Prior immunosuppressive therapy is associated with mortality in COVID-19 patients: A retrospective study of 835 patients.

Though it is widely believed that chronic immunosuppressive medications increase the severity of coronavirus disease 2019 (COVID-19) illness, there is little data to support this. We performed a retrospective study of COVID-19 positive patients diagnosed at a single academic medical center between March 10, 2020 and October 13, 2020. A total of 835 patients diagnosed with COVID-19 by polymerase chain reaction were included (median age 64 years; 52% female). Of these, 46 (5.5%) had a prescription for an immunosuppressive therapy before diagnosis, most commonly oral steroids (20, 43%), mycophenolate (12, 26%), or tacrolimus (11, 24%). Patients on immunosuppressive therapy with COVID-19 had increased mortality (30% vs. 17%, p = 0.036; odds ratio 2.1, 95% confidence interval 1.11-4.04), which remained significant (p = 0.040) after performing multivariate logistic regression controlling for gender, age, race, and comorbidity status. Laboratory markers of inflammation were uniformly elevated in both patients on or not on immunosuppressive therapies who died, but lymphocytes and neutrophils were decreased in both COVID-19 patients on immunosuppressive therapies who died and who remained alive. These findings demonstrate that COVID-19 disease is more severe in patients taking prior immunosuppressive medications. This finding emphasizes the need for aggressive monitoring and supportive care for immunosuppressed patients who are diagnosed with COVID-19.

Unbiased identification of clinical characteristics predictive of COVID-19 severity.

There is currently limited clinical ability to identify COVID-19 patients at risk for severe outcomes. To unbiasedly identify metrics associated with severe outcomes in COVID-19 patients, we conducted a retrospective study of 835 COVID-19 positive patients at a single academic medical center between March 10, 2020 and October 13, 2020. As of December 1, 2020, 656 (79%) patients required hospitalization and 149 (18%) died. Unbiased comparisons of all clinical characteristics and mortality revealed that abnormal pH (OR 8.54, 95% CI 5.34-13.6), abnormal creatinine (OR 6.94, 95% CI 4.22-11.4), and abnormal PTT (OR 4.78, 95% CI 3.11-7.33) were most significantly associated with mortality. Correlation with ordinal severity scores confirmed these associations, in addition to associations between respiratory rate (Spearman's rho  = -0.56), absolute neutrophil count (Spearman's rho  = -0.5), and C-reactive protein (Spearman's rho  =  0.59) with disease severity. Unsupervised principal component analysis and machine learning model classification of patient demographics, laboratory results, medications, comorbidities, signs and symptoms, and vitals are capable of separating patients on the basis of COVID-19 mortality (AUC 0.82). This retrospective analysis identifies laboratory and clinical metrics most relevant to predict COVID-19 severity.