ABSTRACT
The coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), can result in a hyperinflammatory state, leading to acute respiratory distress syndrome (ARDS), myocardial injury, and thrombotic complications, among other sequelae. Statins, which are known to have anti-inflammatory and antithrombotic properties, have been studied in the setting of other viral infections and ARDS, but their benefit has not been assessed in COVID-19. Thus, we sought to determine whether antecedent statin use is associated with lower in-hospital mortality in patients hospitalized for COVID-19. This is a retrospective analysis of patients admitted with COVID-19 from February 1 st through May 12 th , 2020 with study period ending on June 11 th , 2020. Antecedent statin use was assessed using medication information available in the electronic medical record. We constructed a multivariable logistic regression model to predict the propensity of receiving statins, adjusting for baseline socio-demographic and clinical characteristics, and outpatient medications. The primary endpoint included in-hospital mortality within 30 days. A total of 2626 patients were admitted during the study period, of whom 951 (36.2%) were antecedent statin users. Among 1296 patients (648 statin users, 648 non-statin users) identified with 1:1 propensity-score matching, demographic, baseline, and outpatient medication information were well balanced. Statin use was significantly associated with lower odds of the primary endpoint in the propensity-matched cohort (OR 0.48, 95% CI 0.36 a" 0.64, p<0.001). We conclude that antecedent statin use in patients hospitalized with COVID-19 was associated with lower inpatient mortality. Randomized clinical trials evaluating the utility of statin therapy in patients with COVID-19 are needed.
ABSTRACT
Small, liberal arts colleges are known to have close campus communities with strong relationships between professors and students. In this paper we consider the person-to-group and related person-to-person network at one of these institutions using student and faculty data from Fall 2019 courses, athletics ensembles, housing, and student organizations. This data is used as a baseline to model the Fall 2020 semester with the college's COVID-19 mitigation strategies: cancel or virtualize some groups, split the semester into two independent sessions, and separate larger courses into hybrid meetings. Network analysis shows that students and faculty had at most 4 degrees of separation in Fall 2019, student organizations can have a large impact on campus connectedness, all semester modifications implemented in Fall 2020 can reduce connectedness, and the largest reduction was seen by splitting the semester into two sessions.