Introduction: Participant retention is important to maintaining statistical power, minimizing bias, and preventing scientific error in Alzheimer disease and related dementias research. Methods: We surveyed representative investigators from NIH-funded Alzheimer’s Disease Research Centers (ADRC), querying their use of retention tactics across 12 strategies. We compared survey results to data from the National Alzheimer’s Coordinating Center for each center. We used a generalized estimating equation with independent working covariance model and empirical standard errors to assess relationships between survey results and rates of retention, controlling for participant characteristics. Results: Twenty-five (83%) responding ADRCs employed an average 42 (SD=7) retention tactics. In a multivariable model that accounted for participant characteristics, the number of retention tactics used by a center was associated with participant retention (odds ratio=1.68, 95% confidence interval: 1.42, 1.98; P<0.001 for the middle compared with the lowest tertile survey scores; odds ratio=1.59, 95% confidence interval: 1.30, 1.94; P<0.001 for the highest compared with the lowest tertile survey scores) at the first follow-up visit. Participant characteristics such as normal cognition diagnosis, older age, higher education, and Caucasian race were also associated with higher retention. Conclusions: Retention in clinical research is more likely to be achieved by employing a variety of tactics.

This cohort study examines trends in medication use among patients hospitalized for COVID-19–related treatment in a large US university health care system from the start of stay-at-home orders in March 2020 throughout the rest of the year.

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Background: Understanding medication use patterns for patients with COVID-19 will provide needed insight into the evolution of COVID-19 treatment over the course of the SARS-CoV-2 pandemic and aid clinical management considerations. Objectives: To systematically determine most frequently used medications among COVID-19 patients overall and by hospitalization status. Secondary objective was use measurement of medications considered potential therapeutic options. Methods: Retrospective cohort study was performed using data from the University of California COVID Research Data Set (UC CORDS) patients between March 10, 2020, and December 31, 2020. Main outcomes were percentages of patients prescribed medications, overall, by age group, and by comorbidity based on hospitalization status for COVID-19 patients. Use percentage by month of COVID-19 diagnosis was measured. Cumulative count of potential therapeutic options was measured over time. Results: Dataset included 22 896 unique patients with COVID-19 (mean [SD] age, 42.4 [20.4] years; 12 154 [53%] women). Most frequently used medications in patients overall were acetaminophen (21.2%), albuterol (14.9%), ondansetron (13.9%), and enoxaparin (10.8%). Dexamethasone use increased from fewer than 50 total hospitalized patients through April who had received the medication, to more than 500 patients by mid-August. Cumulative count of enoxaparin users was the largest throughout the study period. Conclusion and Relevance: In this retrospective cohort study, across age and comorbidity groups, predominant utilization was for supportive care therapy. Dexamethasone and remdesivir experienced large increases in use. Conversely, hydroxychloroquine and azithromycin use markedly dropped. Medication utilization rapidly shifted toward more evidence-concordant treatment of patients with COVID-19 as rigorous study findings emerged.

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