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Factors Associated With Enrollment into Inpatient Coronavirus Disease 2019 Randomized Controlled Trials: A Cross-sectional Analysis

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Abstract Background Clinical trials for coronavirus disease 2019 (COVID-19) have struggled to achieve diverse patient enrollment, despite underrepresented groups bearing the largest burden of the disease and, presumably, being most… Click to show full abstract

Abstract Background Clinical trials for coronavirus disease 2019 (COVID-19) have struggled to achieve diverse patient enrollment, despite underrepresented groups bearing the largest burden of the disease and, presumably, being most in need of the treatments under investigation. Methods To assess the willingness of patients to enroll into inpatient COVID-19 clinical trials when invited, we conducted a cross-sectional analysis of adults hospitalized with COVID-19 who were approached regarding enrollment. Associations between patient and temporal factors and enrollment were assessed by multivariable logistic regression analysis. Results A total of 926 patients were included in this analysis. Overall, Hispanic/Latinx ethnicity was associated with a nearly half-fold decrease in the likelihood to enroll (adjusted odds ratio [aOR], 0.60 [95% confidence interval {CI}, .41–.88]). Greater baseline disease severity (aOR, 1.09 [95% CI, 1.02–1.17]), age 40–64 years (aOR, 1.83 [95% CI, 1.03–3.25]), and age ≥65 years (aOR, 1.92 [95% CI, 1.08–3.42]) were each independently associated with higher likelihood to enroll. Over the course of the pandemic, patients were less likely to enroll during the summer 2021 wave in COVID-19–related hospitalizations (aOR, 0.14 [95% CI, .10–.19]) compared with patients from the first wave in winter 2020. Conclusions The decision to enroll into clinical trials is multifactorial. Amid a pandemic disproportionately affecting vulnerable groups, Hispanic/Latinx patients were less likely to participate when invited, whereas older adults were more likely. Future recruitment strategies must consider the nuanced perceptions and needs of diverse patient populations to ensure equitable trial participation that advances the quality of healthcare for all.

Keywords: coronavirus disease; sectional analysis; disease; cross sectional; analysis; disease 2019

Journal Title: Open Forum Infectious Diseases
Year Published: 2023

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