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Dear Editor, While studies have established risk factors for clinical deterioration in coronavirus disease 2019 (COVID-19) patients [1, 2], or attempted to identify phenotypes based on experts opinion [3], identifying sub-phenotypes based on more easily obtained data could help identify patients at highest risk of clinical deterioration and refine inclusion of more homogeneous subpopulations in clinical trials. We here applied an unsupervised, multivariate clustering algorithm using easy-to-obtain clinical variables to identify COVID-19 sub-phenotypes and examined the association with clinical deterioration. This retrospective cohort study was performed among adult COVID-19-positive patients (using real-time reverse transcriptase-polymerase chain reaction assay) with a hospital visit between February 28 and March 26, 2020, at eight teaching hospitals of the Assistance Publique-Hôpitaux de Paris. The Institutional Review Board (IRB) of Ile-de-France VII approved the study and waived the need for informed consent from individual patients (DC 2009/CO-15-000). We selected 22 candidate variables for the clustering analysis including demographic information among 608 patients with available candidate variables, disease history, major clinical symptoms, and medications on the day of positive diagnostic, which represents the final cohort (Supplementary file). We