K-Means Clustering Identifies Diverse Clinical Phenotypes in COVID-19 Patients: Implications for Mortality Risks and Remdesivir Impact

The impact of remdesivir on mortality in patients with COVID-19 is still controversial. We aimed to identify clinical phenotype clusters of COVID-19 hospitalized patients with highest benefit from remdesivir use and validate these findings in an external cohort. We included consecutive patients hospitalized between February 2020 and February 2021 for COVID-19. The derivation cohort comprised subjects admitted to Hospital Clinic of Barcelona. The validation cohort included patients from Hospital Universitari Mutua de Terrassa (Terrassa) and Hospital Universitari La Fe (Valencia), all tertiary centers in Spain. We employed K-means clustering to group patients according to reverse transcription polymerase chain reaction (rRT-PCR) cycle threshold (Ct) values and lymphocyte counts at diagnosis, and pre-test symptom duration. The impact of remdesivir on 60-day mortality in each cluster was assessed. A total of 1160 patients (median age 66, interquartile range (IQR) 55–78) were included. We identified five clusters, with mortality rates ranging from 0 to 36.7