RESUMEN
BackgroundMaintenance drugs are used to treat chronic conditions. Several classes of maintenance drugs have attracted attention because of their potential to affect susceptibility to and severity of COVID-19. MethodsUsing claims data on 20% random sample of Part D Medicare enrollees from April to December 2020, we identified patients diagnosed with COVID-19. Using a nested case-control design, non-COVID-19 controls were identified by 1:5 matching on age, race, sex, dual-eligibility status and geographical region. We identified usage of angiotensin-converting enzyme inhibitors (ACEI), angiotensin-receptor blockers (ARB), warfarin, direct factor Xa inhibitors, clopidogrel, famotidine and hydroxychloroquine based on Medicare prescription claims data. Using extended Cox regression models with time-varying propensity score adjustment we examined the independent effect of each study drug on contracting COVID-19. For severity of COVID-19, we performed extended Cox regressions on all COVID-19 patients, using COVID-19-related hospitalization and all-cause mortality as outcomes. Covariates included gender, age, race, geographic region, low-income indicator and co-morbidities. To compensate for indication bias related to the use of hydroxychloroquine for the prophylaxis or treatment of COVID-19, we censored patients who only started on hydroxychloroquine in 2020. ResultsUp to December 2020, our sample contained 374,229 Medicare patients over 65 who were diagnosed with COVID-19. Among the COVID-19 patients, 209,208 (55.9%) were on at least one study drug. The three most common study drugs were ACEI 97,872 (26.1%), ARB 83,329 (22.3%) and clopidogrel 38,203 (10.2%). Current users of ACEI, ARB, warfarin, direct factor Xa inhibitor and clopidogrel were associated with reduced risk of getting COVID-19 (3-13%), and reduced risk of dying after a COVID-19 diagnosis (8-19%). Famotidine did not show consistent significant effects. Hydroxychloroquine did not show significant effects after censoring of recent starters. ConclusionsMaintenance use of ACEI, ARB, warfarin, direct factor Xa inhibitor and clopidogrel was associated with reduction in risk of acquiring COVID-19 and dying from it.
RESUMEN
BackgroundGiven the limited supply of two COVID-19 vaccines, it will be important to choose which risk groups to prioritize for vaccination in order to get the most health benefits from that supply. MethodIn order to help decide how to get the maximum health yield from this limited supply, we implemented a logistic regression model to predict COVID-19 death risk by age, race, and sex and did the same to predict COVID-19 case risk. ResultsOur predictive model ranked all demographic groups by COVID-19 death risk. It was highly concentrated in some demographic groups, e.g. 85+ year old Black, Non-Hispanic patients suffered 1,953 deaths per 100,000. If we vaccinated the 17 demographic groups at highest COVID-19 death ranked by our logistic model, it would require only 3.7% of the vaccine supply needed to vaccinate all the United States, and yet prevent 47% of COVID-19 deaths. Nursing home residents had a higher COVID-19 death risk at 5,200 deaths/100,000, more than our highest demographic risk group. Risk of prison residents and health care workers (HCW) were lower than that of our demographic groups with the highest risks. We saw much less concentration of COVID-19 case risk in any demographic groups compared to the high concentration of COVID-19 death in some such groups. We should prioritize vaccinations with the goal of reducing deaths, not cases, while the vaccine supply is low. ConclusionSARS-CoV-2 vaccines protect against severe COVID-19 infection and thus against COVID-19 death per vaccine studies. Allocating at least some of the early vaccine supplies to high risk demographic groups could maximize lives saved. Our model, and the risk estimate it produced, could help states define their vaccine allocation rules.
