Statistical and machine learning analysis
REGRESSION
Hierarchical consensus clustering based on the most variable cytokines resulted in two clusters of patients with distinct cytokine profiles. A logistic regression model was used to classify patients in CL-1 or CL-2 based on a two-cytokine ratio. This model was tested on the 81 patients with a cytokine characterization in the first three days of hospital admission and the association of both groups with demographic and clinical parameters was assessed. (See SM for details on clustering, logistic regression model and validation procedures).All machine learning (ML) results correspond to two-classes balanced classification problems, tackled through Random Forest models. Input features correspond to cytokine levels, and labels for the two classes are defined according to the patient clinical course, either improving or deteriorating, as measured by laboratory and physical parameters. See SM for details on other ML models, parameter tuning, and validation procedures.