Risk factors associated with post-acute sequelae of SARS-CoV-2: an N3C and NIH RECOVER study

BMC Public Health

Research Article

Catherine Xie¹  Julie A. McMurry²  Melissa A. Haendel³  Richard Moffitt⁴  Tellen D. Bennett⁵  Heidi Spratt⁶  Nariman Ammar⁷  Charisse Madlock-Brown⁸  Klint Mane⁹  Hemalkumar B. Mehta^1,10  Emily R. Pfaff^1,11  Peter E. DeWitt^1,12  Seth Russell^1,12  Elaine L. Hill^1,13  Sharad Kumar Singh^1,14  Donald Brown^1,15  Emily Cathey^1,16  Johanna Loomba^1,16  Suchetha Sharma^1,17  Christopher G. Chute^1,18 

[1] CMC BOX 275184, University of Rochester, 500 Joseph C. Wilson Blvd, 14627-5184, Rochester, NY, USA;Center for Health AI, University of Colorado School of Medicine, 12800 East 19Th Avenue, 80045, Aurora, CO, USA;Center for Health AI, University of Colorado School of Medicine, East 17Th Place Campus Box C290, 1300180045, Aurora, CO, USA;Department of Biomedical Informatics, Stony Brook University, and Stony Brook Cancer Center, MART L7 081011794, Stony Brook, NY, USA;Department of Biomedical Informatics, University of Colorado School of Medicine, 1890 N. Revere Court, Mail Stop 600, 80045, Aurora, CO, USA;Department of Biostatistics and Data Science, Medical Branch, University of Texas, 301 University Blvd, 77555-1148, Galveston, TX, USA;Department of Diagnostic and Health Sciences, University of Tennessee Health Science Center, 50 N Dunlap St., 38103, Memphis, TN, USA;Department of Diagnostic and Health Sciences, University of Tennessee Health Science Center, 930 Madison Avenue 6Th Floor, 38163, Memphis, TN, USA;Department of Economics, University of Rochester, 1232 Mount Hope Ave, 14620, Rochester, NY, USA;Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe St, 21205, Baltimore, MD, USA;Department of Medicine, North Carolina Translational and Clinical Sciences Institute, University of North Carolina at Chapel Hill, 160 N Medical Drive, 27599, Chapel Hill, NC, USA;Department of Pediatrics, University of Colorado School of Medicine, 1890 N. Revere Court, Mail Stop 600, 80045, Aurora, CO, USA;Department of Public Health Sciences, University of Rochester Medical Center, 265 Crittenden Boulevard Box 420644, 14642, Rochester, NY, USA;Goergen Institute for Data Science, University of Rochester, 1209 Wegmans Hall, 14627, Rochester, NY, USA;Integrated Translational Health Research Institute of Virginia (iTHRIV), University of Virginia, PO Box 400747, 151 Engineer’s Way Olsson Hall Rm. 102E, Charlottesville, VA, USA;Ivy Foundations Building, Integrated Translational Health Research Institute of Virginia (iTHRIV), University of Virginia, 560 Ray C Hunt Drive RM 2153, 22903, Charlottesville, VA, USA;School of Data Science, University of Virginia, 3 Elliewood Ave, 22903, Charlottesville, VA, USA;Schools of Medicine, Public Health, and Nursing, Johns Hopkins University, 2024 E Monument St., 21287, Baltimore, MD, USA;

关键词: Post-acute sequelae of SARS-CoV-2;    PASC;    Long-COVID;    COVID-19;    Risk factors;   

DOI  :  10.1186/s12889-023-16916-w

 received in 2022-10-19, accepted in 2023-10-05,  发布年份 2023

来源: Springer

【 摘 要 】

BackgroundMore than one-third of individuals experience post-acute sequelae of SARS-CoV-2 infection (PASC, which includes long-COVID). The objective is to identify risk factors associated with PASC/long-COVID diagnosis.MethodsThis was a retrospective case–control study including 31 health systems in the United States from the National COVID Cohort Collaborative (N3C). 8,325 individuals with PASC (defined by the presence of the International Classification of Diseases, version 10 code U09.9 or a long-COVID clinic visit) matched to 41,625 controls within the same health system and COVID index date within ± 45 days of the corresponding case's earliest COVID index date. Measurements of risk factors included demographics, comorbidities, treatment and acute characteristics related to COVID-19. Multivariable logistic regression, random forest, and XGBoost were used to determine the associations between risk factors and PASC.ResultsAmong 8,325 individuals with PASC, the majority were > 50 years of age (56.6%), female (62.8%), and non-Hispanic White (68.6%). In logistic regression, middle-age categories (40 to 69 years; OR ranging from 2.32 to 2.58), female sex (OR 1.4, 95% CI 1.33–1.48), hospitalization associated with COVID-19 (OR 3.8, 95% CI 3.05–4.73), long (8–30 days, OR 1.69, 95% CI 1.31–2.17) or extended hospital stay (30 + days, OR 3.38, 95% CI 2.45–4.67), receipt of mechanical ventilation (OR 1.44, 95% CI 1.18–1.74), and several comorbidities including depression (OR 1.50, 95% CI 1.40–1.60), chronic lung disease (OR 1.63, 95% CI 1.53–1.74), and obesity (OR 1.23, 95% CI 1.16–1.3) were associated with increased likelihood of PASC diagnosis or care at a long-COVID clinic. Characteristics associated with a lower likelihood of PASC diagnosis or care at a long-COVID clinic included younger age (18 to 29 years), male sex, non-Hispanic Black race, and comorbidities such as substance abuse, cardiomyopathy, psychosis, and dementia. More doctors per capita in the county of residence was associated with an increased likelihood of PASC diagnosis or care at a long-COVID clinic. Our findings were consistent in sensitivity analyses using a variety of analytic techniques and approaches to select controls.ConclusionsThis national study identified important risk factors for PASC diagnosis such as middle age, severe COVID-19 disease, and specific comorbidities. Further clinical and epidemiological research is needed to better understand underlying mechanisms and the potential role of vaccines and therapeutics in altering PASC course.

【 授权许可】

CC BY   
© BioMed Central Ltd., part of Springer Nature 2023

【 图 表 】

40517_2023_273_Article_IEq6.gif

40517_2023_273_Article_IEq2.gif

Fig. 1

41512_2023_158_Article_IEq2.gif