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Background Cardiogenic shock (CS) is a heterogeneous syndrome with varied presentations and outcomes. We used a machine learning approach to test the hypothesis that patients with CS have distinct phenotypes at presentation, which are associated with unique clinical profiles and in-hospital mortality. Methods and Results We analyzed data from 1959 patients with CS from 2 international cohorts CSWG (Cardiogenic Shock Working Group Registry) (myocardial infarction [CSWG-MI; n=410] and acute-on-chronic heart failure [CSWG-HF; n=480]) and t