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Reviews of "Risk Factors Associated with Post-Acute Sequelae of SARS-CoV-2 in an EHR Cohort: A National COVID Cohort Collaborative (N3C) Analysis as Part of the NIH RECOVER Program"

Reviewers: D Nash (New York School of Public Health) | πŸ“’πŸ“’πŸ“’ ◻️◻️ β€’ P Kohler (Kantonsspital St Gallen) | πŸ“—πŸ“—πŸ“—πŸ“—β—»οΈ

Published onOct 11, 2022
Reviews of "Risk Factors Associated with Post-Acute Sequelae of SARS-CoV-2 in an EHR Cohort: A National COVID Cohort Collaborative (N3C) Analysis as Part of the NIH RECOVER Program"
key-enterThis Pub is a Review of
Risk Factors Associated with Post-Acute Sequelae of SARS-CoV-2 in an EHR Cohort: A National COVID Cohort Collaborative (N3C) Analysis as part of the NIH RECOVER program
Description

ABSTRACTBackgroundMore than one-third of individuals experience post-acute sequelae of SARS-CoV-2 infection (PASC, which includes long-COVID).ObjectiveTo identify risk factors associated with PASC/long-COVID.DesignRetrospective case-control study.Setting31 health systems in the United States from the National COVID Cohort Collaborative (N3C).Patients8,325 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.MeasurementsRisk factors included demographics, comorbidities, and 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 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.KEY POINTSQuestionWhat risk factors are associated with post-acute sequelae of SARS-CoV-2 (PASC) in the National COVID Cohort Collaborative (N3C) EHR Cohort?FindingsThis national study identified important risk factors for PASC such as middle age, severe COVID-19 disease, specific comorbidities, and the number of physicians per capita.MeaningClinicians can use these risk factors to identify patients at high risk for PASC while they are still in the acute phase of their infection and also to support targeted enrollment in clinical trials for preventing or treating PASC.

To read the original manuscript, click the link above.

Summary of Reviews: This preprint identifies risk factors for long-COVID based on a case-control study using EHR data from 31 US Health Centers. Reviewers find this study to be potentially informative to reliable and highlight the study’s limited generalizability and potential introduction of bias in the control selection process.

Reviewer 1 (Denis N…) | πŸ“’πŸ“’πŸ“’ ◻️◻️

Reviewer 2 (Philipp K…) | πŸ“—πŸ“—πŸ“—πŸ“—β—»οΈ

RR:C19 Strength of Evidence Scale Key

πŸ“• ◻️◻️◻️◻️ = Misleading

πŸ“™πŸ“™ ◻️◻️◻️ = Not Informative

πŸ“’πŸ“’πŸ“’ ◻️◻️ = Potentially Informative

πŸ“—πŸ“—πŸ“—πŸ“—β—»οΈ = Reliable

πŸ“˜πŸ“˜πŸ“˜πŸ“˜πŸ“˜ = Strong

To read the reviews, click the links below.Β 


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