 44.1%; PPV, 96.2%; negative predictive value, 57.7%), or in emergency department or hospital discharges (PPV, 75.5%).^13,14 The pilot study of the algorithm’s Tier 1 development (phase 1) evaluated whether the selected ICD-10 diagnostic codes accurately included the VWE population within the VHA and revealed that while most codes (eg, epilepsy [G40.xxx]; posttraumatic seizures [R56.1]; and unspecified convulsions [R56.9]), had a low false positive rate (< 16%), the R40.4 code (transient alteration of awareness) had a higher false positivity of 42%. While this is not surprising given the broad spectrum of conditions that can manifest as transient alteration of awareness, it underscores the inherent challenges in diagnosing epilepsy using diagnosis codes.

In phase 2, the Tier 1 algorithm was validated as effective for identifying VWE in the VHA system, as its PPV was determined to be high (85%). In comparison, Tiers 2 and 3, whose criteria did not require data on VHA prescribed ASM use, had lower tiers of epilepsy predictability (PPV about 60% for both). This was thought to be acceptable because Tiers 2 and 3 represent a smaller population of the identified VWEs (about 8%). These VWEs may otherwise have been missed, partly because veterans are not required to get ASMs from the VHA.

Upon VHA implementation in FY 2021, this diagnostic algorithm exhibited significant clinical utility when integrated within the VSSC Neurology Cube. It facilitated an efficient approach to identifying VWEs using readily available databases. This led to better tracking of real-time epilepsy cases, which facilitated improving current resource allocation and targeted intervention strategies such as identification of drug-resistant epilepsy patients, optimizing strategies for telehealth and patient outreach for awareness of epilepsy care resources within VHA. Meanwhile, data acquired by the algorithm over the decade since its development (FY 2014 to FY 2023) contributed to more accurate epidemiologic information and identification of historic trends. Development of the algorithm represents one of the ways ECoEs have led to improved care for VWEs. ECoEs have been shown to improve health care for veterans in several metrics.¹⁵

A strength of this study is the rigorous multitiered validation process to confirm the diagnostic accuracy of ICD-10 codes against the gold standard ILAE definition of epilepsy to identify “definite” epilepsy cases within the VHA. The use of specific ICD codes further enhances the precision of epilepsy diagnoses. The inclusion of ASMs, which are sometimes prescribed for conditions other than epilepsy, could potentially inflate false positive rates.¹⁶

This study focused exclusively on the identification and validation of definite epilepsy cases within the VHA VSSC database, employing more stringent diagnostic criteria to ensure the highest level of certainty in ascertaining epilepsy. It is important to note there is a separate category of probable epilepsy, which involves a broader set of diagnostic criteria. While not covered in this study, probable epilepsy would be subject to future research and validation, which could provide insights into a wider spectrum of epilepsy diagnoses. Such future research could help refine the algorithm’s applicability and accuracy and potentially lead to more comprehensive surveillance and management strategies in clinical practice.

This study highlights the inherent challenges in leveraging administrative data for disease identification, particularly for conditions such as epilepsy, where diagnostic clarity can be complex. However, other conditions such as multiple sclerosis have noted similar success with the use of VHA administrative data for categorizing disease.¹⁷

Limitations

The algorithm discussed in this article is, in and of itself, generalizable. However, the validation process was unique to the VHA patient population, limiting the generalizability of the findings. Documentation practices and HCP attitudes within the VHA may differ from those in other health care settings. Identifying people with epilepsy can be challenging because of changing definitions of epilepsy over time. In addition to clinical evaluation, EEG and magnetic resonance imaging results, response to ASM treatment, and video-EEG monitoring of habitual events all can help establish the diagnosis. Therefore, studies may vary in how inclusive or exclusive the criteria are. ASMs such as gabapentin, pregabalin, carbamazepine, lamotrigine, topiramate, and valproate are used to treat other conditions, including headaches, generalized pain, and mood disorders. Consequently, including these ASMs in the Tier 1 definition may have increased the false positive rate. Additional research is needed to evaluate whether excluding these ASMs from the algorithm based on specific criteria (eg, dose of ASM used) can further refine the algorithm to identify patients with epilepsy.

Further refinement of this algorithm may also occur as technology changes. Future electronic health records may allow better tracking of different epilepsy factors, the integration of additional diagnostic criteria, and the use of natural language processing or other forms of artificial intelligence.

Conclusions

This study presents a significant step forward in epilepsy surveillance within the VHA. The algorithm offers a robust tool for identifying VWEs with good PPVs, facilitating better resource allocation and targeted care. Despite its limitations, this research lays a foundation for future advancements in the management and understanding of epilepsy within large health care systems. Since this VHA algorithm is based on ASMs and ICD diagnosis codes from patient records, other large managed health care systems also may be able to adapt this algorithm to their data specifications.

Discussion

A diagnosis of dural arteriovenous fistula (dAVF) was made. Lesions involving the spinal cord are traditionally classified by location as extradural, intradural/extramedullary, or intramedullary. Intramedullary spinal cord abnormalities pose considerable diagnostic and management challenges because of the risks of biopsy in this location and the added potential for morbidity and mortality from improperly treated lesions. Although MRI is the preferred imaging modality, PET/CT and magnetic resonance angiography (MRA) may also help narrow the differential diagnosis and potentially avoid complications from an invasive biopsy.¹ This patient’s intramedullary lesion, which represented a dAVF, posed a diagnostic challenge; after diagnosis, it was successfully managed conservatively with dexamethasone and physical therapy.

Intradural tumors account for 2% to 4% of all primary central nervous system (CNS) tumors.² Ependymomas account for 50% to 60% of intramedullary tumors in adults, while astrocytomas account for about 60% of all lesions in children and adolescents.^3,4 The differential diagnosis for intramedullary tumors also includes hemangioblastoma, metastases, primary CNS lymphoma, germ cell tumors, and gangliogliomas.^5,6

Intramedullary metastases remain rare, although the incidence is rising with improvements in oncologic and supportive treatments. Autopsy studies conducted decades ago demonstrated that about 0.9% to 2.1% of patients with systemic cancer have intramedullary metastases at death.^7,8 In patients with an established history of malignancy, a metastatic intramedullary tumor should be placed higher on the differential diagnosis. Intramedullary metastases most often occur in the setting of widespread metastatic disease. A systematic review of the literature on patients with lung cancer (small cell and non-small cell lung carcinomas) and ≥ 1 intramedullary spinal cord metastasis demonstrated that 55.8% of patients had concurrent brain metastases, 20.0% had leptomeningeal carcinomatosis, and 19.5% had vertebral metastases.⁹ While about half of all intramedullary metastases are associated with lung cancer, other common malignancies that metastasize to this area include colorectal, breast, and renal cell carcinoma, as well as lymphoma and melanoma primaries.^10,11

On imaging, intramedullary metastases often appear as several short, studded segments with surrounding edema, typically out of proportion to the size of the lesion.¹ By contrast, astrocytomas and ependymomas often span multiple segments, and enhancement patterns can vary depending on the subtype and grade. Glioblastoma multiforme, or grade 4 IDH wild-type astrocytomas, demonstrate an irregular, heterogeneous pattern of enhancement. Hemangioblastomas vary in size and are classically hypointense to isointense on T1-weighted sequences, isointense to hyperintense on T2-weighted sequences, and demonstrate avid enhancement on T1- postcontrast images. In large hemangioblastomas, flow voids due to prominent vasculature may be visualized.

Numerous nonneoplastic tumor mimics can obscure the differential diagnosis. Vascular malformations, including cavernomas and dAVFs, can also present with enhancement and edema. dAVFs are the most common type of spinal vascular malformation, accounting for about 70% of cases.¹² They are supplied by the radiculomeningeal arteries, whereas pial arteriovenous malformations (AVMs) are supplied by the radiculomedullary and radiculopial arteries. On MRI, dAVFs usually have venous congestion with intramedullary edema, which appears as an ill-defined centromedullary hyperintensity on T2-weighted imaging over multiple segments. The spinal cord may appear swollen with atrophic changes in chronic cases. Spinal cord AVMs are rarer and have an intramedullary nidus. They usually demonstrate mixed heterogeneous signal on T1- and T2-weighted imaging due to blood products, while the nidus demonstrates a variable degree of enhancement. Serpiginous flow voids are seen both within the nidus and at the cord surface.

Demyelinating lesions of the spine may be seen in neuroinflammatory conditions such as multiple sclerosis, neuromyelitis optica spectrum disorder, acute transverse myelitis, and acute disseminated encephalomyelitis. In multiple sclerosis, lesions typically extend ≤ 2 vertebral segments in length, cover less than half of the vertebral cross-sectional area, and have a dorsolateral predilection.¹³ Active lesions may demonstrate enhancement along the rim or in a patchy pattern. In the presence of demyelinating lesions, there may occasionally appear to be an expansile mass with a syrinx.¹⁴

Infections such as tuberculosis and neurosarcoidosis should also remain on the differential diagnosis. On MRI, tuberculosis usually involves the thoracic cord and is typically rim-enhancing.¹⁵ If there are caseating granulomas, T2-weighted images may also demonstrate rim enhancement.¹⁶ Spinal sarcoidosis is unusual without intracranial involvement, and its appearance may include leptomeningeal enhancement, cord expansion, and hyperintense signal on T2- weighted imaging.¹⁷

Finally, iatrogenic causes are also possible, including radiation myelopathy and mechanical spinal cord injury. For radiation myelopathy, it is important to ascertain whether a patient has undergone prior radiotherapy in the region and to obtain the pertinent dosimetry. Spinal cord injury may cause a focal signal abnormality within the cord, with T2 hyperintensity; these foci may or may not present with enhancement, edema, or hematoma and therefore may resemble tumors.¹³

This patient presented with progressive right-sided lower extremity weakness and hypoesthesia and a history of a low-grade right renal/pelvic ureteral tumor. The immediate impression was that the thoracic intramedullary lesion represented a metastatic lesion. However, in the absence of any systemic or intracranial metastases, this progression was much less likely. An extensive interdisciplinary workup was conducted that included medical oncology, neurology, neuroradiology, neuro-oncology, neurosurgery, nuclear medicine, and radiation oncology. Neuroradiology and nuclear medicine identified a slightly hypermetabolic focus on the PET/CT from 1.5 years prior that correlated exactly with the same location as the lesion on the recent spinal MRI. This finding, along with the MRA, confirmed the diagnosis of a dAVF, which was successfully managed conservatively with dexamethasone and physical therapy, rather than through oncologic treatments such as radiotherapy

There remains debate regarding the utility of steroids in treating patients with dAVF. Although there are some case reports documenting that the edema associated with the dAVF responds to steroids, other case series have found that steroids may worsen outcomes in patients with dAVF, possibly due to increased venous hydrostatic pressure.

This case demonstrates the importance of an interdisciplinary workup when evaluating an intramedullary lesion, as well as maintaining a wide differential diagnosis, particularly in the absence of a history of polymetastatic cancer. All the clues (such as the slightly hypermetabolic focus on a PET/CT from 1.5 years prior) need to be obtained to comfortably reach a diagnosis in the absence of pathologic confirmation. These cases can be especially challenging due to the lack of pathologic confirmation, but by understanding the main differentiating features among the various etiologies and obtaining all available information, a correct diagnosis can be made without unnecessary interventions.

Discussion

A diagnosis of dural arteriovenous fistula (dAVF) was made. Lesions involving the spinal cord are traditionally classified by location as extradural, intradural/extramedullary, or intramedullary. Intramedullary spinal cord abnormalities pose considerable diagnostic and management challenges because of the risks of biopsy in this location and the added potential for morbidity and mortality from improperly treated lesions. Although MRI is the preferred imaging modality, PET/CT and magnetic resonance angiography (MRA) may also help narrow the differential diagnosis and potentially avoid complications from an invasive biopsy.¹ This patient’s intramedullary lesion, which represented a dAVF, posed a diagnostic challenge; after diagnosis, it was successfully managed conservatively with dexamethasone and physical therapy.

Intradural tumors account for 2% to 4% of all primary central nervous system (CNS) tumors.² Ependymomas account for 50% to 60% of intramedullary tumors in adults, while astrocytomas account for about 60% of all lesions in children and adolescents.^3,4 The differential diagnosis for intramedullary tumors also includes hemangioblastoma, metastases, primary CNS lymphoma, germ cell tumors, and gangliogliomas.^5,6

Intramedullary metastases remain rare, although the incidence is rising with improvements in oncologic and supportive treatments. Autopsy studies conducted decades ago demonstrated that about 0.9% to 2.1% of patients with systemic cancer have intramedullary metastases at death.^7,8 In patients with an established history of malignancy, a metastatic intramedullary tumor should be placed higher on the differential diagnosis. Intramedullary metastases most often occur in the setting of widespread metastatic disease. A systematic review of the literature on patients with lung cancer (small cell and non-small cell lung carcinomas) and ≥ 1 intramedullary spinal cord metastasis demonstrated that 55.8% of patients had concurrent brain metastases, 20.0% had leptomeningeal carcinomatosis, and 19.5% had vertebral metastases.⁹ While about half of all intramedullary metastases are associated with lung cancer, other common malignancies that metastasize to this area include colorectal, breast, and renal cell carcinoma, as well as lymphoma and melanoma primaries.^10,11

On imaging, intramedullary metastases often appear as several short, studded segments with surrounding edema, typically out of proportion to the size of the lesion.¹ By contrast, astrocytomas and ependymomas often span multiple segments, and enhancement patterns can vary depending on the subtype and grade. Glioblastoma multiforme, or grade 4 IDH wild-type astrocytomas, demonstrate an irregular, heterogeneous pattern of enhancement. Hemangioblastomas vary in size and are classically hypointense to isointense on T1-weighted sequences, isointense to hyperintense on T2-weighted sequences, and demonstrate avid enhancement on T1- postcontrast images. In large hemangioblastomas, flow voids due to prominent vasculature may be visualized.

Numerous nonneoplastic tumor mimics can obscure the differential diagnosis. Vascular malformations, including cavernomas and dAVFs, can also present with enhancement and edema. dAVFs are the most common type of spinal vascular malformation, accounting for about 70% of cases.¹² They are supplied by the radiculomeningeal arteries, whereas pial arteriovenous malformations (AVMs) are supplied by the radiculomedullary and radiculopial arteries. On MRI, dAVFs usually have venous congestion with intramedullary edema, which appears as an ill-defined centromedullary hyperintensity on T2-weighted imaging over multiple segments. The spinal cord may appear swollen with atrophic changes in chronic cases. Spinal cord AVMs are rarer and have an intramedullary nidus. They usually demonstrate mixed heterogeneous signal on T1- and T2-weighted imaging due to blood products, while the nidus demonstrates a variable degree of enhancement. Serpiginous flow voids are seen both within the nidus and at the cord surface.

Demyelinating lesions of the spine may be seen in neuroinflammatory conditions such as multiple sclerosis, neuromyelitis optica spectrum disorder, acute transverse myelitis, and acute disseminated encephalomyelitis. In multiple sclerosis, lesions typically extend ≤ 2 vertebral segments in length, cover less than half of the vertebral cross-sectional area, and have a dorsolateral predilection.¹³ Active lesions may demonstrate enhancement along the rim or in a patchy pattern. In the presence of demyelinating lesions, there may occasionally appear to be an expansile mass with a syrinx.¹⁴

Infections such as tuberculosis and neurosarcoidosis should also remain on the differential diagnosis. On MRI, tuberculosis usually involves the thoracic cord and is typically rim-enhancing.¹⁵ If there are caseating granulomas, T2-weighted images may also demonstrate rim enhancement.¹⁶ Spinal sarcoidosis is unusual without intracranial involvement, and its appearance may include leptomeningeal enhancement, cord expansion, and hyperintense signal on T2- weighted imaging.¹⁷

Finally, iatrogenic causes are also possible, including radiation myelopathy and mechanical spinal cord injury. For radiation myelopathy, it is important to ascertain whether a patient has undergone prior radiotherapy in the region and to obtain the pertinent dosimetry. Spinal cord injury may cause a focal signal abnormality within the cord, with T2 hyperintensity; these foci may or may not present with enhancement, edema, or hematoma and therefore may resemble tumors.¹³

This patient presented with progressive right-sided lower extremity weakness and hypoesthesia and a history of a low-grade right renal/pelvic ureteral tumor. The immediate impression was that the thoracic intramedullary lesion represented a metastatic lesion. However, in the absence of any systemic or intracranial metastases, this progression was much less likely. An extensive interdisciplinary workup was conducted that included medical oncology, neurology, neuroradiology, neuro-oncology, neurosurgery, nuclear medicine, and radiation oncology. Neuroradiology and nuclear medicine identified a slightly hypermetabolic focus on the PET/CT from 1.5 years prior that correlated exactly with the same location as the lesion on the recent spinal MRI. This finding, along with the MRA, confirmed the diagnosis of a dAVF, which was successfully managed conservatively with dexamethasone and physical therapy, rather than through oncologic treatments such as radiotherapy

There remains debate regarding the utility of steroids in treating patients with dAVF. Although there are some case reports documenting that the edema associated with the dAVF responds to steroids, other case series have found that steroids may worsen outcomes in patients with dAVF, possibly due to increased venous hydrostatic pressure.

This case demonstrates the importance of an interdisciplinary workup when evaluating an intramedullary lesion, as well as maintaining a wide differential diagnosis, particularly in the absence of a history of polymetastatic cancer. All the clues (such as the slightly hypermetabolic focus on a PET/CT from 1.5 years prior) need to be obtained to comfortably reach a diagnosis in the absence of pathologic confirmation. These cases can be especially challenging due to the lack of pathologic confirmation, but by understanding the main differentiating features among the various etiologies and obtaining all available information, a correct diagnosis can be made without unnecessary interventions.

Discussion

A diagnosis of dural arteriovenous fistula (dAVF) was made. Lesions involving the spinal cord are traditionally classified by location as extradural, intradural/extramedullary, or intramedullary. Intramedullary spinal cord abnormalities pose considerable diagnostic and management challenges because of the risks of biopsy in this location and the added potential for morbidity and mortality from improperly treated lesions. Although MRI is the preferred imaging modality, PET/CT and magnetic resonance angiography (MRA) may also help narrow the differential diagnosis and potentially avoid complications from an invasive biopsy.¹ This patient’s intramedullary lesion, which represented a dAVF, posed a diagnostic challenge; after diagnosis, it was successfully managed conservatively with dexamethasone and physical therapy.

Intradural tumors account for 2% to 4% of all primary central nervous system (CNS) tumors.² Ependymomas account for 50% to 60% of intramedullary tumors in adults, while astrocytomas account for about 60% of all lesions in children and adolescents.^3,4 The differential diagnosis for intramedullary tumors also includes hemangioblastoma, metastases, primary CNS lymphoma, germ cell tumors, and gangliogliomas.^5,6

Intramedullary metastases remain rare, although the incidence is rising with improvements in oncologic and supportive treatments. Autopsy studies conducted decades ago demonstrated that about 0.9% to 2.1% of patients with systemic cancer have intramedullary metastases at death.^7,8 In patients with an established history of malignancy, a metastatic intramedullary tumor should be placed higher on the differential diagnosis. Intramedullary metastases most often occur in the setting of widespread metastatic disease. A systematic review of the literature on patients with lung cancer (small cell and non-small cell lung carcinomas) and ≥ 1 intramedullary spinal cord metastasis demonstrated that 55.8% of patients had concurrent brain metastases, 20.0% had leptomeningeal carcinomatosis, and 19.5% had vertebral metastases.⁹ While about half of all intramedullary metastases are associated with lung cancer, other common malignancies that metastasize to this area include colorectal, breast, and renal cell carcinoma, as well as lymphoma and melanoma primaries.^10,11

On imaging, intramedullary metastases often appear as several short, studded segments with surrounding edema, typically out of proportion to the size of the lesion.¹ By contrast, astrocytomas and ependymomas often span multiple segments, and enhancement patterns can vary depending on the subtype and grade. Glioblastoma multiforme, or grade 4 IDH wild-type astrocytomas, demonstrate an irregular, heterogeneous pattern of enhancement. Hemangioblastomas vary in size and are classically hypointense to isointense on T1-weighted sequences, isointense to hyperintense on T2-weighted sequences, and demonstrate avid enhancement on T1- postcontrast images. In large hemangioblastomas, flow voids due to prominent vasculature may be visualized.

Numerous nonneoplastic tumor mimics can obscure the differential diagnosis. Vascular malformations, including cavernomas and dAVFs, can also present with enhancement and edema. dAVFs are the most common type of spinal vascular malformation, accounting for about 70% of cases.¹² They are supplied by the radiculomeningeal arteries, whereas pial arteriovenous malformations (AVMs) are supplied by the radiculomedullary and radiculopial arteries. On MRI, dAVFs usually have venous congestion with intramedullary edema, which appears as an ill-defined centromedullary hyperintensity on T2-weighted imaging over multiple segments. The spinal cord may appear swollen with atrophic changes in chronic cases. Spinal cord AVMs are rarer and have an intramedullary nidus. They usually demonstrate mixed heterogeneous signal on T1- and T2-weighted imaging due to blood products, while the nidus demonstrates a variable degree of enhancement. Serpiginous flow voids are seen both within the nidus and at the cord surface.

Demyelinating lesions of the spine may be seen in neuroinflammatory conditions such as multiple sclerosis, neuromyelitis optica spectrum disorder, acute transverse myelitis, and acute disseminated encephalomyelitis. In multiple sclerosis, lesions typically extend ≤ 2 vertebral segments in length, cover less than half of the vertebral cross-sectional area, and have a dorsolateral predilection.¹³ Active lesions may demonstrate enhancement along the rim or in a patchy pattern. In the presence of demyelinating lesions, there may occasionally appear to be an expansile mass with a syrinx.¹⁴

Infections such as tuberculosis and neurosarcoidosis should also remain on the differential diagnosis. On MRI, tuberculosis usually involves the thoracic cord and is typically rim-enhancing.¹⁵ If there are caseating granulomas, T2-weighted images may also demonstrate rim enhancement.¹⁶ Spinal sarcoidosis is unusual without intracranial involvement, and its appearance may include leptomeningeal enhancement, cord expansion, and hyperintense signal on T2- weighted imaging.¹⁷

Finally, iatrogenic causes are also possible, including radiation myelopathy and mechanical spinal cord injury. For radiation myelopathy, it is important to ascertain whether a patient has undergone prior radiotherapy in the region and to obtain the pertinent dosimetry. Spinal cord injury may cause a focal signal abnormality within the cord, with T2 hyperintensity; these foci may or may not present with enhancement, edema, or hematoma and therefore may resemble tumors.¹³

This patient presented with progressive right-sided lower extremity weakness and hypoesthesia and a history of a low-grade right renal/pelvic ureteral tumor. The immediate impression was that the thoracic intramedullary lesion represented a metastatic lesion. However, in the absence of any systemic or intracranial metastases, this progression was much less likely. An extensive interdisciplinary workup was conducted that included medical oncology, neurology, neuroradiology, neuro-oncology, neurosurgery, nuclear medicine, and radiation oncology. Neuroradiology and nuclear medicine identified a slightly hypermetabolic focus on the PET/CT from 1.5 years prior that correlated exactly with the same location as the lesion on the recent spinal MRI. This finding, along with the MRA, confirmed the diagnosis of a dAVF, which was successfully managed conservatively with dexamethasone and physical therapy, rather than through oncologic treatments such as radiotherapy

There remains debate regarding the utility of steroids in treating patients with dAVF. Although there are some case reports documenting that the edema associated with the dAVF responds to steroids, other case series have found that steroids may worsen outcomes in patients with dAVF, possibly due to increased venous hydrostatic pressure.

This case demonstrates the importance of an interdisciplinary workup when evaluating an intramedullary lesion, as well as maintaining a wide differential diagnosis, particularly in the absence of a history of polymetastatic cancer. All the clues (such as the slightly hypermetabolic focus on a PET/CT from 1.5 years prior) need to be obtained to comfortably reach a diagnosis in the absence of pathologic confirmation. These cases can be especially challenging due to the lack of pathologic confirmation, but by understanding the main differentiating features among the various etiologies and obtaining all available information, a correct diagnosis can be made without unnecessary interventions.

Hyperkalemia involves elevated serum potassium levels (> 5.0 mEq/L) and represents an important electrolyte disturbance due to its potentially severe consequences, including cardiac effects that can lead to dysrhythmia and even asystole and death.^1,2 In a US Medicare population, the prevalence of hyperkalemia has been estimated at 2.7% and is associated with substantial health care costs.³ The prevalence is even more marked in patients with preexisting conditions such as chronic kidney disease (CKD) and heart failure.^4,5

Hyperkalemia can result from multiple factors, including impaired renal function, adrenal disease, adverse drug reactions of angiotensin-converting enzyme inhibitors (ACEIs) and other medications, and heritable mutations.⁶ Hyperkalemia poses a considerable clinical risk, associated with adverse outcomes such as myocardial infarction and increased mortality in patients with CKD.^5,7,8 Electrocardiographic (ECG) changes associated with hyperkalemia play a vital role in guiding clinical decisions and treatment strategies.⁹ Understanding the pathophysiology, risk factors, and consequences of hyperkalemia, as well as the significance of ECG changes in its management, is essential for health care practitioners.

Case Presentation

An 81-year-old Hispanic man with a history of hypertension, hypothyroidism, gout, and CKD stage 3B presented to the emergency department with progressive weakness resulting in falls and culminating in an inability to ambulate independently. Additional symptoms included nausea, diarrhea, and myalgia. His vital signs were notable for a pulse of 41 beats/min. The physical examination was remarkable for significant weakness of the bilateral upper extremities, inability to bear his own weight, and bilateral lower extremity edema. His initial ECG upon arrival showed bradycardia with wide QRS, absent P waves, and peaked T waves (Figure 1a). These findings differed from his baseline ECG taken 1 year earlier, which showed sinus rhythm with premature atrial complexes and an old right bundle branch block (Figure 1b).

Medication review revealed that the patient was currently prescribed 100 mg allopurinol daily, 2.5 mg amlodipine daily, 10 mg atorvastatin at bedtime, 4 mg doxazosin daily, 112 mcg levothyroxine daily, 100 mg losartan daily, 25 mg metoprolol daily, and 0.4 mg tamsulosin daily. The patient had also been taking over-the-counter indomethacin for knee pain.

Based on the ECG results, he was treated with 0.083%/6 mL nebulized albuterol, 4.65 Mq/250 mL saline solution intravenous (IV) calcium gluconate, 10 units IV insulin with concomitant 50%/25 mL IV dextrose and 8.4 g of oral patiromer suspension. IV furosemide was held due to concern for renal function. The decision to proceed with hemodialysis was made. Repeat laboratory tests were performed, and an ECG obtained after treatment initiation but prior to hemodialysis demonstrated improvement of rate and T wave shortening (Figure 1c). The serum potassium level dropped from 9.8 mEq/L to 7.9 mEq/L (reference range, 3.5-5.0 mEq/L) (Table 1).

In addition to hemodialysis, sodium zirconium 10 g orally 3 times daily was added. Laboratory test results and an ECG was performed after dialysis continued to demonstrate improvement (Figure 1d). The patient’s potassium level decreased to 5.8 mEq/L, with the ECG demonstrating stability of heart rate and further improvement of the PR interval, QRS complex, and T waves.

Despite the established treatment regimen, potassium levels again rose to 6.7 mEq/L, but there were no significant changes in the ECG, and thus no medication changes were made (Figure 1e). Subsequent monitoring demonstrated a further increase in potassium to 7.4 mEq/L, with an ECG demonstrating a return to the baseline of 1 year prior. The patient underwent hemodialysis again and was given oral furosemide 60 mg every 12 hours. The potassium concentration after dialysis decreased to 4.7 mEq/L and remained stable, not going above 5.0 mEq/L on subsequent monitoring. The patient had resolution of all symptoms and was discharged.

Discussion

We have described in detail the presentation of each pathology and mechanisms of each treatment, starting with the patient’s initial condition that brought him to the emergency room—muscle weakness. Skeletal muscle weakness is a common manifestation of hyperkalemia, occurring in 20% to 40% of cases, and is more prevalent in severe elevations of potassium. Rarely, the weakness can progress to flaccid paralysis of the patient’s extremities and, in extreme cases, the diaphragm.

Muscle weakness progression occurs in a manner that resembles Guillain-Barré syndrome, starting in the lower extremities and ascending toward the upper extremities.¹⁰ This is known as secondary hyperkalemic periodic paralysis. Hyperkalemia lowers the transmembrane gradient in neurons, leading to neuronal depolarization independent of the degree of hyperkalemia. If the degree of hyperkalemia is large enough, this depolarization inactivates voltage-gated sodium channels, making neurons refractory to excitation. Electromyographical studies have shown reduction in the compounded muscle action potential.¹¹ The transient nature of this paralysis is reflected by rapid correction of weakness and paralysis when the electrolyte disorder is corrected.

The patient in this case also presented with bradycardia. The ECG manifestations of hyperkalemia can include atrial asystole, intraventricular conduction disturbances, peaked T waves, and widened QRS complexes. However, some patients with renal insufficiency may not exhibit ECG changes despite significantly elevated serum potassium levels.¹²

The severity of hyperkalemia is crucial in determining the associated ECG changes, with levels > 6.0 mEq/L presenting with abnormalities.¹³ ECG findings alone may not always accurately reflect the severity of hyperkalemia, as up to 60% of patients with potassium levels > 6.0 mEq/L may not show ECG changes.¹⁴ Additionally, extreme hyperkalemia can lead to inconsistent ECG findings, making it challenging to rely solely on ECG for diagnosis and monitoring.⁸ The level of potassium that causes these effects varies widely through patient populations.

The main mechanism by which hyperkalemia affects the heart’s conduction system is through voltage differences across the conduction fibers and eventual steady-state inactivation of sodium channels. This combination of mechanisms shortens the action potential duration, allowing more cardiomyocytes to undergo synchronized depolarization. This amalgamation of cardiomyocytes repolarizing can be reflected on ECGs as peaked T waves. As the action potential decreases, there is a period during which cardiomyocytes are prone to tachyarrhythmias and ventricular fibrillation.

A reduced action potential may lead to increased rates of depolarization and thus conduction, which in some scenarios may increase heart rate. As the levels of potassium rise, intracellular accumulation impedes the entry of sodium by decreasing the cation gradient across the cell membrane. This effectively slows the sinus nodes and prolongs the QRS by slowing the overall propagation of action potentials. By this mechanism, conduction delays, blocks, or asystole are manifested. The patient in this case showed conduction delays, peaked T waves, and disappearance of P waves when he first arrived.

Hyperkalemia Treatment

Hyperkalemia develops most commonly due to acute or chronic kidney diseases, as was the case with this patient. The patient’s hyperkalemia was also augmented by the use of nonsteroidal anti-inflammatory drugs (NSAIDs), which can directly affect renal function. A properly functioning kidney is responsible for excretion of up to 90% of ingested potassium, while the remainder is excreted through the gastrointestinal (GI) tract. Definitive treatment of hyperkalemia is mitigated primarily through these 2 organ systems. The treatment also includes transitory mechanisms of potassium reduction. The goal of each method is to preserve the action potential of cardiomyocytes and myocytes. This patient presented with acute symptomatic hyperkalemia and received various medications to acutely, transitorily, and definitively treat it.

Initial therapy included calcium gluconate, which functions to stabilize the myocardial cell membrane. Hyperkalemia decreases the resting membrane action potential of excitable cells and predisposes them to early depolarization and thus dysrhythmias. Calcium decreases the threshold potential across cells and offsets the overall gradient back to near normal levels.¹⁵ Calcium can be delivered through calcium gluconate or calcium chloride. Calcium chloride is not preferred because extravasation can cause pain, blistering and tissue ischemia. Central venous access is required, potentially delaying prompt treatment. Calcium acts rapidly after administration—within 1 to 3 minutes—but only lasts 30 to 60 minutes.¹⁶ Administration of calcium gluconate can be repeated as often as necessary, but patients must be monitored for adverse effects of calcium such as nausea, abdominal pain, polydipsia, polyuria, muscle weakness, and paresthesia. Care must be taken when patients are taking digoxin, because calcium may potentiate toxicity.¹⁷ Although calcium provides immediate benefits it does little to correct the underlying cause; other medications are required to remove potassium from the body.

Two medication classes have been proven to shift potassium intracellularly. The first are β-2 agonists, such as albuterol/levalbuterol, and the second is insulin. Both work through sodium-potassium-ATPase in a direct manner. β-2 agonists stimulate sodium-potassium-ATPase to move more potassium intracellularly, but these effects have been seen only with high doses of albuterol, typically 4× the standard dose of 0.5 mg in nebulized solutions to achieve decreases in potassium of 0.3 to 0.6 mEq/L, although some trials have reported decreases of 0.62 to 0.98 mEq/L.^15,18 These potassium-lowering effects of β-2 agonist are modest, but can be seen 20 to 30 minutes after administration and persist up to 1 to 2 hours. β-2 agonists are also readily affected by β blockers, which may reduce or negate the desired effect in hyperkalemia. For these reasons, a β-2 agonist should not be given as monotherapy and should be provided as an adjuvant to more independent therapies such as insulin. Insulin binds to receptors on muscle cells and increases the quantity of sodium-potassium-ATPase and glucose transporters. With this increase in influx pumps, surrounding tissues with higher resting membrane potentials can absorb the potassium load, thereby protecting cardiomyocytes.

Potassium Removal

Three methods are currently available to remove potassium from the body: GI excretion, renal excretion, and direct removal from the bloodstream. Under normal physiologic conditions, the kidneys account for about 90% of the body’s ability to remove potassium. Loop diuretics facilitate the removal of potassium by increasing urine production and have an additional potassium-wasting effect. Although the onset of action of loop diuretics is typically 30 to 60 minutes after oral administration, their effect can last for several hours. In this patient, furosemide was introduced later in the treatment plan to manage recurring hyperkalemia by enhancing renal potassium excretion.

Potassium binders such as patiromer act in the GI tract, effectively reducing serum potassium levels although with a slower onset of action than furosemide, generally taking hours to days to exert its effect. Both medications illustrate a tailored approach to managing potassium levels, adapted to the evolving needs and renal function of the patient. The last method is using hemodialysis—by far the most rapid method to remove potassium, but also the most invasive. The different methods of treating hyperkalemia are summarized in Table 2. This patient required multiple days of hemodialysis to completely correct the electrolyte disorder. Upon discharge, the patient continued oral furosemide 40 mg daily and eventually discontinued hemodialysis due to stable renal function.

Often, after correcting an inciting event, potassium stores in the body eventually stabilize and do not require additional follow-up. Patients prone to hyperkalemia should be thoroughly educated on medications to avoid (NSAIDs, ACEIs/ARBs, trimethoprim), an adequate low potassium diet, and symptoms that may warrant medical attention.¹⁹

Conclusions

This case illustrates the importance of recognizing the spectrum of manifestations of hyperkalemia, which ranged from muscle weakness to cardiac dysrhythmias. Management strategies for the patient included stabilization of cardiac membranes, potassium shifting, and potassium removal, each tailored to the patient’s individual clinical findings.

The case further illustrates the critical role of continuous monitoring and dynamic adjustment of therapeutic strategies in response to evolving clinical and laboratory findings. The initial and subsequent ECGs, alongside laboratory tests, were instrumental in guiding the adjustments needed in the treatment regimen, ensuring both the efficacy and safety of the interventions. This proactive approach can mitigate the risk of recurrent hyperkalemia and its complications.

Hyperkalemia involves elevated serum potassium levels (> 5.0 mEq/L) and represents an important electrolyte disturbance due to its potentially severe consequences, including cardiac effects that can lead to dysrhythmia and even asystole and death.^1,2 In a US Medicare population, the prevalence of hyperkalemia has been estimated at 2.7% and is associated with substantial health care costs.³ The prevalence is even more marked in patients with preexisting conditions such as chronic kidney disease (CKD) and heart failure.^4,5

Hyperkalemia can result from multiple factors, including impaired renal function, adrenal disease, adverse drug reactions of angiotensin-converting enzyme inhibitors (ACEIs) and other medications, and heritable mutations.⁶ Hyperkalemia poses a considerable clinical risk, associated with adverse outcomes such as myocardial infarction and increased mortality in patients with CKD.^5,7,8 Electrocardiographic (ECG) changes associated with hyperkalemia play a vital role in guiding clinical decisions and treatment strategies.⁹ Understanding the pathophysiology, risk factors, and consequences of hyperkalemia, as well as the significance of ECG changes in its management, is essential for health care practitioners.

Case Presentation

An 81-year-old Hispanic man with a history of hypertension, hypothyroidism, gout, and CKD stage 3B presented to the emergency department with progressive weakness resulting in falls and culminating in an inability to ambulate independently. Additional symptoms included nausea, diarrhea, and myalgia. His vital signs were notable for a pulse of 41 beats/min. The physical examination was remarkable for significant weakness of the bilateral upper extremities, inability to bear his own weight, and bilateral lower extremity edema. His initial ECG upon arrival showed bradycardia with wide QRS, absent P waves, and peaked T waves (Figure 1a). These findings differed from his baseline ECG taken 1 year earlier, which showed sinus rhythm with premature atrial complexes and an old right bundle branch block (Figure 1b).

Medication review revealed that the patient was currently prescribed 100 mg allopurinol daily, 2.5 mg amlodipine daily, 10 mg atorvastatin at bedtime, 4 mg doxazosin daily, 112 mcg levothyroxine daily, 100 mg losartan daily, 25 mg metoprolol daily, and 0.4 mg tamsulosin daily. The patient had also been taking over-the-counter indomethacin for knee pain.

Based on the ECG results, he was treated with 0.083%/6 mL nebulized albuterol, 4.65 Mq/250 mL saline solution intravenous (IV) calcium gluconate, 10 units IV insulin with concomitant 50%/25 mL IV dextrose and 8.4 g of oral patiromer suspension. IV furosemide was held due to concern for renal function. The decision to proceed with hemodialysis was made. Repeat laboratory tests were performed, and an ECG obtained after treatment initiation but prior to hemodialysis demonstrated improvement of rate and T wave shortening (Figure 1c). The serum potassium level dropped from 9.8 mEq/L to 7.9 mEq/L (reference range, 3.5-5.0 mEq/L) (Table 1).

In addition to hemodialysis, sodium zirconium 10 g orally 3 times daily was added. Laboratory test results and an ECG was performed after dialysis continued to demonstrate improvement (Figure 1d). The patient’s potassium level decreased to 5.8 mEq/L, with the ECG demonstrating stability of heart rate and further improvement of the PR interval, QRS complex, and T waves.

Despite the established treatment regimen, potassium levels again rose to 6.7 mEq/L, but there were no significant changes in the ECG, and thus no medication changes were made (Figure 1e). Subsequent monitoring demonstrated a further increase in potassium to 7.4 mEq/L, with an ECG demonstrating a return to the baseline of 1 year prior. The patient underwent hemodialysis again and was given oral furosemide 60 mg every 12 hours. The potassium concentration after dialysis decreased to 4.7 mEq/L and remained stable, not going above 5.0 mEq/L on subsequent monitoring. The patient had resolution of all symptoms and was discharged.

Discussion

We have described in detail the presentation of each pathology and mechanisms of each treatment, starting with the patient’s initial condition that brought him to the emergency room—muscle weakness. Skeletal muscle weakness is a common manifestation of hyperkalemia, occurring in 20% to 40% of cases, and is more prevalent in severe elevations of potassium. Rarely, the weakness can progress to flaccid paralysis of the patient’s extremities and, in extreme cases, the diaphragm.

Muscle weakness progression occurs in a manner that resembles Guillain-Barré syndrome, starting in the lower extremities and ascending toward the upper extremities.¹⁰ This is known as secondary hyperkalemic periodic paralysis. Hyperkalemia lowers the transmembrane gradient in neurons, leading to neuronal depolarization independent of the degree of hyperkalemia. If the degree of hyperkalemia is large enough, this depolarization inactivates voltage-gated sodium channels, making neurons refractory to excitation. Electromyographical studies have shown reduction in the compounded muscle action potential.¹¹ The transient nature of this paralysis is reflected by rapid correction of weakness and paralysis when the electrolyte disorder is corrected.

The patient in this case also presented with bradycardia. The ECG manifestations of hyperkalemia can include atrial asystole, intraventricular conduction disturbances, peaked T waves, and widened QRS complexes. However, some patients with renal insufficiency may not exhibit ECG changes despite significantly elevated serum potassium levels.¹²

The severity of hyperkalemia is crucial in determining the associated ECG changes, with levels > 6.0 mEq/L presenting with abnormalities.¹³ ECG findings alone may not always accurately reflect the severity of hyperkalemia, as up to 60% of patients with potassium levels > 6.0 mEq/L may not show ECG changes.¹⁴ Additionally, extreme hyperkalemia can lead to inconsistent ECG findings, making it challenging to rely solely on ECG for diagnosis and monitoring.⁸ The level of potassium that causes these effects varies widely through patient populations.

The main mechanism by which hyperkalemia affects the heart’s conduction system is through voltage differences across the conduction fibers and eventual steady-state inactivation of sodium channels. This combination of mechanisms shortens the action potential duration, allowing more cardiomyocytes to undergo synchronized depolarization. This amalgamation of cardiomyocytes repolarizing can be reflected on ECGs as peaked T waves. As the action potential decreases, there is a period during which cardiomyocytes are prone to tachyarrhythmias and ventricular fibrillation.

A reduced action potential may lead to increased rates of depolarization and thus conduction, which in some scenarios may increase heart rate. As the levels of potassium rise, intracellular accumulation impedes the entry of sodium by decreasing the cation gradient across the cell membrane. This effectively slows the sinus nodes and prolongs the QRS by slowing the overall propagation of action potentials. By this mechanism, conduction delays, blocks, or asystole are manifested. The patient in this case showed conduction delays, peaked T waves, and disappearance of P waves when he first arrived.

Hyperkalemia Treatment

Hyperkalemia develops most commonly due to acute or chronic kidney diseases, as was the case with this patient. The patient’s hyperkalemia was also augmented by the use of nonsteroidal anti-inflammatory drugs (NSAIDs), which can directly affect renal function. A properly functioning kidney is responsible for excretion of up to 90% of ingested potassium, while the remainder is excreted through the gastrointestinal (GI) tract. Definitive treatment of hyperkalemia is mitigated primarily through these 2 organ systems. The treatment also includes transitory mechanisms of potassium reduction. The goal of each method is to preserve the action potential of cardiomyocytes and myocytes. This patient presented with acute symptomatic hyperkalemia and received various medications to acutely, transitorily, and definitively treat it.

Initial therapy included calcium gluconate, which functions to stabilize the myocardial cell membrane. Hyperkalemia decreases the resting membrane action potential of excitable cells and predisposes them to early depolarization and thus dysrhythmias. Calcium decreases the threshold potential across cells and offsets the overall gradient back to near normal levels.¹⁵ Calcium can be delivered through calcium gluconate or calcium chloride. Calcium chloride is not preferred because extravasation can cause pain, blistering and tissue ischemia. Central venous access is required, potentially delaying prompt treatment. Calcium acts rapidly after administration—within 1 to 3 minutes—but only lasts 30 to 60 minutes.¹⁶ Administration of calcium gluconate can be repeated as often as necessary, but patients must be monitored for adverse effects of calcium such as nausea, abdominal pain, polydipsia, polyuria, muscle weakness, and paresthesia. Care must be taken when patients are taking digoxin, because calcium may potentiate toxicity.¹⁷ Although calcium provides immediate benefits it does little to correct the underlying cause; other medications are required to remove potassium from the body.

Two medication classes have been proven to shift potassium intracellularly. The first are β-2 agonists, such as albuterol/levalbuterol, and the second is insulin. Both work through sodium-potassium-ATPase in a direct manner. β-2 agonists stimulate sodium-potassium-ATPase to move more potassium intracellularly, but these effects have been seen only with high doses of albuterol, typically 4× the standard dose of 0.5 mg in nebulized solutions to achieve decreases in potassium of 0.3 to 0.6 mEq/L, although some trials have reported decreases of 0.62 to 0.98 mEq/L.^15,18 These potassium-lowering effects of β-2 agonist are modest, but can be seen 20 to 30 minutes after administration and persist up to 1 to 2 hours. β-2 agonists are also readily affected by β blockers, which may reduce or negate the desired effect in hyperkalemia. For these reasons, a β-2 agonist should not be given as monotherapy and should be provided as an adjuvant to more independent therapies such as insulin. Insulin binds to receptors on muscle cells and increases the quantity of sodium-potassium-ATPase and glucose transporters. With this increase in influx pumps, surrounding tissues with higher resting membrane potentials can absorb the potassium load, thereby protecting cardiomyocytes.

Potassium Removal

Three methods are currently available to remove potassium from the body: GI excretion, renal excretion, and direct removal from the bloodstream. Under normal physiologic conditions, the kidneys account for about 90% of the body’s ability to remove potassium. Loop diuretics facilitate the removal of potassium by increasing urine production and have an additional potassium-wasting effect. Although the onset of action of loop diuretics is typically 30 to 60 minutes after oral administration, their effect can last for several hours. In this patient, furosemide was introduced later in the treatment plan to manage recurring hyperkalemia by enhancing renal potassium excretion.

Potassium binders such as patiromer act in the GI tract, effectively reducing serum potassium levels although with a slower onset of action than furosemide, generally taking hours to days to exert its effect. Both medications illustrate a tailored approach to managing potassium levels, adapted to the evolving needs and renal function of the patient. The last method is using hemodialysis—by far the most rapid method to remove potassium, but also the most invasive. The different methods of treating hyperkalemia are summarized in Table 2. This patient required multiple days of hemodialysis to completely correct the electrolyte disorder. Upon discharge, the patient continued oral furosemide 40 mg daily and eventually discontinued hemodialysis due to stable renal function.

Often, after correcting an inciting event, potassium stores in the body eventually stabilize and do not require additional follow-up. Patients prone to hyperkalemia should be thoroughly educated on medications to avoid (NSAIDs, ACEIs/ARBs, trimethoprim), an adequate low potassium diet, and symptoms that may warrant medical attention.¹⁹

Conclusions

This case illustrates the importance of recognizing the spectrum of manifestations of hyperkalemia, which ranged from muscle weakness to cardiac dysrhythmias. Management strategies for the patient included stabilization of cardiac membranes, potassium shifting, and potassium removal, each tailored to the patient’s individual clinical findings.

The case further illustrates the critical role of continuous monitoring and dynamic adjustment of therapeutic strategies in response to evolving clinical and laboratory findings. The initial and subsequent ECGs, alongside laboratory tests, were instrumental in guiding the adjustments needed in the treatment regimen, ensuring both the efficacy and safety of the interventions. This proactive approach can mitigate the risk of recurrent hyperkalemia and its complications.

Hyperkalemia involves elevated serum potassium levels (> 5.0 mEq/L) and represents an important electrolyte disturbance due to its potentially severe consequences, including cardiac effects that can lead to dysrhythmia and even asystole and death.^1,2 In a US Medicare population, the prevalence of hyperkalemia has been estimated at 2.7% and is associated with substantial health care costs.³ The prevalence is even more marked in patients with preexisting conditions such as chronic kidney disease (CKD) and heart failure.^4,5

Hyperkalemia can result from multiple factors, including impaired renal function, adrenal disease, adverse drug reactions of angiotensin-converting enzyme inhibitors (ACEIs) and other medications, and heritable mutations.⁶ Hyperkalemia poses a considerable clinical risk, associated with adverse outcomes such as myocardial infarction and increased mortality in patients with CKD.^5,7,8 Electrocardiographic (ECG) changes associated with hyperkalemia play a vital role in guiding clinical decisions and treatment strategies.⁹ Understanding the pathophysiology, risk factors, and consequences of hyperkalemia, as well as the significance of ECG changes in its management, is essential for health care practitioners.

Case Presentation

An 81-year-old Hispanic man with a history of hypertension, hypothyroidism, gout, and CKD stage 3B presented to the emergency department with progressive weakness resulting in falls and culminating in an inability to ambulate independently. Additional symptoms included nausea, diarrhea, and myalgia. His vital signs were notable for a pulse of 41 beats/min. The physical examination was remarkable for significant weakness of the bilateral upper extremities, inability to bear his own weight, and bilateral lower extremity edema. His initial ECG upon arrival showed bradycardia with wide QRS, absent P waves, and peaked T waves (Figure 1a). These findings differed from his baseline ECG taken 1 year earlier, which showed sinus rhythm with premature atrial complexes and an old right bundle branch block (Figure 1b).

Medication review revealed that the patient was currently prescribed 100 mg allopurinol daily, 2.5 mg amlodipine daily, 10 mg atorvastatin at bedtime, 4 mg doxazosin daily, 112 mcg levothyroxine daily, 100 mg losartan daily, 25 mg metoprolol daily, and 0.4 mg tamsulosin daily. The patient had also been taking over-the-counter indomethacin for knee pain.

Based on the ECG results, he was treated with 0.083%/6 mL nebulized albuterol, 4.65 Mq/250 mL saline solution intravenous (IV) calcium gluconate, 10 units IV insulin with concomitant 50%/25 mL IV dextrose and 8.4 g of oral patiromer suspension. IV furosemide was held due to concern for renal function. The decision to proceed with hemodialysis was made. Repeat laboratory tests were performed, and an ECG obtained after treatment initiation but prior to hemodialysis demonstrated improvement of rate and T wave shortening (Figure 1c). The serum potassium level dropped from 9.8 mEq/L to 7.9 mEq/L (reference range, 3.5-5.0 mEq/L) (Table 1).

In addition to hemodialysis, sodium zirconium 10 g orally 3 times daily was added. Laboratory test results and an ECG was performed after dialysis continued to demonstrate improvement (Figure 1d). The patient’s potassium level decreased to 5.8 mEq/L, with the ECG demonstrating stability of heart rate and further improvement of the PR interval, QRS complex, and T waves.

Despite the established treatment regimen, potassium levels again rose to 6.7 mEq/L, but there were no significant changes in the ECG, and thus no medication changes were made (Figure 1e). Subsequent monitoring demonstrated a further increase in potassium to 7.4 mEq/L, with an ECG demonstrating a return to the baseline of 1 year prior. The patient underwent hemodialysis again and was given oral furosemide 60 mg every 12 hours. The potassium concentration after dialysis decreased to 4.7 mEq/L and remained stable, not going above 5.0 mEq/L on subsequent monitoring. The patient had resolution of all symptoms and was discharged.

Discussion

We have described in detail the presentation of each pathology and mechanisms of each treatment, starting with the patient’s initial condition that brought him to the emergency room—muscle weakness. Skeletal muscle weakness is a common manifestation of hyperkalemia, occurring in 20% to 40% of cases, and is more prevalent in severe elevations of potassium. Rarely, the weakness can progress to flaccid paralysis of the patient’s extremities and, in extreme cases, the diaphragm.

Muscle weakness progression occurs in a manner that resembles Guillain-Barré syndrome, starting in the lower extremities and ascending toward the upper extremities.¹⁰ This is known as secondary hyperkalemic periodic paralysis. Hyperkalemia lowers the transmembrane gradient in neurons, leading to neuronal depolarization independent of the degree of hyperkalemia. If the degree of hyperkalemia is large enough, this depolarization inactivates voltage-gated sodium channels, making neurons refractory to excitation. Electromyographical studies have shown reduction in the compounded muscle action potential.¹¹ The transient nature of this paralysis is reflected by rapid correction of weakness and paralysis when the electrolyte disorder is corrected.

The patient in this case also presented with bradycardia. The ECG manifestations of hyperkalemia can include atrial asystole, intraventricular conduction disturbances, peaked T waves, and widened QRS complexes. However, some patients with renal insufficiency may not exhibit ECG changes despite significantly elevated serum potassium levels.¹²

The severity of hyperkalemia is crucial in determining the associated ECG changes, with levels > 6.0 mEq/L presenting with abnormalities.¹³ ECG findings alone may not always accurately reflect the severity of hyperkalemia, as up to 60% of patients with potassium levels > 6.0 mEq/L may not show ECG changes.¹⁴ Additionally, extreme hyperkalemia can lead to inconsistent ECG findings, making it challenging to rely solely on ECG for diagnosis and monitoring.⁸ The level of potassium that causes these effects varies widely through patient populations.

The main mechanism by which hyperkalemia affects the heart’s conduction system is through voltage differences across the conduction fibers and eventual steady-state inactivation of sodium channels. This combination of mechanisms shortens the action potential duration, allowing more cardiomyocytes to undergo synchronized depolarization. This amalgamation of cardiomyocytes repolarizing can be reflected on ECGs as peaked T waves. As the action potential decreases, there is a period during which cardiomyocytes are prone to tachyarrhythmias and ventricular fibrillation.

A reduced action potential may lead to increased rates of depolarization and thus conduction, which in some scenarios may increase heart rate. As the levels of potassium rise, intracellular accumulation impedes the entry of sodium by decreasing the cation gradient across the cell membrane. This effectively slows the sinus nodes and prolongs the QRS by slowing the overall propagation of action potentials. By this mechanism, conduction delays, blocks, or asystole are manifested. The patient in this case showed conduction delays, peaked T waves, and disappearance of P waves when he first arrived.

Hyperkalemia Treatment

Hyperkalemia develops most commonly due to acute or chronic kidney diseases, as was the case with this patient. The patient’s hyperkalemia was also augmented by the use of nonsteroidal anti-inflammatory drugs (NSAIDs), which can directly affect renal function. A properly functioning kidney is responsible for excretion of up to 90% of ingested potassium, while the remainder is excreted through the gastrointestinal (GI) tract. Definitive treatment of hyperkalemia is mitigated primarily through these 2 organ systems. The treatment also includes transitory mechanisms of potassium reduction. The goal of each method is to preserve the action potential of cardiomyocytes and myocytes. This patient presented with acute symptomatic hyperkalemia and received various medications to acutely, transitorily, and definitively treat it.

Initial therapy included calcium gluconate, which functions to stabilize the myocardial cell membrane. Hyperkalemia decreases the resting membrane action potential of excitable cells and predisposes them to early depolarization and thus dysrhythmias. Calcium decreases the threshold potential across cells and offsets the overall gradient back to near normal levels.¹⁵ Calcium can be delivered through calcium gluconate or calcium chloride. Calcium chloride is not preferred because extravasation can cause pain, blistering and tissue ischemia. Central venous access is required, potentially delaying prompt treatment. Calcium acts rapidly after administration—within 1 to 3 minutes—but only lasts 30 to 60 minutes.¹⁶ Administration of calcium gluconate can be repeated as often as necessary, but patients must be monitored for adverse effects of calcium such as nausea, abdominal pain, polydipsia, polyuria, muscle weakness, and paresthesia. Care must be taken when patients are taking digoxin, because calcium may potentiate toxicity.¹⁷ Although calcium provides immediate benefits it does little to correct the underlying cause; other medications are required to remove potassium from the body.

Two medication classes have been proven to shift potassium intracellularly. The first are β-2 agonists, such as albuterol/levalbuterol, and the second is insulin. Both work through sodium-potassium-ATPase in a direct manner. β-2 agonists stimulate sodium-potassium-ATPase to move more potassium intracellularly, but these effects have been seen only with high doses of albuterol, typically 4× the standard dose of 0.5 mg in nebulized solutions to achieve decreases in potassium of 0.3 to 0.6 mEq/L, although some trials have reported decreases of 0.62 to 0.98 mEq/L.^15,18 These potassium-lowering effects of β-2 agonist are modest, but can be seen 20 to 30 minutes after administration and persist up to 1 to 2 hours. β-2 agonists are also readily affected by β blockers, which may reduce or negate the desired effect in hyperkalemia. For these reasons, a β-2 agonist should not be given as monotherapy and should be provided as an adjuvant to more independent therapies such as insulin. Insulin binds to receptors on muscle cells and increases the quantity of sodium-potassium-ATPase and glucose transporters. With this increase in influx pumps, surrounding tissues with higher resting membrane potentials can absorb the potassium load, thereby protecting cardiomyocytes.

Potassium Removal

Three methods are currently available to remove potassium from the body: GI excretion, renal excretion, and direct removal from the bloodstream. Under normal physiologic conditions, the kidneys account for about 90% of the body’s ability to remove potassium. Loop diuretics facilitate the removal of potassium by increasing urine production and have an additional potassium-wasting effect. Although the onset of action of loop diuretics is typically 30 to 60 minutes after oral administration, their effect can last for several hours. In this patient, furosemide was introduced later in the treatment plan to manage recurring hyperkalemia by enhancing renal potassium excretion.

Potassium binders such as patiromer act in the GI tract, effectively reducing serum potassium levels although with a slower onset of action than furosemide, generally taking hours to days to exert its effect. Both medications illustrate a tailored approach to managing potassium levels, adapted to the evolving needs and renal function of the patient. The last method is using hemodialysis—by far the most rapid method to remove potassium, but also the most invasive. The different methods of treating hyperkalemia are summarized in Table 2. This patient required multiple days of hemodialysis to completely correct the electrolyte disorder. Upon discharge, the patient continued oral furosemide 40 mg daily and eventually discontinued hemodialysis due to stable renal function.

Often, after correcting an inciting event, potassium stores in the body eventually stabilize and do not require additional follow-up. Patients prone to hyperkalemia should be thoroughly educated on medications to avoid (NSAIDs, ACEIs/ARBs, trimethoprim), an adequate low potassium diet, and symptoms that may warrant medical attention.¹⁹

Conclusions

This case illustrates the importance of recognizing the spectrum of manifestations of hyperkalemia, which ranged from muscle weakness to cardiac dysrhythmias. Management strategies for the patient included stabilization of cardiac membranes, potassium shifting, and potassium removal, each tailored to the patient’s individual clinical findings.

The case further illustrates the critical role of continuous monitoring and dynamic adjustment of therapeutic strategies in response to evolving clinical and laboratory findings. The initial and subsequent ECGs, alongside laboratory tests, were instrumental in guiding the adjustments needed in the treatment regimen, ensuring both the efficacy and safety of the interventions. This proactive approach can mitigate the risk of recurrent hyperkalemia and its complications.