Jiajun Luo, Johnny Powell, Sage Ross, Julie Johnson, Christopher O. Olopade, Jayant Pinto, Karen Kim, Habibul Ahsan, Briseis Aschebrook-Kilfoy
{"title":"Evaluating the impact of sickle cell disease on COVID-19 susceptibility and severity: a retrospective cohort study based on electronic health record","authors":"Jiajun Luo, Johnny Powell, Sage Ross, Julie Johnson, Christopher O. Olopade, Jayant Pinto, Karen Kim, Habibul Ahsan, Briseis Aschebrook-Kilfoy","doi":"10.3389/fepid.2023.1241645","DOIUrl":null,"url":null,"abstract":"Background Sickle cell trait/disease (SCT/SCD) are enriched among Black people and associated with various comorbidities. The overrepresentation of these characteristics prevents traditional regression approach obtaining convincing evidence for the independent effect of SCT/SCD on other health outcomes. This study aims to investigate the association between SCT/SCD and COVID-19-related outcomes using causal inference approaches that balance the covariate. Methods We leveraged electronic health record (EHR) data from the University of Chicago Medicine between March 2020 and December 2021. Demographic characteristics were retrieved. Medical conditions were identified using ICD-10 codes. Five approaches, including two traditional regression approaches (unadjusted and adjusted) and three causal inference approaches [covariate balancing propensity score (CBPS) matching, CBPS weighting, and CBPS adjustment], were employed. Results A total of 112,334 patients were included in the study, among which 504 had SCT and 388 SCD. Patients with SCT/SCD were more likely to be non-Hispanic Black people, younger, female, non-smokers, and had a diagnosis of diabetes, heart failure, asthma, and cerebral infarction. Causal inference approaches achieved a balanced distribution of these covariates while traditional approaches failed. Across these approaches, SCD was consistently associated with COVID-19-related pneumonia (odds ratios (OR) estimates, 3.23 (95% CI: 2.13–4.89) to 2.57 (95% CI: 1.10–6.00)) and pain (OR estimates, 6.51 (95% CI: 4.68–9.06) to 2.47 (95% CI: 1.35–4.49)). While CBPS matching suggested an association between SCD and COVID-19-related acute respiratory distress syndrome (OR = 2.01, 95% CI: 0.97–4.17), this association was significant in other approaches (OR estimates, 2.96 (95% CI: 1.69–5.18) to 2.50 (95% CI: 1.43–4.37)). No association was observed between SCT and COVID-19-related outcomes in causal inference approaches. Conclusion Using causal inference approaches, we provide comprehensive evidence for the link between SCT/SCD and COVID-19-related outcomes.","PeriodicalId":73083,"journal":{"name":"Frontiers in epidemiology","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in epidemiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/fepid.2023.1241645","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Background Sickle cell trait/disease (SCT/SCD) are enriched among Black people and associated with various comorbidities. The overrepresentation of these characteristics prevents traditional regression approach obtaining convincing evidence for the independent effect of SCT/SCD on other health outcomes. This study aims to investigate the association between SCT/SCD and COVID-19-related outcomes using causal inference approaches that balance the covariate. Methods We leveraged electronic health record (EHR) data from the University of Chicago Medicine between March 2020 and December 2021. Demographic characteristics were retrieved. Medical conditions were identified using ICD-10 codes. Five approaches, including two traditional regression approaches (unadjusted and adjusted) and three causal inference approaches [covariate balancing propensity score (CBPS) matching, CBPS weighting, and CBPS adjustment], were employed. Results A total of 112,334 patients were included in the study, among which 504 had SCT and 388 SCD. Patients with SCT/SCD were more likely to be non-Hispanic Black people, younger, female, non-smokers, and had a diagnosis of diabetes, heart failure, asthma, and cerebral infarction. Causal inference approaches achieved a balanced distribution of these covariates while traditional approaches failed. Across these approaches, SCD was consistently associated with COVID-19-related pneumonia (odds ratios (OR) estimates, 3.23 (95% CI: 2.13–4.89) to 2.57 (95% CI: 1.10–6.00)) and pain (OR estimates, 6.51 (95% CI: 4.68–9.06) to 2.47 (95% CI: 1.35–4.49)). While CBPS matching suggested an association between SCD and COVID-19-related acute respiratory distress syndrome (OR = 2.01, 95% CI: 0.97–4.17), this association was significant in other approaches (OR estimates, 2.96 (95% CI: 1.69–5.18) to 2.50 (95% CI: 1.43–4.37)). No association was observed between SCT and COVID-19-related outcomes in causal inference approaches. Conclusion Using causal inference approaches, we provide comprehensive evidence for the link between SCT/SCD and COVID-19-related outcomes.