COVID-19 Research Paper Volume 14, Issue 1 pp 54—72

PRCTC: a machine learning model for prediction of response to corticosteroid therapy in COVID-19 patients


Figure 1. The features were selected by LASSO. (A) showed LASSO variable trace profiles of the ten features. The vertical dashed line shows the best lambda value (0.081) chosen by tenfold cross-validation. (B) showed features with zero coefficient (colored with gray) at lambda = 0.081, was considered less crucial to the patient’s response to corticosteroid therapy and removed by Lasso logistic regression analysis. Features with positive coefficient (colored with red) are regarded as positively associated with response to corticosteroid therapy. Features with negative coefficient (colored with blue) are regarded as negatively associated with response to corticosteroid therapy. Abbreviations: LASSO least absolute shrinkage and selection operator; IL-8 interleukin-8; IL-10 interleukin-10; IL-6 interleukin-6; IL-2R interleukin-2 receptor; IL-1β interleukin-1β; TNF-α tumor necrosis factor α; PCT procalcitonin; CRP C reactive protein.