CHEST Physician

BOSTON — Social adversity is associated with worse survival among patients with pulmonary hypertension (PH), according to a new retrospective study of a New York City population. Among HIV+ patients with heart failure, PH was associated with about a threefold increase in all-cause mortality, but that risk increased to about sevenfold when social adversity, identified by a licensed social worker, was also present.

A sub-analysis of both HIV+ and HIV– patients showed worse mortality outcomes with social adversity in both groups.

“Almost the majority of patients that we treat have either some social adversity or no insurance or are undocumented, so as a group of residents, we decided to study the impact of these factors on their health and the care that can be provided. We started using the two cohorts and now we keep it going with every new resident,” said Luca Biavati, MD, who presented the study at the CHEST Annual Meeting.

“The presence of any form of socioeconomic disadvantage is negatively impacting care and for a large part of the population, there are some factors that could probably be addressed by either an institutional or hospital policy,” said Dr. Biavati, who is an internal medicine resident at Jacobi Medical Center, New York.

Other factors are more difficult to address, such as lack of education. “[Some patients] don’t understand the gravity of their issue and medical condition until it’s too late, and then they’re not fit enough for the treatment, or just because of the social situation, they cannot qualify for advanced therapies,” said Dr. Biavati.

The researchers established two cohorts: One consisting of patients with HIV and heart failure who may or may not have had PH and one comprising patients with PH with or without HIV and heart failure. In the HIV/heart failure group, PH without social adversity was associated with a nearly threefold increase in all-cause mortality (hazard ratio [HR], 2.83; P = .004), whereas PH with social adversity was linked to a more than sevenfold increase in all-cause mortality (HR, 7.14; P < .001). Social adversity without PA was associated with a more than fourfold increase (HR, 4.47; P < .001).

Within the PH cohort, social adversity was associated with lower survival (P < .001). When the researchers broke down the results by types of social adversity, they found statistically significant relationships between greater mortality risk and economic instability within the HIV+ population (HR, 2.59; P = .040), transportation issues within the HIV– population (HR, 12.8; P < .001), and lack of social or family support within both the HIV– (HR, 5.49; P < .001) and the HIV+ population (HR, 2.03; P = .028). 

The research has prompted interventions, which are now being studied at the institution, according to Dr. Biavati. “We have a policy of giving medications in bags when we discharge a patient with a social adversity. We literally go to the pharmacy, bring up the bag of medication, and we [put it] in their hands before they leave the hospital. They get a 1- or 3-month supply, depending on the medication, and then we usually discharge them with a clinical appointment already scheduled with either a pulmonary or primary care provider, and we usually call them before every appointment to confirm that they’re coming. That increases the chances of some success, but there’s still a very long way to go,” said Dr. Biavati.

Dr. Biavati was blinded to the results of the intervention, so he could not report on whether it was working. “But I can tell you that I’ve had busier clinics, so hopefully that means that they’re showing up more,” he said.

The problem is complex, according to Sandeep Jain, MD, who moderated the session. “Social adversity means lack of education. Lack of education means lack of compliance. Lack of compliance means what can you do if people are not taking medications? So it’s all matched together. It’s all lack of education and lack of money, lack of family support. And these drugs they have to take every single day. It’s not that easy. It’s very easy for us to say I had antiretroviral treatment for 6 months. It is almost impossible to continue regular treatment for that long [for a patient with social adversity]. You can’t blame them if they aren’t taking treatments. It’s very difficult for them,” said Dr. Jain.

That underscores the need for interventions that can address the needs of patients with social adversity. “We have to [practice] medicine considering the social situation of the patient and not just the medicine that we study in books. That’s kind of what we are faced with every day. We have therapies, and then life happens. It’s much harder to care for those patients,” said Dr. Biavati.

Dr. Biavati and Dr. Jain reported no relevant financial relationships.
 

A version of this article first appeared on Medscape.com.

BOSTON — Social adversity is associated with worse survival among patients with pulmonary hypertension (PH), according to a new retrospective study of a New York City population. Among HIV+ patients with heart failure, PH was associated with about a threefold increase in all-cause mortality, but that risk increased to about sevenfold when social adversity, identified by a licensed social worker, was also present.

A sub-analysis of both HIV+ and HIV– patients showed worse mortality outcomes with social adversity in both groups.

“Almost the majority of patients that we treat have either some social adversity or no insurance or are undocumented, so as a group of residents, we decided to study the impact of these factors on their health and the care that can be provided. We started using the two cohorts and now we keep it going with every new resident,” said Luca Biavati, MD, who presented the study at the CHEST Annual Meeting.

“The presence of any form of socioeconomic disadvantage is negatively impacting care and for a large part of the population, there are some factors that could probably be addressed by either an institutional or hospital policy,” said Dr. Biavati, who is an internal medicine resident at Jacobi Medical Center, New York.

Other factors are more difficult to address, such as lack of education. “[Some patients] don’t understand the gravity of their issue and medical condition until it’s too late, and then they’re not fit enough for the treatment, or just because of the social situation, they cannot qualify for advanced therapies,” said Dr. Biavati.

The researchers established two cohorts: One consisting of patients with HIV and heart failure who may or may not have had PH and one comprising patients with PH with or without HIV and heart failure. In the HIV/heart failure group, PH without social adversity was associated with a nearly threefold increase in all-cause mortality (hazard ratio [HR], 2.83; P = .004), whereas PH with social adversity was linked to a more than sevenfold increase in all-cause mortality (HR, 7.14; P < .001). Social adversity without PA was associated with a more than fourfold increase (HR, 4.47; P < .001).

Within the PH cohort, social adversity was associated with lower survival (P < .001). When the researchers broke down the results by types of social adversity, they found statistically significant relationships between greater mortality risk and economic instability within the HIV+ population (HR, 2.59; P = .040), transportation issues within the HIV– population (HR, 12.8; P < .001), and lack of social or family support within both the HIV– (HR, 5.49; P < .001) and the HIV+ population (HR, 2.03; P = .028). 

The research has prompted interventions, which are now being studied at the institution, according to Dr. Biavati. “We have a policy of giving medications in bags when we discharge a patient with a social adversity. We literally go to the pharmacy, bring up the bag of medication, and we [put it] in their hands before they leave the hospital. They get a 1- or 3-month supply, depending on the medication, and then we usually discharge them with a clinical appointment already scheduled with either a pulmonary or primary care provider, and we usually call them before every appointment to confirm that they’re coming. That increases the chances of some success, but there’s still a very long way to go,” said Dr. Biavati.

Dr. Biavati was blinded to the results of the intervention, so he could not report on whether it was working. “But I can tell you that I’ve had busier clinics, so hopefully that means that they’re showing up more,” he said.

The problem is complex, according to Sandeep Jain, MD, who moderated the session. “Social adversity means lack of education. Lack of education means lack of compliance. Lack of compliance means what can you do if people are not taking medications? So it’s all matched together. It’s all lack of education and lack of money, lack of family support. And these drugs they have to take every single day. It’s not that easy. It’s very easy for us to say I had antiretroviral treatment for 6 months. It is almost impossible to continue regular treatment for that long [for a patient with social adversity]. You can’t blame them if they aren’t taking treatments. It’s very difficult for them,” said Dr. Jain.

That underscores the need for interventions that can address the needs of patients with social adversity. “We have to [practice] medicine considering the social situation of the patient and not just the medicine that we study in books. That’s kind of what we are faced with every day. We have therapies, and then life happens. It’s much harder to care for those patients,” said Dr. Biavati.

Dr. Biavati and Dr. Jain reported no relevant financial relationships.
 

A version of this article first appeared on Medscape.com.

BOSTON — Social adversity is associated with worse survival among patients with pulmonary hypertension (PH), according to a new retrospective study of a New York City population. Among HIV+ patients with heart failure, PH was associated with about a threefold increase in all-cause mortality, but that risk increased to about sevenfold when social adversity, identified by a licensed social worker, was also present.

A sub-analysis of both HIV+ and HIV– patients showed worse mortality outcomes with social adversity in both groups.

“Almost the majority of patients that we treat have either some social adversity or no insurance or are undocumented, so as a group of residents, we decided to study the impact of these factors on their health and the care that can be provided. We started using the two cohorts and now we keep it going with every new resident,” said Luca Biavati, MD, who presented the study at the CHEST Annual Meeting.

“The presence of any form of socioeconomic disadvantage is negatively impacting care and for a large part of the population, there are some factors that could probably be addressed by either an institutional or hospital policy,” said Dr. Biavati, who is an internal medicine resident at Jacobi Medical Center, New York.

Other factors are more difficult to address, such as lack of education. “[Some patients] don’t understand the gravity of their issue and medical condition until it’s too late, and then they’re not fit enough for the treatment, or just because of the social situation, they cannot qualify for advanced therapies,” said Dr. Biavati.

The researchers established two cohorts: One consisting of patients with HIV and heart failure who may or may not have had PH and one comprising patients with PH with or without HIV and heart failure. In the HIV/heart failure group, PH without social adversity was associated with a nearly threefold increase in all-cause mortality (hazard ratio [HR], 2.83; P = .004), whereas PH with social adversity was linked to a more than sevenfold increase in all-cause mortality (HR, 7.14; P < .001). Social adversity without PA was associated with a more than fourfold increase (HR, 4.47; P < .001).

Within the PH cohort, social adversity was associated with lower survival (P < .001). When the researchers broke down the results by types of social adversity, they found statistically significant relationships between greater mortality risk and economic instability within the HIV+ population (HR, 2.59; P = .040), transportation issues within the HIV– population (HR, 12.8; P < .001), and lack of social or family support within both the HIV– (HR, 5.49; P < .001) and the HIV+ population (HR, 2.03; P = .028). 

The research has prompted interventions, which are now being studied at the institution, according to Dr. Biavati. “We have a policy of giving medications in bags when we discharge a patient with a social adversity. We literally go to the pharmacy, bring up the bag of medication, and we [put it] in their hands before they leave the hospital. They get a 1- or 3-month supply, depending on the medication, and then we usually discharge them with a clinical appointment already scheduled with either a pulmonary or primary care provider, and we usually call them before every appointment to confirm that they’re coming. That increases the chances of some success, but there’s still a very long way to go,” said Dr. Biavati.

Dr. Biavati was blinded to the results of the intervention, so he could not report on whether it was working. “But I can tell you that I’ve had busier clinics, so hopefully that means that they’re showing up more,” he said.

The problem is complex, according to Sandeep Jain, MD, who moderated the session. “Social adversity means lack of education. Lack of education means lack of compliance. Lack of compliance means what can you do if people are not taking medications? So it’s all matched together. It’s all lack of education and lack of money, lack of family support. And these drugs they have to take every single day. It’s not that easy. It’s very easy for us to say I had antiretroviral treatment for 6 months. It is almost impossible to continue regular treatment for that long [for a patient with social adversity]. You can’t blame them if they aren’t taking treatments. It’s very difficult for them,” said Dr. Jain.

That underscores the need for interventions that can address the needs of patients with social adversity. “We have to [practice] medicine considering the social situation of the patient and not just the medicine that we study in books. That’s kind of what we are faced with every day. We have therapies, and then life happens. It’s much harder to care for those patients,” said Dr. Biavati.

Dr. Biavati and Dr. Jain reported no relevant financial relationships.
 

A version of this article first appeared on Medscape.com.

LOS ANGELES — Metformin prescribed within a week of SARS-CoV-2 infection was associated with a 53% reduction in long COVID or death over 6 months in people without diabetes or prediabetes, according to data presented at the Infectious Disease Week (IDWeek) 2024 Annual Meeting.

Long COVID was determined by using the diagnostic code U09.9 or a computable phenotype based on symptoms and conditions. Most participants in this study were infected with the Omicron variant.

Researchers, led by Carolyn Bramante, MD, MPH, an internist, pediatrician, and obesity medicine specialist at the University of Minnesota Medical School in Minneapolis, simulated a randomized controlled trial of metformin vs control using the National COVID Cohort Collaborative (N3C) Electronic Health Record Database.

The intervention was a prescription for metformin within 6 days of SARS-CoV-2 infection. Those in the control group, which was designed to mimic placebo, had a prescription for fluvoxamine, fluticasone, ivermectin, or montelukast (all drugs that have been used off-label for COVID but have shown no effect on acute COVID outcomes in clinical trials). Exclusions included anyone with a previous metformin prescription or a comparator prescription; any indication for chronic metformin use; or a contraindication for metformin.
 

Why Study Metformin for Long COVID?

Dr. Bramante led a previous randomized controlled trial, COVID-OUT, with 1323 people that indicated metformin showed possible benefit for preventing the more severe components of COVID-19. She also led a 2020 review, in which she examined electronic health records from adults with type 2 diabetes or obesity. The researchers found that women taking metformin before they developed COVID-19 were significantly less likely to die after being hospitalized — although men didn’t see the same protective effect. Another randomized trial of 20 people found that 60% of those taking metformin vs 100% of those given a placebo had detectable SARS-CoV-2 viral load by day 4.

Other trials have highlighted the anti-inflammatory and antiviral properties of metformin. The existing evidence coupled with metformin’s well-established safety profile, led Dr. Bramante’s team to conduct the current simulated trial in people without diabetes or prediabetes. Dr. Bramante noted that metformin’s only US Food and Drug Administration–approved indication is for diabetes.

The current study featured a similar racial/ethnic makeup in the metformin and control groups: 16% and 17% were Black and 16% and 13% were Hispanic, respectively. Within 6 months, 4.0% in the metformin group developed long COVID or died compared with 8.5% in the control group (Relative Risk [RR], 0.47; 95% CI, 0.25-0.89). For prescriptions made on days 0-1 relative to infection, the RR was 0.39 (95% CI, 0.12-1.24). When metformin was prescribed on days 0-14, the RR was 0.75 (95% CI, 0.52-1.08).

The reason it’s important to have an active comparator is to control for things that can’t be measured, such as engagement in healthcare and the placebo effect, Dr. Bramante said.

Emily Erbelding, MD, MPH, director of the Division of Microbiology and Infectious Diseases at the National Institute of Allergy and Infectious Diseases, who was not part of the study, noted the potential implications of the findings.
 

Proven Safety and Low Cost of Metformin 

“We don’t have therapies for long COVID, and we don’t know how to prevent it in people who have SARS-CoV-2 infections,” Dr. Erbelding noted. “This analysis points to metformin, a drug that millions of people have taken safely for their diabetes or their borderline diabetes. It’s licensed, it’s out there, and it’s inexpensive. The fact that we have data that point to this potentially being a therapy is important. I think that’s the power of this.”

Dr. Erbelding said a strength of the study is the size of the N3C Electronic Health Record Database (with data on nearly 9 million COVID cases) the researchers used to simulate the randomized controlled trial.

“(These results) gives us a reason to think about doing a large randomized controlled study with metformin,” she said. However, there are some limitations, she noted.

“The definition of long COVID may not have been applied exactly the same way across all the patients and you don’t know what led the prescribers to prescribe metformin. There might have been confounders that couldn’t be controlled for or weren’t evident in the way they approached the data.”

This study has “relatively rigorous methodology for an observational study,” Dr. Erbelding said. “It’s novel to try to simulate a randomized controlled trial through a large, observational, electronic record–based cohort. Maybe we should be doing more of this because these bioinformatic systems exist now. And we need to get all the public health use out of them that we can.” 

“The fact that they may be unlocking something new here that needs follow-up in a truly randomized controlled trial is important as well because there are a lot of people out there suffering from long COVID.”

Bramante and Erbelding disclosed no relevant financial relationships. This research was supported in part by the intramural/extramural research program of the National Center for Advancing Translational Science, National Institutes of Health.
 

A version of this article appeared on Medscape.com.

LOS ANGELES — Metformin prescribed within a week of SARS-CoV-2 infection was associated with a 53% reduction in long COVID or death over 6 months in people without diabetes or prediabetes, according to data presented at the Infectious Disease Week (IDWeek) 2024 Annual Meeting.

Long COVID was determined by using the diagnostic code U09.9 or a computable phenotype based on symptoms and conditions. Most participants in this study were infected with the Omicron variant.

Researchers, led by Carolyn Bramante, MD, MPH, an internist, pediatrician, and obesity medicine specialist at the University of Minnesota Medical School in Minneapolis, simulated a randomized controlled trial of metformin vs control using the National COVID Cohort Collaborative (N3C) Electronic Health Record Database.

The intervention was a prescription for metformin within 6 days of SARS-CoV-2 infection. Those in the control group, which was designed to mimic placebo, had a prescription for fluvoxamine, fluticasone, ivermectin, or montelukast (all drugs that have been used off-label for COVID but have shown no effect on acute COVID outcomes in clinical trials). Exclusions included anyone with a previous metformin prescription or a comparator prescription; any indication for chronic metformin use; or a contraindication for metformin.
 

Why Study Metformin for Long COVID?

Dr. Bramante led a previous randomized controlled trial, COVID-OUT, with 1323 people that indicated metformin showed possible benefit for preventing the more severe components of COVID-19. She also led a 2020 review, in which she examined electronic health records from adults with type 2 diabetes or obesity. The researchers found that women taking metformin before they developed COVID-19 were significantly less likely to die after being hospitalized — although men didn’t see the same protective effect. Another randomized trial of 20 people found that 60% of those taking metformin vs 100% of those given a placebo had detectable SARS-CoV-2 viral load by day 4.

Other trials have highlighted the anti-inflammatory and antiviral properties of metformin. The existing evidence coupled with metformin’s well-established safety profile, led Dr. Bramante’s team to conduct the current simulated trial in people without diabetes or prediabetes. Dr. Bramante noted that metformin’s only US Food and Drug Administration–approved indication is for diabetes.

The current study featured a similar racial/ethnic makeup in the metformin and control groups: 16% and 17% were Black and 16% and 13% were Hispanic, respectively. Within 6 months, 4.0% in the metformin group developed long COVID or died compared with 8.5% in the control group (Relative Risk [RR], 0.47; 95% CI, 0.25-0.89). For prescriptions made on days 0-1 relative to infection, the RR was 0.39 (95% CI, 0.12-1.24). When metformin was prescribed on days 0-14, the RR was 0.75 (95% CI, 0.52-1.08).

The reason it’s important to have an active comparator is to control for things that can’t be measured, such as engagement in healthcare and the placebo effect, Dr. Bramante said.

Emily Erbelding, MD, MPH, director of the Division of Microbiology and Infectious Diseases at the National Institute of Allergy and Infectious Diseases, who was not part of the study, noted the potential implications of the findings.
 

Proven Safety and Low Cost of Metformin 

“We don’t have therapies for long COVID, and we don’t know how to prevent it in people who have SARS-CoV-2 infections,” Dr. Erbelding noted. “This analysis points to metformin, a drug that millions of people have taken safely for their diabetes or their borderline diabetes. It’s licensed, it’s out there, and it’s inexpensive. The fact that we have data that point to this potentially being a therapy is important. I think that’s the power of this.”

Dr. Erbelding said a strength of the study is the size of the N3C Electronic Health Record Database (with data on nearly 9 million COVID cases) the researchers used to simulate the randomized controlled trial.

“(These results) gives us a reason to think about doing a large randomized controlled study with metformin,” she said. However, there are some limitations, she noted.

“The definition of long COVID may not have been applied exactly the same way across all the patients and you don’t know what led the prescribers to prescribe metformin. There might have been confounders that couldn’t be controlled for or weren’t evident in the way they approached the data.”

This study has “relatively rigorous methodology for an observational study,” Dr. Erbelding said. “It’s novel to try to simulate a randomized controlled trial through a large, observational, electronic record–based cohort. Maybe we should be doing more of this because these bioinformatic systems exist now. And we need to get all the public health use out of them that we can.” 

“The fact that they may be unlocking something new here that needs follow-up in a truly randomized controlled trial is important as well because there are a lot of people out there suffering from long COVID.”

Bramante and Erbelding disclosed no relevant financial relationships. This research was supported in part by the intramural/extramural research program of the National Center for Advancing Translational Science, National Institutes of Health.
 

A version of this article appeared on Medscape.com.

LOS ANGELES — Metformin prescribed within a week of SARS-CoV-2 infection was associated with a 53% reduction in long COVID or death over 6 months in people without diabetes or prediabetes, according to data presented at the Infectious Disease Week (IDWeek) 2024 Annual Meeting.

Long COVID was determined by using the diagnostic code U09.9 or a computable phenotype based on symptoms and conditions. Most participants in this study were infected with the Omicron variant.

Researchers, led by Carolyn Bramante, MD, MPH, an internist, pediatrician, and obesity medicine specialist at the University of Minnesota Medical School in Minneapolis, simulated a randomized controlled trial of metformin vs control using the National COVID Cohort Collaborative (N3C) Electronic Health Record Database.

The intervention was a prescription for metformin within 6 days of SARS-CoV-2 infection. Those in the control group, which was designed to mimic placebo, had a prescription for fluvoxamine, fluticasone, ivermectin, or montelukast (all drugs that have been used off-label for COVID but have shown no effect on acute COVID outcomes in clinical trials). Exclusions included anyone with a previous metformin prescription or a comparator prescription; any indication for chronic metformin use; or a contraindication for metformin.
 

Why Study Metformin for Long COVID?

Dr. Bramante led a previous randomized controlled trial, COVID-OUT, with 1323 people that indicated metformin showed possible benefit for preventing the more severe components of COVID-19. She also led a 2020 review, in which she examined electronic health records from adults with type 2 diabetes or obesity. The researchers found that women taking metformin before they developed COVID-19 were significantly less likely to die after being hospitalized — although men didn’t see the same protective effect. Another randomized trial of 20 people found that 60% of those taking metformin vs 100% of those given a placebo had detectable SARS-CoV-2 viral load by day 4.

Other trials have highlighted the anti-inflammatory and antiviral properties of metformin. The existing evidence coupled with metformin’s well-established safety profile, led Dr. Bramante’s team to conduct the current simulated trial in people without diabetes or prediabetes. Dr. Bramante noted that metformin’s only US Food and Drug Administration–approved indication is for diabetes.

The current study featured a similar racial/ethnic makeup in the metformin and control groups: 16% and 17% were Black and 16% and 13% were Hispanic, respectively. Within 6 months, 4.0% in the metformin group developed long COVID or died compared with 8.5% in the control group (Relative Risk [RR], 0.47; 95% CI, 0.25-0.89). For prescriptions made on days 0-1 relative to infection, the RR was 0.39 (95% CI, 0.12-1.24). When metformin was prescribed on days 0-14, the RR was 0.75 (95% CI, 0.52-1.08).

The reason it’s important to have an active comparator is to control for things that can’t be measured, such as engagement in healthcare and the placebo effect, Dr. Bramante said.

Emily Erbelding, MD, MPH, director of the Division of Microbiology and Infectious Diseases at the National Institute of Allergy and Infectious Diseases, who was not part of the study, noted the potential implications of the findings.
 

Proven Safety and Low Cost of Metformin 

“We don’t have therapies for long COVID, and we don’t know how to prevent it in people who have SARS-CoV-2 infections,” Dr. Erbelding noted. “This analysis points to metformin, a drug that millions of people have taken safely for their diabetes or their borderline diabetes. It’s licensed, it’s out there, and it’s inexpensive. The fact that we have data that point to this potentially being a therapy is important. I think that’s the power of this.”

Dr. Erbelding said a strength of the study is the size of the N3C Electronic Health Record Database (with data on nearly 9 million COVID cases) the researchers used to simulate the randomized controlled trial.

“(These results) gives us a reason to think about doing a large randomized controlled study with metformin,” she said. However, there are some limitations, she noted.

“The definition of long COVID may not have been applied exactly the same way across all the patients and you don’t know what led the prescribers to prescribe metformin. There might have been confounders that couldn’t be controlled for or weren’t evident in the way they approached the data.”

This study has “relatively rigorous methodology for an observational study,” Dr. Erbelding said. “It’s novel to try to simulate a randomized controlled trial through a large, observational, electronic record–based cohort. Maybe we should be doing more of this because these bioinformatic systems exist now. And we need to get all the public health use out of them that we can.” 

“The fact that they may be unlocking something new here that needs follow-up in a truly randomized controlled trial is important as well because there are a lot of people out there suffering from long COVID.”

Bramante and Erbelding disclosed no relevant financial relationships. This research was supported in part by the intramural/extramural research program of the National Center for Advancing Translational Science, National Institutes of Health.
 

A version of this article appeared on Medscape.com.

A “digital twin” model successfully predicted adverse outcomes in intensive care unit (ICU) patients treated for sepsis. The research used an adaptive approach, updating time-sensitive values such as blood pressure and vitals every 15 minutes. The approach also took into account treatment decisions and has potential as a decision-making and educational tool.

The digital twin could reduce the risk for some interventions, according to Amos Lal, MD, who presented the study at the CHEST Annual Meeting. That’s because the model can predict the outcome. “You don’t actually have to make an intervention to the patient, which might be risky. By doing that, you can actually prevent a lot of harm,” said Dr. Lal, assistant professor of medicine at Mayo Clinic in Rochester, Minnesota.

The researchers used a one-dimensional convolutional neural network (CNN), similar to two-dimensional CNNs that are used to classify images, substituting the color channels used in imaging with 38 time-dependent variables. They applied it to predicting outcomes in the ICU, focusing on data generated within the first 24 hours of admission. The team made the model dynamic by adding time-sensitive data like vitals, laboratory values, and interventions every 15 minutes. That contrasts with existing models that are usually static, relying on values at admission or at 24 hours, for example. It also takes into account time-insensitive data like age, gender, and comorbidities. “Combining these two and coming up with the prediction model in real time can give you a more informed decision about how these patients are going to perform over a period of 2 weeks or 4 weeks of their stay within the ICU. And of course, as we get more and more data within the first 24 hours, the performance of the model improves as well,” said Dr. Lal.

The researchers tested the model by creating a virtual model of the patient and then performing an intervention on the patient and a simulated intervention on the virtual patient. “Then we advance the clock and the patient either improved or deteriorated, and we compared how the digital twin performed, whether the changes were concordant or discordant [between the virtual and real-world patients],” said Dr. Lal.

The model was designed to predict which patients with sepsis would be at greater risk for death or ICU stays longer than 14 days. It was created using data from 28,617 patients with critical care sepsis at a single hospital who were treated between 2011 and 2018, with 70% used as a training set, 20% as a test set, and 10% as a validation set. The researchers conducted an external validation using MIMIC-IV data on 30,903 patients from the Beth Israel Deaconess Medical Center in Boston. The model included 31 time-independent variables and 38 time-dependent variables that were collected every 15 minutes at the Mayo Clinic and every 60 minutes at Beth Israel Deaconess. Surgical patients represented 24% of the Mayo dataset and 58% of the MIMIC-IV dataset, but otherwise the two groups were demographically similar.

At 24 hours, the area under the receiver operating characteristic curve for predicting 14-day mortality was −0.82 in the Mayo validation cohort and −0.78 in the MIMIC validation cohort. The model improved in accuracy over time as more data were accumulated.

The session’s co-moderators, Sandeep Jain, MD, and Casey Cable, MD, praised the work. Dr. Cable, associate professor of pulmonary care medicine at VCU Health, Richmond, Virginia, noted that the model used both surgical patients and medical patients with sepsis, and the two groups can present quite differently. Another variable was the COVID pandemic, where some patients presented at the hospital when they were quite sick. “I’m curious how different starting points would play into it,” she said.

She called for institutions to develop such models on their own rather than relying on companies that might develop software solutions. “I think that this needs to be clinician-led, from the ground up,” said Dr. Cable.

Dr. Jain, an associate professor of pulmonary care medicine at Broward Health, suggested that such models might need to be individualized for each institution, but “my fear is it could become too expensive, so I think a group like CHEST could come together and [create] an open source system to have their researchers jumpstart the research on this,” he said.

Dr. Lal, Dr. Jain, and Dr. Cable reported no relevant financial relationships.

A version of this article appeared on Medscape.com.

A “digital twin” model successfully predicted adverse outcomes in intensive care unit (ICU) patients treated for sepsis. The research used an adaptive approach, updating time-sensitive values such as blood pressure and vitals every 15 minutes. The approach also took into account treatment decisions and has potential as a decision-making and educational tool.

The digital twin could reduce the risk for some interventions, according to Amos Lal, MD, who presented the study at the CHEST Annual Meeting. That’s because the model can predict the outcome. “You don’t actually have to make an intervention to the patient, which might be risky. By doing that, you can actually prevent a lot of harm,” said Dr. Lal, assistant professor of medicine at Mayo Clinic in Rochester, Minnesota.

The researchers used a one-dimensional convolutional neural network (CNN), similar to two-dimensional CNNs that are used to classify images, substituting the color channels used in imaging with 38 time-dependent variables. They applied it to predicting outcomes in the ICU, focusing on data generated within the first 24 hours of admission. The team made the model dynamic by adding time-sensitive data like vitals, laboratory values, and interventions every 15 minutes. That contrasts with existing models that are usually static, relying on values at admission or at 24 hours, for example. It also takes into account time-insensitive data like age, gender, and comorbidities. “Combining these two and coming up with the prediction model in real time can give you a more informed decision about how these patients are going to perform over a period of 2 weeks or 4 weeks of their stay within the ICU. And of course, as we get more and more data within the first 24 hours, the performance of the model improves as well,” said Dr. Lal.

The researchers tested the model by creating a virtual model of the patient and then performing an intervention on the patient and a simulated intervention on the virtual patient. “Then we advance the clock and the patient either improved or deteriorated, and we compared how the digital twin performed, whether the changes were concordant or discordant [between the virtual and real-world patients],” said Dr. Lal.

The model was designed to predict which patients with sepsis would be at greater risk for death or ICU stays longer than 14 days. It was created using data from 28,617 patients with critical care sepsis at a single hospital who were treated between 2011 and 2018, with 70% used as a training set, 20% as a test set, and 10% as a validation set. The researchers conducted an external validation using MIMIC-IV data on 30,903 patients from the Beth Israel Deaconess Medical Center in Boston. The model included 31 time-independent variables and 38 time-dependent variables that were collected every 15 minutes at the Mayo Clinic and every 60 minutes at Beth Israel Deaconess. Surgical patients represented 24% of the Mayo dataset and 58% of the MIMIC-IV dataset, but otherwise the two groups were demographically similar.

At 24 hours, the area under the receiver operating characteristic curve for predicting 14-day mortality was −0.82 in the Mayo validation cohort and −0.78 in the MIMIC validation cohort. The model improved in accuracy over time as more data were accumulated.

The session’s co-moderators, Sandeep Jain, MD, and Casey Cable, MD, praised the work. Dr. Cable, associate professor of pulmonary care medicine at VCU Health, Richmond, Virginia, noted that the model used both surgical patients and medical patients with sepsis, and the two groups can present quite differently. Another variable was the COVID pandemic, where some patients presented at the hospital when they were quite sick. “I’m curious how different starting points would play into it,” she said.

She called for institutions to develop such models on their own rather than relying on companies that might develop software solutions. “I think that this needs to be clinician-led, from the ground up,” said Dr. Cable.

Dr. Jain, an associate professor of pulmonary care medicine at Broward Health, suggested that such models might need to be individualized for each institution, but “my fear is it could become too expensive, so I think a group like CHEST could come together and [create] an open source system to have their researchers jumpstart the research on this,” he said.

Dr. Lal, Dr. Jain, and Dr. Cable reported no relevant financial relationships.

A version of this article appeared on Medscape.com.

A “digital twin” model successfully predicted adverse outcomes in intensive care unit (ICU) patients treated for sepsis. The research used an adaptive approach, updating time-sensitive values such as blood pressure and vitals every 15 minutes. The approach also took into account treatment decisions and has potential as a decision-making and educational tool.

The digital twin could reduce the risk for some interventions, according to Amos Lal, MD, who presented the study at the CHEST Annual Meeting. That’s because the model can predict the outcome. “You don’t actually have to make an intervention to the patient, which might be risky. By doing that, you can actually prevent a lot of harm,” said Dr. Lal, assistant professor of medicine at Mayo Clinic in Rochester, Minnesota.

The researchers used a one-dimensional convolutional neural network (CNN), similar to two-dimensional CNNs that are used to classify images, substituting the color channels used in imaging with 38 time-dependent variables. They applied it to predicting outcomes in the ICU, focusing on data generated within the first 24 hours of admission. The team made the model dynamic by adding time-sensitive data like vitals, laboratory values, and interventions every 15 minutes. That contrasts with existing models that are usually static, relying on values at admission or at 24 hours, for example. It also takes into account time-insensitive data like age, gender, and comorbidities. “Combining these two and coming up with the prediction model in real time can give you a more informed decision about how these patients are going to perform over a period of 2 weeks or 4 weeks of their stay within the ICU. And of course, as we get more and more data within the first 24 hours, the performance of the model improves as well,” said Dr. Lal.

The researchers tested the model by creating a virtual model of the patient and then performing an intervention on the patient and a simulated intervention on the virtual patient. “Then we advance the clock and the patient either improved or deteriorated, and we compared how the digital twin performed, whether the changes were concordant or discordant [between the virtual and real-world patients],” said Dr. Lal.

The model was designed to predict which patients with sepsis would be at greater risk for death or ICU stays longer than 14 days. It was created using data from 28,617 patients with critical care sepsis at a single hospital who were treated between 2011 and 2018, with 70% used as a training set, 20% as a test set, and 10% as a validation set. The researchers conducted an external validation using MIMIC-IV data on 30,903 patients from the Beth Israel Deaconess Medical Center in Boston. The model included 31 time-independent variables and 38 time-dependent variables that were collected every 15 minutes at the Mayo Clinic and every 60 minutes at Beth Israel Deaconess. Surgical patients represented 24% of the Mayo dataset and 58% of the MIMIC-IV dataset, but otherwise the two groups were demographically similar.

At 24 hours, the area under the receiver operating characteristic curve for predicting 14-day mortality was −0.82 in the Mayo validation cohort and −0.78 in the MIMIC validation cohort. The model improved in accuracy over time as more data were accumulated.

The session’s co-moderators, Sandeep Jain, MD, and Casey Cable, MD, praised the work. Dr. Cable, associate professor of pulmonary care medicine at VCU Health, Richmond, Virginia, noted that the model used both surgical patients and medical patients with sepsis, and the two groups can present quite differently. Another variable was the COVID pandemic, where some patients presented at the hospital when they were quite sick. “I’m curious how different starting points would play into it,” she said.

She called for institutions to develop such models on their own rather than relying on companies that might develop software solutions. “I think that this needs to be clinician-led, from the ground up,” said Dr. Cable.

Dr. Jain, an associate professor of pulmonary care medicine at Broward Health, suggested that such models might need to be individualized for each institution, but “my fear is it could become too expensive, so I think a group like CHEST could come together and [create] an open source system to have their researchers jumpstart the research on this,” he said.

Dr. Lal, Dr. Jain, and Dr. Cable reported no relevant financial relationships.

A version of this article appeared on Medscape.com.

BOSTON — Patients with COPD are at an increased risk for fatal pulmonary embolism (PE) and may require personalized, targeted thromboprophylaxis. Those are the conclusions of investigators who analyzed public health data and found that patients with COPD have a markedly increased risk for PE-related death, particularly among those aged 65-85 years.

The data suggest that “maybe we should start thinking about if we are admitting a patient with COPD in that specific age group, higher thromboprophylaxis for PE,” said Marwa Oudah, MD, a pulmonary hypertension fellow at the University of Pennsylvania, Philadelphia. She presented her group’s findings in a rapid-fire oral abstract session at the CHEST Annual Meeting.
 

Known Risk Factor

COPD is a known risk factor for PE. To estimate how the obstructive lung disease may contribute to PE-related deaths among patients of varying ages, Oudah and colleagues drew data on deaths due to an underlying cause of PE from 1999 to 2020 from the Centers for Disease Control and Prevention’s WONDER database.

They stratified the patients into two groups — those with or without COPD — whose data were included in the Multiple Causes of Death dataset, according to age groups ranging from 35 years to over 100 years. The investigators calculated proportional mortality ratios in the non-COPD group and applied these to the COPD-positive group among different age ranges to estimate the observed vs expected number of deaths.

A total of 10,434 persons who died from PE and had COPD listed among causes of death were identified. The sample was evenly divided by sex. The peak range of deaths was among those aged 75-84 years.

The authors saw an increase in PE-related mortality among patients with COPD aged 65-85 years (P < .001).

The ratios of observed-to-expected deaths among patients in this age range were “substantially greater than 1” said Oudah, with patients aged 75-79 years at highest risk for PE-related death, with an observed-to-expected ratio of 1.443.

In contrast, the rate of observed deaths among patients aged 85-89 years was similar to the expected rate, suggesting that the COPD-PE interaction may wane among older patients, she said.

Among patients aged 35-64 years, the risk for death from PE was not significantly higher for any of the 5-year age categories.

The investigators emphasized that “given the observed trend, individualized patient assessments are imperative to optimize preventable measures against PE in the aging COPD population.”
 

Confounding Comorbidities

In an interview, a pulmonary specialist who was not involved in the study commented that older persons with COPD tend to have multiple comorbidities that may contribute to the risk for PE.

“Older patients have so many comorbidities, and their risk for pulmonary embolism and thromboembolic disease is pretty high, so I’m not surprised that 75 to 79 years olds are having a higher mortality from PE, but it’s a little difficult to say whether that’s due to COPD,” said Krishna Sundar, MBBS, MD, FCCP, a pulmonary, sleep medicine, and critical care medicine specialist at St. John’s Medical Center in Jackson, Wyoming, who moderated the session.

The authors did not report a study funding source. Oudah and Sundar reported no relevant financial relationships.

A version of this article first appeared on Medscape.com.

BOSTON — Patients with COPD are at an increased risk for fatal pulmonary embolism (PE) and may require personalized, targeted thromboprophylaxis. Those are the conclusions of investigators who analyzed public health data and found that patients with COPD have a markedly increased risk for PE-related death, particularly among those aged 65-85 years.

The data suggest that “maybe we should start thinking about if we are admitting a patient with COPD in that specific age group, higher thromboprophylaxis for PE,” said Marwa Oudah, MD, a pulmonary hypertension fellow at the University of Pennsylvania, Philadelphia. She presented her group’s findings in a rapid-fire oral abstract session at the CHEST Annual Meeting.
 

Known Risk Factor

COPD is a known risk factor for PE. To estimate how the obstructive lung disease may contribute to PE-related deaths among patients of varying ages, Oudah and colleagues drew data on deaths due to an underlying cause of PE from 1999 to 2020 from the Centers for Disease Control and Prevention’s WONDER database.

They stratified the patients into two groups — those with or without COPD — whose data were included in the Multiple Causes of Death dataset, according to age groups ranging from 35 years to over 100 years. The investigators calculated proportional mortality ratios in the non-COPD group and applied these to the COPD-positive group among different age ranges to estimate the observed vs expected number of deaths.

A total of 10,434 persons who died from PE and had COPD listed among causes of death were identified. The sample was evenly divided by sex. The peak range of deaths was among those aged 75-84 years.

The authors saw an increase in PE-related mortality among patients with COPD aged 65-85 years (P < .001).

The ratios of observed-to-expected deaths among patients in this age range were “substantially greater than 1” said Oudah, with patients aged 75-79 years at highest risk for PE-related death, with an observed-to-expected ratio of 1.443.

In contrast, the rate of observed deaths among patients aged 85-89 years was similar to the expected rate, suggesting that the COPD-PE interaction may wane among older patients, she said.

Among patients aged 35-64 years, the risk for death from PE was not significantly higher for any of the 5-year age categories.

The investigators emphasized that “given the observed trend, individualized patient assessments are imperative to optimize preventable measures against PE in the aging COPD population.”
 

Confounding Comorbidities

In an interview, a pulmonary specialist who was not involved in the study commented that older persons with COPD tend to have multiple comorbidities that may contribute to the risk for PE.

“Older patients have so many comorbidities, and their risk for pulmonary embolism and thromboembolic disease is pretty high, so I’m not surprised that 75 to 79 years olds are having a higher mortality from PE, but it’s a little difficult to say whether that’s due to COPD,” said Krishna Sundar, MBBS, MD, FCCP, a pulmonary, sleep medicine, and critical care medicine specialist at St. John’s Medical Center in Jackson, Wyoming, who moderated the session.

The authors did not report a study funding source. Oudah and Sundar reported no relevant financial relationships.

A version of this article first appeared on Medscape.com.

BOSTON — Patients with COPD are at an increased risk for fatal pulmonary embolism (PE) and may require personalized, targeted thromboprophylaxis. Those are the conclusions of investigators who analyzed public health data and found that patients with COPD have a markedly increased risk for PE-related death, particularly among those aged 65-85 years.

The data suggest that “maybe we should start thinking about if we are admitting a patient with COPD in that specific age group, higher thromboprophylaxis for PE,” said Marwa Oudah, MD, a pulmonary hypertension fellow at the University of Pennsylvania, Philadelphia. She presented her group’s findings in a rapid-fire oral abstract session at the CHEST Annual Meeting.
 

Known Risk Factor

COPD is a known risk factor for PE. To estimate how the obstructive lung disease may contribute to PE-related deaths among patients of varying ages, Oudah and colleagues drew data on deaths due to an underlying cause of PE from 1999 to 2020 from the Centers for Disease Control and Prevention’s WONDER database.

They stratified the patients into two groups — those with or without COPD — whose data were included in the Multiple Causes of Death dataset, according to age groups ranging from 35 years to over 100 years. The investigators calculated proportional mortality ratios in the non-COPD group and applied these to the COPD-positive group among different age ranges to estimate the observed vs expected number of deaths.

A total of 10,434 persons who died from PE and had COPD listed among causes of death were identified. The sample was evenly divided by sex. The peak range of deaths was among those aged 75-84 years.

The authors saw an increase in PE-related mortality among patients with COPD aged 65-85 years (P < .001).

The ratios of observed-to-expected deaths among patients in this age range were “substantially greater than 1” said Oudah, with patients aged 75-79 years at highest risk for PE-related death, with an observed-to-expected ratio of 1.443.

In contrast, the rate of observed deaths among patients aged 85-89 years was similar to the expected rate, suggesting that the COPD-PE interaction may wane among older patients, she said.

Among patients aged 35-64 years, the risk for death from PE was not significantly higher for any of the 5-year age categories.

The investigators emphasized that “given the observed trend, individualized patient assessments are imperative to optimize preventable measures against PE in the aging COPD population.”
 

Confounding Comorbidities

In an interview, a pulmonary specialist who was not involved in the study commented that older persons with COPD tend to have multiple comorbidities that may contribute to the risk for PE.

“Older patients have so many comorbidities, and their risk for pulmonary embolism and thromboembolic disease is pretty high, so I’m not surprised that 75 to 79 years olds are having a higher mortality from PE, but it’s a little difficult to say whether that’s due to COPD,” said Krishna Sundar, MBBS, MD, FCCP, a pulmonary, sleep medicine, and critical care medicine specialist at St. John’s Medical Center in Jackson, Wyoming, who moderated the session.

The authors did not report a study funding source. Oudah and Sundar reported no relevant financial relationships.

A version of this article first appeared on Medscape.com.

BOSTON — Patients with COPD who have exacerbations requiring hospitalization should be monitored for cardiac arrhythmias, investigators said.

This recommendation is based on results of a study of medical records showing that among more than 20,000 hospitalizations for patients with COPD without concurrent heart failure (HF), 40% patients had at least 6 minutes of daily atrial fibrillation (AF) burden, and nearly half of these patients had at least an hour of daily AF burden; patients with COPD and concurrent HF had similar daily AF burdens, reported Trent Fischer, MD, MS, senior principal scientist at Medtronic in Minneapolis.

“We can conclude that AF burden increases in the weeks after a hospitalization for COPD if they don’t have a concurrent diagnosis of heart failure. Also, having concurrent heart failure increases the risk of atrial fibrillation and increases the atrial fibrillation burden around the time of COPD hospitalization,” he said in a rapid-fire oral abstract session at the CHEST Annual Meeting.

The findings indicated a need for increased vigilance for AF around the time of a serious COPD exacerbation and may explain at least some of the increased risks for stroke observed in patients who are hospitalized for COPD exacerbations, he said.
 

Retrospective Study

Dr. Fischer and colleagues conducted the study to characterize the AF burden among patients both with and without HF who were hospitalized for acute COPD exacerbation and to determine the temporal relationship between AF and hospitalization.

They drew data from 2007 through 2021 on patients with implantable cardioverter defibrillators, cardiac resynchronization therapy devices, pacemakers, and implantable cardiac monitors, using the Optum de-identified electronic health record dataset linked with Medtronic’s CareLink database to conduct a retrospective analysis.

They looked at admissions for COPD linked to available device diagnostic parameters between 30 days prior to and 60 days after admission for COPD.

They identified a total of 20,056 COPD hospitalizations for patients with concurrent HF and 3877 for those without HF.

Among patients with HF, 43% had a daily AF burden of at least 6 minutes, and 22% had at least 1 hour of irregular rhythms. Among patients without HF, 40% had at least 6 minutes of irregular rhythms daily, and 18% had at least 1 hour.

Among patients with HF, the daily average AF burden increased from a baseline of 158 min/d 30 days before an admission to 170 min/d at admission, returning to baseline by 20 days after hospitalization.

For patients without HF, the AF burden increased from 107 min/d at baseline to 113 min/d during hospitalization and returned to baseline by 20 days after hospitalization.
 

Confounding Factor?

In the Q&A, session moderator Krishna Sundar, MBBS, MD, FCCP, a pulmonary, sleep medicine, and critical care medicine specialist at St. John’s Medical Center in Jackson, Wyoming, said that when patients with HF get admitted for COPD exacerbations, their HF typically worsens and asked Dr. Fischer how he could tell the difference.

“I know there’s a lot of interaction between heart failure and COPD. They’re well-know comorbidities, and the exacerbation of one can bring on worsening of the other. At least with this database, we can’t really tease out any sort of differences,” Dr. Fischer replied.

“I think that a diagnosis of COPD exacerbation is pretty well laid out, but it’s sometimes difficult to separate worsening of heart failure in these patients, and often these patients get treated for both problems. It’s clear that it’s the heart failure patients who are having more atrial fibrillation episodes, which is not surprising, but the question is how much is the COPD exacerbation contributing to the atrial fibrillation?” said Dr. Sundar.

The study was supported by Medtronic. Dr. Fischer is employed by the company. Dr. Sundar reported no relevant financial relationships.



A version of this article appeared on Medscape.com.

BOSTON — Patients with COPD who have exacerbations requiring hospitalization should be monitored for cardiac arrhythmias, investigators said.

This recommendation is based on results of a study of medical records showing that among more than 20,000 hospitalizations for patients with COPD without concurrent heart failure (HF), 40% patients had at least 6 minutes of daily atrial fibrillation (AF) burden, and nearly half of these patients had at least an hour of daily AF burden; patients with COPD and concurrent HF had similar daily AF burdens, reported Trent Fischer, MD, MS, senior principal scientist at Medtronic in Minneapolis.

“We can conclude that AF burden increases in the weeks after a hospitalization for COPD if they don’t have a concurrent diagnosis of heart failure. Also, having concurrent heart failure increases the risk of atrial fibrillation and increases the atrial fibrillation burden around the time of COPD hospitalization,” he said in a rapid-fire oral abstract session at the CHEST Annual Meeting.

The findings indicated a need for increased vigilance for AF around the time of a serious COPD exacerbation and may explain at least some of the increased risks for stroke observed in patients who are hospitalized for COPD exacerbations, he said.
 

Retrospective Study

Dr. Fischer and colleagues conducted the study to characterize the AF burden among patients both with and without HF who were hospitalized for acute COPD exacerbation and to determine the temporal relationship between AF and hospitalization.

They drew data from 2007 through 2021 on patients with implantable cardioverter defibrillators, cardiac resynchronization therapy devices, pacemakers, and implantable cardiac monitors, using the Optum de-identified electronic health record dataset linked with Medtronic’s CareLink database to conduct a retrospective analysis.

They looked at admissions for COPD linked to available device diagnostic parameters between 30 days prior to and 60 days after admission for COPD.

They identified a total of 20,056 COPD hospitalizations for patients with concurrent HF and 3877 for those without HF.

Among patients with HF, 43% had a daily AF burden of at least 6 minutes, and 22% had at least 1 hour of irregular rhythms. Among patients without HF, 40% had at least 6 minutes of irregular rhythms daily, and 18% had at least 1 hour.

Among patients with HF, the daily average AF burden increased from a baseline of 158 min/d 30 days before an admission to 170 min/d at admission, returning to baseline by 20 days after hospitalization.

For patients without HF, the AF burden increased from 107 min/d at baseline to 113 min/d during hospitalization and returned to baseline by 20 days after hospitalization.
 

Confounding Factor?

In the Q&A, session moderator Krishna Sundar, MBBS, MD, FCCP, a pulmonary, sleep medicine, and critical care medicine specialist at St. John’s Medical Center in Jackson, Wyoming, said that when patients with HF get admitted for COPD exacerbations, their HF typically worsens and asked Dr. Fischer how he could tell the difference.

“I know there’s a lot of interaction between heart failure and COPD. They’re well-know comorbidities, and the exacerbation of one can bring on worsening of the other. At least with this database, we can’t really tease out any sort of differences,” Dr. Fischer replied.

“I think that a diagnosis of COPD exacerbation is pretty well laid out, but it’s sometimes difficult to separate worsening of heart failure in these patients, and often these patients get treated for both problems. It’s clear that it’s the heart failure patients who are having more atrial fibrillation episodes, which is not surprising, but the question is how much is the COPD exacerbation contributing to the atrial fibrillation?” said Dr. Sundar.

The study was supported by Medtronic. Dr. Fischer is employed by the company. Dr. Sundar reported no relevant financial relationships.



A version of this article appeared on Medscape.com.

BOSTON — Patients with COPD who have exacerbations requiring hospitalization should be monitored for cardiac arrhythmias, investigators said.

This recommendation is based on results of a study of medical records showing that among more than 20,000 hospitalizations for patients with COPD without concurrent heart failure (HF), 40% patients had at least 6 minutes of daily atrial fibrillation (AF) burden, and nearly half of these patients had at least an hour of daily AF burden; patients with COPD and concurrent HF had similar daily AF burdens, reported Trent Fischer, MD, MS, senior principal scientist at Medtronic in Minneapolis.

“We can conclude that AF burden increases in the weeks after a hospitalization for COPD if they don’t have a concurrent diagnosis of heart failure. Also, having concurrent heart failure increases the risk of atrial fibrillation and increases the atrial fibrillation burden around the time of COPD hospitalization,” he said in a rapid-fire oral abstract session at the CHEST Annual Meeting.

The findings indicated a need for increased vigilance for AF around the time of a serious COPD exacerbation and may explain at least some of the increased risks for stroke observed in patients who are hospitalized for COPD exacerbations, he said.
 

Retrospective Study

Dr. Fischer and colleagues conducted the study to characterize the AF burden among patients both with and without HF who were hospitalized for acute COPD exacerbation and to determine the temporal relationship between AF and hospitalization.

They drew data from 2007 through 2021 on patients with implantable cardioverter defibrillators, cardiac resynchronization therapy devices, pacemakers, and implantable cardiac monitors, using the Optum de-identified electronic health record dataset linked with Medtronic’s CareLink database to conduct a retrospective analysis.

They looked at admissions for COPD linked to available device diagnostic parameters between 30 days prior to and 60 days after admission for COPD.

They identified a total of 20,056 COPD hospitalizations for patients with concurrent HF and 3877 for those without HF.

Among patients with HF, 43% had a daily AF burden of at least 6 minutes, and 22% had at least 1 hour of irregular rhythms. Among patients without HF, 40% had at least 6 minutes of irregular rhythms daily, and 18% had at least 1 hour.

Among patients with HF, the daily average AF burden increased from a baseline of 158 min/d 30 days before an admission to 170 min/d at admission, returning to baseline by 20 days after hospitalization.

For patients without HF, the AF burden increased from 107 min/d at baseline to 113 min/d during hospitalization and returned to baseline by 20 days after hospitalization.
 

Confounding Factor?

In the Q&A, session moderator Krishna Sundar, MBBS, MD, FCCP, a pulmonary, sleep medicine, and critical care medicine specialist at St. John’s Medical Center in Jackson, Wyoming, said that when patients with HF get admitted for COPD exacerbations, their HF typically worsens and asked Dr. Fischer how he could tell the difference.

“I know there’s a lot of interaction between heart failure and COPD. They’re well-know comorbidities, and the exacerbation of one can bring on worsening of the other. At least with this database, we can’t really tease out any sort of differences,” Dr. Fischer replied.

“I think that a diagnosis of COPD exacerbation is pretty well laid out, but it’s sometimes difficult to separate worsening of heart failure in these patients, and often these patients get treated for both problems. It’s clear that it’s the heart failure patients who are having more atrial fibrillation episodes, which is not surprising, but the question is how much is the COPD exacerbation contributing to the atrial fibrillation?” said Dr. Sundar.

The study was supported by Medtronic. Dr. Fischer is employed by the company. Dr. Sundar reported no relevant financial relationships.



A version of this article appeared on Medscape.com.

Despite some recent progress in compensation equity, women in medicine continue to be paid significantly lower salaries than men.

According to the Female Compensation Report 2024 by Medscape, male doctors of any kind earned an average salary of about $400,000, whereas female doctors earned approximately $309,000 — a 29% gap.

The report analyzed survey data from 7000 practicing physicians who were recruited over a 4-month period starting in October 2023. The respondents comprised roughly 60% women representing over 29 specialties.

In the 2022 report, the pay gap between the genders was 32%. But some women in the field argued substantial headway is still needed.

“You can try and pick apart the data, but I’d say we’re not really making progress,” said Susan T. Hingle, MD, an internist in Illinois and president of the American Medical Women’s Association. “A decline by a couple of percentage points is not significantly addressing this pay gap that over a lifetime is huge, can be millions of dollars.”

The gender gap was narrower among female primary care physicians (PCPs) vs medical specialists. Female PCPs earned around $253,000 per year, whereas male PCPs earned about $295,000 per year. Hingle suggested that female PCPs may enjoy more pay equity because health systems have a harder time filling these positions.

On the other hand, the gap for specialists rose from 27% in 2022 to 31% in 2023. Differences in how aggressively women and men negotiate compensation packages may play a role, said Hingle.

“Taking negotiation out of the equation would be progress to me,” said Hingle.

Pay disparity did not appear to be the result of time spent on the job — female doctors reported an average of 49 work hours per week, whereas their male counterparts reported 50 work hours per week.

Meanwhile, the pay gap progressively worsened over time. Among doctors aged 28-34 years, men earned an average of $53,000 more than women. By ages 46-49, men earned an average of $157,000 more than women.

“I had to take my employer to court to get equal compensation, sad as it is to say,” said a hospitalist in North Carolina.

Nearly 60% of women surveyed felt they were not being paid fairly for their efforts, up from less than half reported in Medscape’s 2021 report. Hingle said that this figure may not only reflect sentiments about the compensation gap, but also less support on the job, including fewer physician assistants (PAs), nurses, and administrative staff.

“At my job, I do the work of multiple people,” said a survey respondent. “Junior resident, senior resident, social worker, nurse practitioner, PA — as well as try to be a teacher, researcher, [and] an excellent doctor and have the time to make patients feel as if they are not in a rush.”

Roughly 30% of women physicians said they would not choose to go into medicine again if given the chance compared with 26% of male physicians.

“Gender inequities in our profession have a direct impact,” said Shikha Jain, MD, an oncologist in Chicago and founder of the Women in Medicine nonprofit. “I think women in general don’t feel valued in the care they’re providing.” 

Jain cited bullying, harassment, and fewer opportunities for leadership and recognition as factors beyond pay that affect female physicians’ feelings of being valued.

A version of this article first appeared on Medscape.com.

Despite some recent progress in compensation equity, women in medicine continue to be paid significantly lower salaries than men.

According to the Female Compensation Report 2024 by Medscape, male doctors of any kind earned an average salary of about $400,000, whereas female doctors earned approximately $309,000 — a 29% gap.

The report analyzed survey data from 7000 practicing physicians who were recruited over a 4-month period starting in October 2023. The respondents comprised roughly 60% women representing over 29 specialties.

In the 2022 report, the pay gap between the genders was 32%. But some women in the field argued substantial headway is still needed.

“You can try and pick apart the data, but I’d say we’re not really making progress,” said Susan T. Hingle, MD, an internist in Illinois and president of the American Medical Women’s Association. “A decline by a couple of percentage points is not significantly addressing this pay gap that over a lifetime is huge, can be millions of dollars.”

The gender gap was narrower among female primary care physicians (PCPs) vs medical specialists. Female PCPs earned around $253,000 per year, whereas male PCPs earned about $295,000 per year. Hingle suggested that female PCPs may enjoy more pay equity because health systems have a harder time filling these positions.

On the other hand, the gap for specialists rose from 27% in 2022 to 31% in 2023. Differences in how aggressively women and men negotiate compensation packages may play a role, said Hingle.

“Taking negotiation out of the equation would be progress to me,” said Hingle.

Pay disparity did not appear to be the result of time spent on the job — female doctors reported an average of 49 work hours per week, whereas their male counterparts reported 50 work hours per week.

Meanwhile, the pay gap progressively worsened over time. Among doctors aged 28-34 years, men earned an average of $53,000 more than women. By ages 46-49, men earned an average of $157,000 more than women.

“I had to take my employer to court to get equal compensation, sad as it is to say,” said a hospitalist in North Carolina.

Nearly 60% of women surveyed felt they were not being paid fairly for their efforts, up from less than half reported in Medscape’s 2021 report. Hingle said that this figure may not only reflect sentiments about the compensation gap, but also less support on the job, including fewer physician assistants (PAs), nurses, and administrative staff.

“At my job, I do the work of multiple people,” said a survey respondent. “Junior resident, senior resident, social worker, nurse practitioner, PA — as well as try to be a teacher, researcher, [and] an excellent doctor and have the time to make patients feel as if they are not in a rush.”

Roughly 30% of women physicians said they would not choose to go into medicine again if given the chance compared with 26% of male physicians.

“Gender inequities in our profession have a direct impact,” said Shikha Jain, MD, an oncologist in Chicago and founder of the Women in Medicine nonprofit. “I think women in general don’t feel valued in the care they’re providing.” 

Jain cited bullying, harassment, and fewer opportunities for leadership and recognition as factors beyond pay that affect female physicians’ feelings of being valued.

A version of this article first appeared on Medscape.com.

Despite some recent progress in compensation equity, women in medicine continue to be paid significantly lower salaries than men.

According to the Female Compensation Report 2024 by Medscape, male doctors of any kind earned an average salary of about $400,000, whereas female doctors earned approximately $309,000 — a 29% gap.

The report analyzed survey data from 7000 practicing physicians who were recruited over a 4-month period starting in October 2023. The respondents comprised roughly 60% women representing over 29 specialties.

In the 2022 report, the pay gap between the genders was 32%. But some women in the field argued substantial headway is still needed.

“You can try and pick apart the data, but I’d say we’re not really making progress,” said Susan T. Hingle, MD, an internist in Illinois and president of the American Medical Women’s Association. “A decline by a couple of percentage points is not significantly addressing this pay gap that over a lifetime is huge, can be millions of dollars.”

The gender gap was narrower among female primary care physicians (PCPs) vs medical specialists. Female PCPs earned around $253,000 per year, whereas male PCPs earned about $295,000 per year. Hingle suggested that female PCPs may enjoy more pay equity because health systems have a harder time filling these positions.

On the other hand, the gap for specialists rose from 27% in 2022 to 31% in 2023. Differences in how aggressively women and men negotiate compensation packages may play a role, said Hingle.

“Taking negotiation out of the equation would be progress to me,” said Hingle.

Pay disparity did not appear to be the result of time spent on the job — female doctors reported an average of 49 work hours per week, whereas their male counterparts reported 50 work hours per week.

Meanwhile, the pay gap progressively worsened over time. Among doctors aged 28-34 years, men earned an average of $53,000 more than women. By ages 46-49, men earned an average of $157,000 more than women.

“I had to take my employer to court to get equal compensation, sad as it is to say,” said a hospitalist in North Carolina.

Nearly 60% of women surveyed felt they were not being paid fairly for their efforts, up from less than half reported in Medscape’s 2021 report. Hingle said that this figure may not only reflect sentiments about the compensation gap, but also less support on the job, including fewer physician assistants (PAs), nurses, and administrative staff.

“At my job, I do the work of multiple people,” said a survey respondent. “Junior resident, senior resident, social worker, nurse practitioner, PA — as well as try to be a teacher, researcher, [and] an excellent doctor and have the time to make patients feel as if they are not in a rush.”

Roughly 30% of women physicians said they would not choose to go into medicine again if given the chance compared with 26% of male physicians.

“Gender inequities in our profession have a direct impact,” said Shikha Jain, MD, an oncologist in Chicago and founder of the Women in Medicine nonprofit. “I think women in general don’t feel valued in the care they’re providing.” 

Jain cited bullying, harassment, and fewer opportunities for leadership and recognition as factors beyond pay that affect female physicians’ feelings of being valued.

A version of this article first appeared on Medscape.com.

Thoracic Oncology and Chest Procedures Network

Pleural Disease Section

Considerable heterogeneity exists in the management of primary spontaneous pneumothorax (PSP). American and European guidelines have been grappling with this question for decades: What is the best way to manage PSP? A 2023 randomized, controlled trial (Marx et al. AJRCCM) sought to answer this.

CHEST

The study recruited 379 adults aged 18 to 55 years between 2009 and 2015, with complete and first PSP in 31 French hospitals. One hundred eighty-nine patients initially received simple aspiration and 190 received chest tube drainage. The aspiration device was removed if a chest radiograph (CXR) following 30 minutes of aspiration showed lung apposition, with suction repeated up to one time with incomplete re-expansion. The chest tubes were large-bore (16-F or 20-F) and removed 72 hours postprocedure if the CXR showed complete lung re-expansion.

Pulmonary re-expansion at 24 hours was the primary outcome of interest, analyzed for noninferiority. Simple aspiration was statistically inferior to chest tube drainage (29% vs 18%). However, first-line simple aspiration resulted in shorter length of stay, less subcutaneous emphysema, site infection, pain, and one-year recurrence.

CHEST

Since most first-time PSP occurs in younger, healthier adults, simple aspiration could still be considered as it is better tolerated than large-bore chest tubes. However, with more frequent use of small-bore (≤14-F) catheters, ambulatory drainage could also be a suitable option in carefully selected patients. Additionally, inpatient chest tubes do not need to remain in place for 72 hours, as was this study’s protocol. Society guidelines will need to weigh in on the latest high-quality evidence available for final recommendations.

Thoracic Oncology and Chest Procedures Network

Pleural Disease Section

Considerable heterogeneity exists in the management of primary spontaneous pneumothorax (PSP). American and European guidelines have been grappling with this question for decades: What is the best way to manage PSP? A 2023 randomized, controlled trial (Marx et al. AJRCCM) sought to answer this.

CHEST

The study recruited 379 adults aged 18 to 55 years between 2009 and 2015, with complete and first PSP in 31 French hospitals. One hundred eighty-nine patients initially received simple aspiration and 190 received chest tube drainage. The aspiration device was removed if a chest radiograph (CXR) following 30 minutes of aspiration showed lung apposition, with suction repeated up to one time with incomplete re-expansion. The chest tubes were large-bore (16-F or 20-F) and removed 72 hours postprocedure if the CXR showed complete lung re-expansion.

Pulmonary re-expansion at 24 hours was the primary outcome of interest, analyzed for noninferiority. Simple aspiration was statistically inferior to chest tube drainage (29% vs 18%). However, first-line simple aspiration resulted in shorter length of stay, less subcutaneous emphysema, site infection, pain, and one-year recurrence.

CHEST

Since most first-time PSP occurs in younger, healthier adults, simple aspiration could still be considered as it is better tolerated than large-bore chest tubes. However, with more frequent use of small-bore (≤14-F) catheters, ambulatory drainage could also be a suitable option in carefully selected patients. Additionally, inpatient chest tubes do not need to remain in place for 72 hours, as was this study’s protocol. Society guidelines will need to weigh in on the latest high-quality evidence available for final recommendations.

Thoracic Oncology and Chest Procedures Network

Pleural Disease Section

Considerable heterogeneity exists in the management of primary spontaneous pneumothorax (PSP). American and European guidelines have been grappling with this question for decades: What is the best way to manage PSP? A 2023 randomized, controlled trial (Marx et al. AJRCCM) sought to answer this.

CHEST

The study recruited 379 adults aged 18 to 55 years between 2009 and 2015, with complete and first PSP in 31 French hospitals. One hundred eighty-nine patients initially received simple aspiration and 190 received chest tube drainage. The aspiration device was removed if a chest radiograph (CXR) following 30 minutes of aspiration showed lung apposition, with suction repeated up to one time with incomplete re-expansion. The chest tubes were large-bore (16-F or 20-F) and removed 72 hours postprocedure if the CXR showed complete lung re-expansion.

Pulmonary re-expansion at 24 hours was the primary outcome of interest, analyzed for noninferiority. Simple aspiration was statistically inferior to chest tube drainage (29% vs 18%). However, first-line simple aspiration resulted in shorter length of stay, less subcutaneous emphysema, site infection, pain, and one-year recurrence.

CHEST

Since most first-time PSP occurs in younger, healthier adults, simple aspiration could still be considered as it is better tolerated than large-bore chest tubes. However, with more frequent use of small-bore (≤14-F) catheters, ambulatory drainage could also be a suitable option in carefully selected patients. Additionally, inpatient chest tubes do not need to remain in place for 72 hours, as was this study’s protocol. Society guidelines will need to weigh in on the latest high-quality evidence available for final recommendations.

Airways Disorders Network

Pediatric Chest Medicine Section

Artificial intelligence (AI) refers to the science and engineering of making intelligent machines that mimic human cognitive functions, such as learning and problem solving.¹AI tools are being increasingly utilized in pediatric pulmonary disease management to analyze the tremendous amount of patient data on environmental and physiological variables and compliance with therapy. Asthma exacerbations in young children were detected reliably by AI-aided stethoscope alone.² Inhaler use has been successfully tracked using active and passive patient input to cloud-based dashboards.³ Asthma specialists can potentially use this knowledge to intervene in real time or more frequent intervals than the current episodic care.

CHEST

Sleep trackers using commercial-grade sensors can provide useful information about sleep hygiene, sleep duration, and nocturnal awakenings. An increasing number of “wearables” and “nearables” that utilize AI algorithms to evaluate sleep duration and quality are FDA approved. AI-based scoring of polysomnography data can improve the efficiency of a sleep laboratory. Big data analysis of CPAP compliance in children led to identification of actionable items that can be targeted to improve patient outcomes.⁴

The use of AI models in clinical decision support can result in fewer false alerts and missed patients due to increased model accuracy. Additionally, large language model tools can automatically generate comprehensive progress notes incorporating relevant electronic medical records data, thereby reducing physician charting time.

These case uses highlight the potential to improve workflow efficiency and clinical outcomes in pediatric pulmonary and critical care by incorporating AI tools in medical decision-making and management.

References

1. McCarthy JF, Marx KA, Hoffman PE, et al. Applications of machine learning and high-dimensional visualization in cancer detection, diagnosis, and management. Ann N Y Acad Sci. 2004;1020:239-262.

2. Emeryk A, Derom E, Janeczek K, et al. Home monitoring of asthma exacerbations in children and adults with use of an AI-aided stethoscope. Ann Fam Med. 2023;21(6):517-525.

3. Jaimini U, Thirunarayan K, Kalra M, Venkataraman R, Kadariya D, Sheth A. How is my child’s asthma?” Digital phenotype and actionable insights for pediatric asthma. JMIR Pediatr Parent. 2018;1(2):e11988.

4. Bhattacharjee R, Benjafield AV, Armitstead J, et al. Adherence in children using positive airway pressure therapy: a big-data analysis [published correction appears in Lancet Digit Health. 2020 Sep;2(9):e455.]. Lancet Digit Health. 2020;2(2):e94-e101.

Airways Disorders Network

Pediatric Chest Medicine Section

Artificial intelligence (AI) refers to the science and engineering of making intelligent machines that mimic human cognitive functions, such as learning and problem solving.¹AI tools are being increasingly utilized in pediatric pulmonary disease management to analyze the tremendous amount of patient data on environmental and physiological variables and compliance with therapy. Asthma exacerbations in young children were detected reliably by AI-aided stethoscope alone.² Inhaler use has been successfully tracked using active and passive patient input to cloud-based dashboards.³ Asthma specialists can potentially use this knowledge to intervene in real time or more frequent intervals than the current episodic care.

CHEST

Sleep trackers using commercial-grade sensors can provide useful information about sleep hygiene, sleep duration, and nocturnal awakenings. An increasing number of “wearables” and “nearables” that utilize AI algorithms to evaluate sleep duration and quality are FDA approved. AI-based scoring of polysomnography data can improve the efficiency of a sleep laboratory. Big data analysis of CPAP compliance in children led to identification of actionable items that can be targeted to improve patient outcomes.⁴

The use of AI models in clinical decision support can result in fewer false alerts and missed patients due to increased model accuracy. Additionally, large language model tools can automatically generate comprehensive progress notes incorporating relevant electronic medical records data, thereby reducing physician charting time.

These case uses highlight the potential to improve workflow efficiency and clinical outcomes in pediatric pulmonary and critical care by incorporating AI tools in medical decision-making and management.

References

1. McCarthy JF, Marx KA, Hoffman PE, et al. Applications of machine learning and high-dimensional visualization in cancer detection, diagnosis, and management. Ann N Y Acad Sci. 2004;1020:239-262.

2. Emeryk A, Derom E, Janeczek K, et al. Home monitoring of asthma exacerbations in children and adults with use of an AI-aided stethoscope. Ann Fam Med. 2023;21(6):517-525.

3. Jaimini U, Thirunarayan K, Kalra M, Venkataraman R, Kadariya D, Sheth A. How is my child’s asthma?” Digital phenotype and actionable insights for pediatric asthma. JMIR Pediatr Parent. 2018;1(2):e11988.

4. Bhattacharjee R, Benjafield AV, Armitstead J, et al. Adherence in children using positive airway pressure therapy: a big-data analysis [published correction appears in Lancet Digit Health. 2020 Sep;2(9):e455.]. Lancet Digit Health. 2020;2(2):e94-e101.

Airways Disorders Network

Pediatric Chest Medicine Section

Artificial intelligence (AI) refers to the science and engineering of making intelligent machines that mimic human cognitive functions, such as learning and problem solving.¹AI tools are being increasingly utilized in pediatric pulmonary disease management to analyze the tremendous amount of patient data on environmental and physiological variables and compliance with therapy. Asthma exacerbations in young children were detected reliably by AI-aided stethoscope alone.² Inhaler use has been successfully tracked using active and passive patient input to cloud-based dashboards.³ Asthma specialists can potentially use this knowledge to intervene in real time or more frequent intervals than the current episodic care.

CHEST

Sleep trackers using commercial-grade sensors can provide useful information about sleep hygiene, sleep duration, and nocturnal awakenings. An increasing number of “wearables” and “nearables” that utilize AI algorithms to evaluate sleep duration and quality are FDA approved. AI-based scoring of polysomnography data can improve the efficiency of a sleep laboratory. Big data analysis of CPAP compliance in children led to identification of actionable items that can be targeted to improve patient outcomes.⁴

The use of AI models in clinical decision support can result in fewer false alerts and missed patients due to increased model accuracy. Additionally, large language model tools can automatically generate comprehensive progress notes incorporating relevant electronic medical records data, thereby reducing physician charting time.

These case uses highlight the potential to improve workflow efficiency and clinical outcomes in pediatric pulmonary and critical care by incorporating AI tools in medical decision-making and management.

References

1. McCarthy JF, Marx KA, Hoffman PE, et al. Applications of machine learning and high-dimensional visualization in cancer detection, diagnosis, and management. Ann N Y Acad Sci. 2004;1020:239-262.

2. Emeryk A, Derom E, Janeczek K, et al. Home monitoring of asthma exacerbations in children and adults with use of an AI-aided stethoscope. Ann Fam Med. 2023;21(6):517-525.

3. Jaimini U, Thirunarayan K, Kalra M, Venkataraman R, Kadariya D, Sheth A. How is my child’s asthma?” Digital phenotype and actionable insights for pediatric asthma. JMIR Pediatr Parent. 2018;1(2):e11988.

4. Bhattacharjee R, Benjafield AV, Armitstead J, et al. Adherence in children using positive airway pressure therapy: a big-data analysis [published correction appears in Lancet Digit Health. 2020 Sep;2(9):e455.]. Lancet Digit Health. 2020;2(2):e94-e101.

Critical Care Network

Mechanical Ventilation and Airways Management Section

The ARDSNet trial demonstrated the importance of low tidal volume ventilation in patients with ARDS, and we have learned to monitor parameters such as plateau pressure and driving pressure (DP) to ensure lung-protective ventilation. However, severe hypercapnia can occur with low tidal volume ventilation and respiratory rate would often need to be increased. What role does the higher respiratory rate play? There is growing evidence that respiratory rate may play an important part in the pathogenesis of ventilator-induced lung injury (VILI) and the dynamic effect of both rate and static pressures needs to be evaluated.

CHEST

The concept of mechanical power (MP) was formalized in 2016 by Gattinoni, et al and defined as the product of respiratory rate and total inflation energy gained per breath.¹ Calculations have been developed for both volume-controlled and pressure-controlled ventilation, including elements such as respiratory rate and PEEP. Studies have shown that increased MP is associated with ICU and hospital mortality, even at low tidal volumes.² The use of MP remains limited in clinical practice due to its dynamic nature and difficulty of calculating in routine clinical practice but may be a feasible addition to the continuous monitoring outputs on a ventilator. Additional prospective studies are also needed to define the optimal threshold of MP and to compare monitoring strategies using MP vs DP.

References

1. Gattinoni L, Tonetti T, Cressoni M, et al. Ventilator-related causes of lung injury: the mechanical power. Intensive Care Med. 2016;42(10):1567-1575.

2. Serpa Neto A, Deliberato RO, Johnson AEW, et al. Mechanical power of ventilation is associated with mortality in critically ill patients: an analysis of patients in two observational cohorts. Intensive Care Med. 2018;44(11):1914-1922.

Critical Care Network

Mechanical Ventilation and Airways Management Section

The ARDSNet trial demonstrated the importance of low tidal volume ventilation in patients with ARDS, and we have learned to monitor parameters such as plateau pressure and driving pressure (DP) to ensure lung-protective ventilation. However, severe hypercapnia can occur with low tidal volume ventilation and respiratory rate would often need to be increased. What role does the higher respiratory rate play? There is growing evidence that respiratory rate may play an important part in the pathogenesis of ventilator-induced lung injury (VILI) and the dynamic effect of both rate and static pressures needs to be evaluated.

CHEST

The concept of mechanical power (MP) was formalized in 2016 by Gattinoni, et al and defined as the product of respiratory rate and total inflation energy gained per breath.¹ Calculations have been developed for both volume-controlled and pressure-controlled ventilation, including elements such as respiratory rate and PEEP. Studies have shown that increased MP is associated with ICU and hospital mortality, even at low tidal volumes.² The use of MP remains limited in clinical practice due to its dynamic nature and difficulty of calculating in routine clinical practice but may be a feasible addition to the continuous monitoring outputs on a ventilator. Additional prospective studies are also needed to define the optimal threshold of MP and to compare monitoring strategies using MP vs DP.

References

1. Gattinoni L, Tonetti T, Cressoni M, et al. Ventilator-related causes of lung injury: the mechanical power. Intensive Care Med. 2016;42(10):1567-1575.

2. Serpa Neto A, Deliberato RO, Johnson AEW, et al. Mechanical power of ventilation is associated with mortality in critically ill patients: an analysis of patients in two observational cohorts. Intensive Care Med. 2018;44(11):1914-1922.

Critical Care Network

Mechanical Ventilation and Airways Management Section

The ARDSNet trial demonstrated the importance of low tidal volume ventilation in patients with ARDS, and we have learned to monitor parameters such as plateau pressure and driving pressure (DP) to ensure lung-protective ventilation. However, severe hypercapnia can occur with low tidal volume ventilation and respiratory rate would often need to be increased. What role does the higher respiratory rate play? There is growing evidence that respiratory rate may play an important part in the pathogenesis of ventilator-induced lung injury (VILI) and the dynamic effect of both rate and static pressures needs to be evaluated.

CHEST

The concept of mechanical power (MP) was formalized in 2016 by Gattinoni, et al and defined as the product of respiratory rate and total inflation energy gained per breath.¹ Calculations have been developed for both volume-controlled and pressure-controlled ventilation, including elements such as respiratory rate and PEEP. Studies have shown that increased MP is associated with ICU and hospital mortality, even at low tidal volumes.² The use of MP remains limited in clinical practice due to its dynamic nature and difficulty of calculating in routine clinical practice but may be a feasible addition to the continuous monitoring outputs on a ventilator. Additional prospective studies are also needed to define the optimal threshold of MP and to compare monitoring strategies using MP vs DP.

References

1. Gattinoni L, Tonetti T, Cressoni M, et al. Ventilator-related causes of lung injury: the mechanical power. Intensive Care Med. 2016;42(10):1567-1575.

2. Serpa Neto A, Deliberato RO, Johnson AEW, et al. Mechanical power of ventilation is associated with mortality in critically ill patients: an analysis of patients in two observational cohorts. Intensive Care Med. 2018;44(11):1914-1922.

Pulmonary Vascular and Cardiovascular Network

Pulmonary Vascular Disease Section

The core definition of pulmonary hypertension (PH) remains a mean pulmonary arterial pressure (mPAP) > 20 mm Hg, with precapillary PH defined by a pulmonary arterial wedge pressure (PCWP) ≤ 15 mm Hg and pulmonary vascular resistance (PVR) > 2 Wood units (WU), similar to the 2022 European guidelines.^1,2 There was recognition of uncertainty in patients with borderline PAWP (12-18 mm Hg) for postcapillary PH.

CHEST

A new staging model for group 2 PH was proposed to refine treatment strategies based on disease progression. It’s crucial to phenotype patients, especially those with valvular heart disease, hypertrophic cardiomyopathy, or amyloid cardiomyopathy, and to be cautious when using PAH medications for this PH group.³ 

CHEST

CHEST

References

1. Kovacs G, Bartolome S, Denton CP, et al. Definition, classification and diagnosis of pulmonary hypertension. Eur Respir J. 2024;2401324. (Online ahead of print.)

2. Humbert M, Kovacs G, Hoeper MM, et al. 2022 ESC/ERS Guidelines for the diagnosis and treatment of pulmonary hypertension. Eur Respir J. 2024;61(1):2200879.

3. Maron BA, Bortman G, De Marco T, et al. Pulmonary hypertension associated with left heart disease. Eur Respir J. 2024;2401344. (Online ahead of print.)

4. Shlobin OA, Adir Y, Barbera JA, et al. Pulmonary hypertension associated with lung diseases. Eur Respir J. 2024;2401200. (Online ahead of print.)

5. Chin KM, Gaine SP, Gerges C, et al. Treatment algorithm for pulmonary arterial hypertension. Eur Respir J. 2024;2401325. (Online ahead of print.)

Pulmonary Vascular and Cardiovascular Network

Pulmonary Vascular Disease Section

The core definition of pulmonary hypertension (PH) remains a mean pulmonary arterial pressure (mPAP) > 20 mm Hg, with precapillary PH defined by a pulmonary arterial wedge pressure (PCWP) ≤ 15 mm Hg and pulmonary vascular resistance (PVR) > 2 Wood units (WU), similar to the 2022 European guidelines.^1,2 There was recognition of uncertainty in patients with borderline PAWP (12-18 mm Hg) for postcapillary PH.

CHEST

A new staging model for group 2 PH was proposed to refine treatment strategies based on disease progression. It’s crucial to phenotype patients, especially those with valvular heart disease, hypertrophic cardiomyopathy, or amyloid cardiomyopathy, and to be cautious when using PAH medications for this PH group.³ 

CHEST

CHEST

References

1. Kovacs G, Bartolome S, Denton CP, et al. Definition, classification and diagnosis of pulmonary hypertension. Eur Respir J. 2024;2401324. (Online ahead of print.)

2. Humbert M, Kovacs G, Hoeper MM, et al. 2022 ESC/ERS Guidelines for the diagnosis and treatment of pulmonary hypertension. Eur Respir J. 2024;61(1):2200879.

3. Maron BA, Bortman G, De Marco T, et al. Pulmonary hypertension associated with left heart disease. Eur Respir J. 2024;2401344. (Online ahead of print.)

4. Shlobin OA, Adir Y, Barbera JA, et al. Pulmonary hypertension associated with lung diseases. Eur Respir J. 2024;2401200. (Online ahead of print.)

5. Chin KM, Gaine SP, Gerges C, et al. Treatment algorithm for pulmonary arterial hypertension. Eur Respir J. 2024;2401325. (Online ahead of print.)

Pulmonary Vascular and Cardiovascular Network

Pulmonary Vascular Disease Section

The core definition of pulmonary hypertension (PH) remains a mean pulmonary arterial pressure (mPAP) > 20 mm Hg, with precapillary PH defined by a pulmonary arterial wedge pressure (PCWP) ≤ 15 mm Hg and pulmonary vascular resistance (PVR) > 2 Wood units (WU), similar to the 2022 European guidelines.^1,2 There was recognition of uncertainty in patients with borderline PAWP (12-18 mm Hg) for postcapillary PH.

CHEST

A new staging model for group 2 PH was proposed to refine treatment strategies based on disease progression. It’s crucial to phenotype patients, especially those with valvular heart disease, hypertrophic cardiomyopathy, or amyloid cardiomyopathy, and to be cautious when using PAH medications for this PH group.³ 

CHEST

CHEST

References

1. Kovacs G, Bartolome S, Denton CP, et al. Definition, classification and diagnosis of pulmonary hypertension. Eur Respir J. 2024;2401324. (Online ahead of print.)

2. Humbert M, Kovacs G, Hoeper MM, et al. 2022 ESC/ERS Guidelines for the diagnosis and treatment of pulmonary hypertension. Eur Respir J. 2024;61(1):2200879.

3. Maron BA, Bortman G, De Marco T, et al. Pulmonary hypertension associated with left heart disease. Eur Respir J. 2024;2401344. (Online ahead of print.)

4. Shlobin OA, Adir Y, Barbera JA, et al. Pulmonary hypertension associated with lung diseases. Eur Respir J. 2024;2401200. (Online ahead of print.)

5. Chin KM, Gaine SP, Gerges C, et al. Treatment algorithm for pulmonary arterial hypertension. Eur Respir J. 2024;2401325. (Online ahead of print.)