Evidence map›Paper›PMID 38455889›Full record

ArticleFrontiers in epidemiology2023

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

Open access · diamondAbstract read
In one paragraph

Article in Frontiers in epidemiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 62% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 2 institutions in 1 country.

Jiajun LuoDepartment of Public Health Sciences, University of Chicago, Chicago, IL, United States.
Johnny PowellInstitute for Population and Precision Health, University of Chicago, Chicago, IL, United States.
Sage RossInstitute for Population and Precision Health, University of Chicago, Chicago, IL, United States.
Julie JohnsonCenter for Research Informatics, University of Chicago, Chicago, IL, United States.
Christopher O OlopadeDepartment of Medicine, University of Chicago, Chicago, IL, United States.
Jayant PintoDepartment of Surgery, University of Chicago, Chicago, IL, United States.
Karen KimComprehensive Cancer Center, University of Chicago, Chicago, IL, United States.
Habibul AhsanDepartment of Public Health Sciences, University of Chicago, Chicago, IL, United States.
Briseis Aschebrook-KilfoyDepartment of Public Health Sciences, University of Chicago, Chicago, IL, United States.
University of Chicago · USChicago Department of Public Health · US

Funding

Summer Program to Increase Heart, Lung, and Blood Biomedical ResearchR25HL096383 · NHLBI · UNIVERSITY OF CHICAGO · PI CHRISTOPHER O OLOPADE, William F Parker · 2009 to 2026
$2.1M
NHLBI NIH HHS R25 HL096383
6 · The paper itself

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.

Indexed as

ARDScausal inferencepneumoniapropensity scoresickle cell diseasesickle cell trait

Identifiers

PMID38455889
PMCPMC10910923
OpenAlexW4386714490

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.