Evaluating the impact of sickle cell disease on COVID-19 susceptibility and severity: a retrospective cohort study based on electronic health record

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

Evaluating the impact of sickle cell disease on COVID-19 susceptibility and severity: a retrospective cohort study based on electronic health record

Front Epidemiol. 2023 Sep 12:3:1241645. doi: 10.3389/fepid.2023.1241645. eCollection 2023.

Authors

Jiajun Luo^{1

2

3}, Johnny Powell², Sage Ross², Julie Johnson⁴, Christopher O Olopade⁵, Jayant Pinto⁶, Karen Kim^{3

5}, Habibul Ahsan^{1

2

3}, Briseis Aschebrook-Kilfoy^{1

2

3}

Affiliations

¹ Department of Public Health Sciences, University of Chicago, Chicago, IL, United States.
² Institute for Population and Precision Health, University of Chicago, Chicago, IL, United States.
³ Comprehensive Cancer Center, University of Chicago, Chicago, IL, United States.
⁴ Center for Research Informatics, University of Chicago, Chicago, IL, United States.
⁵ Department of Medicine, University of Chicago, Chicago, IL, United States.
⁶ Department of Surgery, University of Chicago, Chicago, IL, United States.

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.

Keywords: ARDS; causal inference; pneumonia; propensity score; sickle cell disease; sickle cell trait.