Jiajun Luo, Johnny Powell, Sage Ross, Julie Johnson, Christopher O. Olopade, Jayant Pinto, Karen Kim, Habibul Ahsan, Briseis Aschebrook-Kilfoy
{"title":"评估镰状细胞病对COVID-19易感性和严重程度的影响:基于电子健康记录的回顾性队列研究","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":"{\"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}","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}
Evaluating the impact of sickle cell disease on COVID-19 susceptibility and severity: a retrospective cohort study based on electronic health record
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.