3.2 Predictions of severity
To assess the similarities and differences of patients with different severities, principal component analysis (PCA) was applied to reduce the dimensionality and visualize the patients on a low dimensional space. On the Fig. 2 biplot, a trajectory from ”non-severe” towards ”non-survived” via ”severe & survived” patients was observed. It supports that the blood count parameters and biochemical parameters can potentially indicate the severity of the patient. Interestingly, the heterogeneity within the ”non-survived” group is much larger than ”non-severe” group, suggesting the existence of various reasons for severity. An heatmap of the overview of changes of laboratory results between three groups is presented in Fig. S2.