Publications
1.
Hawkins, Kellie L.; Dandachi, Dima; Verzani, Zoe; Brannock, M. Daniel; Lewis, Colby; Abedian, Sajjad; Jaferian, Sohrab; Wuller, Shannon; Truong, Jennifer; Witvliet, Margot Gage; Dymond, Gretchen; Mehta, Hemalkumar B.; Patel, Payal B.; Hill, Elaine; Weiner, Mark G.; Carton, Thomas W.; Kaushal, Rainu; Feuerriegel, Elen; Tran, Huong G.; Marks, Kristen; Oliveira, Carlos R.; Gardner, Edward M.; Ofotokun, Igho; Gulick, Roy M.; Erlandson, Kristine M.
HIV Infection and Long COVID: A RECOVER Program, Electronic Health Record-Based Cohort Study Journal Article
In: Clinical Infectious Diseases, vol. 81, iss. 3, pp. 427-438, 2025.
Abstract | Links | BibTeX | Tags: chronic diseases, COVID-19, health disparities, HIV, long COVID
@article{nokey,
title = {HIV Infection and Long COVID: A RECOVER Program, Electronic Health Record-Based Cohort Study},
author = {Kellie L. Hawkins and Dima Dandachi and Zoe Verzani and M. Daniel Brannock and Colby Lewis and Sajjad Abedian and Sohrab Jaferian and Shannon Wuller and Jennifer Truong and Margot Gage Witvliet and Gretchen Dymond and Hemalkumar B. Mehta and Payal B. Patel and Elaine Hill and Mark G. Weiner and Thomas W. Carton and Rainu Kaushal and Elen Feuerriegel and Huong G. Tran and Kristen Marks and Carlos R. Oliveira and Edward M. Gardner and Igho Ofotokun and Roy M. Gulick and Kristine M. Erlandson},
doi = {10.1093/cid/ciaf242},
year = {2025},
date = {2025-10-06},
urldate = {2025-10-06},
journal = {Clinical Infectious Diseases},
volume = {81},
issue = {3},
pages = {427-438},
abstract = {Background: People with human immunodeficiency virus (HIV) may be at increased risk for long COVID after acute severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We investigated the association between HIV and long COVID in 2 large electronic health record databases.
Methods: Using data from the Patient-Centered Clinical Research Network (PCORnet) and the National Clinical Cohort Collaborative (N3C) from 1 January 2018 to 30 April 2024, our analytic sample included individuals aged ≥21 years with SARS-CoV-2. All individuals were classified as having HIV or not. We estimated the adjusted odds ratio (aOR) of long COVID by HIV status using logistic regression. Multivariable models controlled for potential associated factors and used 2 cohort definitions: a computed phenotype definition or ICD-10 code-based definition.
Results: We included 1 369 896 patients from PCORnet (11 964 with and 1 357 932 without HIV) and 3 312 355 patients from N3C (23 931 with and 3 288 424 without HIV). Using the computed phenotype definition of long COVID, we noted a small, but significant, increase in odds of developing long COVID among people with compared to those without HIV (PCORnet: aOR, 1.09 [95% confidence interval {CI}, 1.04-1.14]; N3C: aOR, 1.18 [95% CI, 1.13-1.23]). Using the ICD-10 definition of long COVID, there was no association between HIV and long COVID (PCORnet: aOR, 1.01 [95% CI, .88-1.16]; N3C: aOR, 1.07 [95% CI, .97-1.18]).
Conclusions: In this large multicenter study, people with HIV had a modestly increased risk of long COVID when defined by a computed phenotype, but not when using ICD-10 codes. These findings suggest that long COVID may be underrecognized in people with HIV and underscore challenges in diagnosing long COVID in populations with baseline chronic conditions.},
keywords = {chronic diseases, COVID-19, health disparities, HIV, long COVID},
pubstate = {published},
tppubtype = {article}
}
Background: People with human immunodeficiency virus (HIV) may be at increased risk for long COVID after acute severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We investigated the association between HIV and long COVID in 2 large electronic health record databases.
Methods: Using data from the Patient-Centered Clinical Research Network (PCORnet) and the National Clinical Cohort Collaborative (N3C) from 1 January 2018 to 30 April 2024, our analytic sample included individuals aged ≥21 years with SARS-CoV-2. All individuals were classified as having HIV or not. We estimated the adjusted odds ratio (aOR) of long COVID by HIV status using logistic regression. Multivariable models controlled for potential associated factors and used 2 cohort definitions: a computed phenotype definition or ICD-10 code-based definition.
Results: We included 1 369 896 patients from PCORnet (11 964 with and 1 357 932 without HIV) and 3 312 355 patients from N3C (23 931 with and 3 288 424 without HIV). Using the computed phenotype definition of long COVID, we noted a small, but significant, increase in odds of developing long COVID among people with compared to those without HIV (PCORnet: aOR, 1.09 [95% confidence interval {CI}, 1.04-1.14]; N3C: aOR, 1.18 [95% CI, 1.13-1.23]). Using the ICD-10 definition of long COVID, there was no association between HIV and long COVID (PCORnet: aOR, 1.01 [95% CI, .88-1.16]; N3C: aOR, 1.07 [95% CI, .97-1.18]).
Conclusions: In this large multicenter study, people with HIV had a modestly increased risk of long COVID when defined by a computed phenotype, but not when using ICD-10 codes. These findings suggest that long COVID may be underrecognized in people with HIV and underscore challenges in diagnosing long COVID in populations with baseline chronic conditions.
Methods: Using data from the Patient-Centered Clinical Research Network (PCORnet) and the National Clinical Cohort Collaborative (N3C) from 1 January 2018 to 30 April 2024, our analytic sample included individuals aged ≥21 years with SARS-CoV-2. All individuals were classified as having HIV or not. We estimated the adjusted odds ratio (aOR) of long COVID by HIV status using logistic regression. Multivariable models controlled for potential associated factors and used 2 cohort definitions: a computed phenotype definition or ICD-10 code-based definition.
Results: We included 1 369 896 patients from PCORnet (11 964 with and 1 357 932 without HIV) and 3 312 355 patients from N3C (23 931 with and 3 288 424 without HIV). Using the computed phenotype definition of long COVID, we noted a small, but significant, increase in odds of developing long COVID among people with compared to those without HIV (PCORnet: aOR, 1.09 [95% confidence interval {CI}, 1.04-1.14]; N3C: aOR, 1.18 [95% CI, 1.13-1.23]). Using the ICD-10 definition of long COVID, there was no association between HIV and long COVID (PCORnet: aOR, 1.01 [95% CI, .88-1.16]; N3C: aOR, 1.07 [95% CI, .97-1.18]).
Conclusions: In this large multicenter study, people with HIV had a modestly increased risk of long COVID when defined by a computed phenotype, but not when using ICD-10 codes. These findings suggest that long COVID may be underrecognized in people with HIV and underscore challenges in diagnosing long COVID in populations with baseline chronic conditions.
2.
Charlson, Mary E.; Mittleman, Ilana; Ramos, Rosio; Cassells, Andrea; Lin, T. J.; Eggleston, Alice; Wells, Marin T.; Hollenberg, James; Pirraglia, Paul; Winston, Ginger; Tobin, Jonathan N.
Preventing "tipping points" in high comorbidity patients: A lifeline from health coaches - rationale, design and methods Journal Article
In: Contemporary Clinical Trials, vol. 152, pp. 107865, 2025.
Abstract | Links | BibTeX | Tags: chronic diseases, federally qualified health centers, practice-based research networks
@article{nokey,
title = {Preventing "tipping points" in high comorbidity patients: A lifeline from health coaches - rationale, design and methods},
author = {Mary E. Charlson and Ilana Mittleman and Rosio Ramos and Andrea Cassells and T.J. Lin and Alice Eggleston and Marin T. Wells and James Hollenberg and Paul Pirraglia and Ginger Winston and Jonathan N. Tobin},
doi = {10.1016/j.cct.2025.107865},
year = {2025},
date = {2025-02-28},
journal = {Contemporary Clinical Trials},
volume = {152},
pages = {107865},
abstract = {Background: This paper describes an innovative cluster randomized controlled trial design to evaluate the comparative effectiveness of two approaches to preventing significant destabilization, leading to unplanned hospitalization and increased disability for patients with high comorbidity, that is, multiple chronic diseases defined by an enhanced Charlson Comorbidity Index ≥4.
Methods: A total of 1974 patients were randomized in four waves at each of the sixteen Federally Qualified Health Centers (FQHCs) in four health systems -two in New York and two in Chicago. The two interventions compared 1) Patient-Centered Medical Home (PCMH) as implemented by the FQHCs (usual care control); or 2) PCMH plus a coaching intervention delivered by Health Coaches (experimental) helping patients identify life goals to encourage self-management enhanced by a positive affect/self-affirmation strategy. The two primary patient-centered clinical outcomes are 1) Unplanned hospitalizations; and 2) Within-patient changes in quality of life and disability, as measured by the World Health Organization Disability Assessment Scale 2 (WHODAS 2.0). The hypotheses are: 1) intervention patients will have a 5 % relative reduction in unplanned hospitalizations as compared to control patients; and 2) reduced disability measured by WHODAS2.0; 3) destabilization or 'tipping points' leading to hospitalization will be more often triggered by psychosocial issues than by medical Issues.
Conclusion: This cluster RCT has the potential to transform the care for patients with high comorbidity by helping motivate patients to engage in self-management and to successfully navigate the barriers, challenges, and stresses leading to destabilization, hospitalization, and increased disability.},
keywords = {chronic diseases, federally qualified health centers, practice-based research networks},
pubstate = {published},
tppubtype = {article}
}
Background: This paper describes an innovative cluster randomized controlled trial design to evaluate the comparative effectiveness of two approaches to preventing significant destabilization, leading to unplanned hospitalization and increased disability for patients with high comorbidity, that is, multiple chronic diseases defined by an enhanced Charlson Comorbidity Index ≥4.
Methods: A total of 1974 patients were randomized in four waves at each of the sixteen Federally Qualified Health Centers (FQHCs) in four health systems -two in New York and two in Chicago. The two interventions compared 1) Patient-Centered Medical Home (PCMH) as implemented by the FQHCs (usual care control); or 2) PCMH plus a coaching intervention delivered by Health Coaches (experimental) helping patients identify life goals to encourage self-management enhanced by a positive affect/self-affirmation strategy. The two primary patient-centered clinical outcomes are 1) Unplanned hospitalizations; and 2) Within-patient changes in quality of life and disability, as measured by the World Health Organization Disability Assessment Scale 2 (WHODAS 2.0). The hypotheses are: 1) intervention patients will have a 5 % relative reduction in unplanned hospitalizations as compared to control patients; and 2) reduced disability measured by WHODAS2.0; 3) destabilization or 'tipping points' leading to hospitalization will be more often triggered by psychosocial issues than by medical Issues.
Conclusion: This cluster RCT has the potential to transform the care for patients with high comorbidity by helping motivate patients to engage in self-management and to successfully navigate the barriers, challenges, and stresses leading to destabilization, hospitalization, and increased disability.
Methods: A total of 1974 patients were randomized in four waves at each of the sixteen Federally Qualified Health Centers (FQHCs) in four health systems -two in New York and two in Chicago. The two interventions compared 1) Patient-Centered Medical Home (PCMH) as implemented by the FQHCs (usual care control); or 2) PCMH plus a coaching intervention delivered by Health Coaches (experimental) helping patients identify life goals to encourage self-management enhanced by a positive affect/self-affirmation strategy. The two primary patient-centered clinical outcomes are 1) Unplanned hospitalizations; and 2) Within-patient changes in quality of life and disability, as measured by the World Health Organization Disability Assessment Scale 2 (WHODAS 2.0). The hypotheses are: 1) intervention patients will have a 5 % relative reduction in unplanned hospitalizations as compared to control patients; and 2) reduced disability measured by WHODAS2.0; 3) destabilization or 'tipping points' leading to hospitalization will be more often triggered by psychosocial issues than by medical Issues.
Conclusion: This cluster RCT has the potential to transform the care for patients with high comorbidity by helping motivate patients to engage in self-management and to successfully navigate the barriers, challenges, and stresses leading to destabilization, hospitalization, and increased disability.
3.
Blecker, Saul; Jones, Simon A.; Petrilli, Christopher M.; Admon, Andrew J.; Weerahandi, Himali; Francois, Fritz; Horwitz, Leora I.
Hospitalizations for Chronic Disease and Acute Conditions in the Time of COVID-19 Journal Article
In: JAMA Internal Medicine, vol. 181, iss. 2, pp. 269-271, 2021.
Abstract | Links | BibTeX | Tags: chronic diseases, COVID-19, hospitalization
@article{nokey,
title = {Hospitalizations for Chronic Disease and Acute Conditions in the Time of COVID-19},
author = {Saul Blecker and Simon A. Jones and Christopher M. Petrilli and Andrew J. Admon and Himali Weerahandi and Fritz Francois and Leora I. Horwitz},
doi = {10.1001/jamainternmed.2020.3978},
year = {2021},
date = {2021-02-01},
journal = {JAMA Internal Medicine},
volume = {181},
issue = {2},
pages = {269-271},
abstract = {This study examines the frequency of hospitalization for all non–COVID-19-related conditions in a health system at the epicenter of the COVID-19 pandemic.},
keywords = {chronic diseases, COVID-19, hospitalization},
pubstate = {published},
tppubtype = {article}
}
This study examines the frequency of hospitalization for all non–COVID-19-related conditions in a health system at the epicenter of the COVID-19 pandemic.