Fig. 1

MCP-3/IL-8 scores were correlated with ICU admission and fatal outcomes. a Unsupervised clustering analysis of average baseline-adjusted and log2-transformed fold changes in cytokines in COVID-19 infected patients needing ICU admission, sepsis patients, and patients experiencing CRS after receiving CAR-T cell therapy. The 39 cytokines/chemokines presented overlap in all three sets of data. C-ICU, COVID-19 patients in ICU wards; sepsis, bacterial septicemia patients. b The most significant predictors for ICU admission were identified by random forest modeling. Relative variable importance is illustrated. c LASSO regression identified 10 analytes that contributed to distinguishing ICU patients from non-ICU patients. The coefficients are shown. Red bars and green bars represent cytokines positively and negatively contributing to the lasso regression model, respectively. d Venn diagram results for the random forest and lasso modeling are shown. *chemokines. e Receiver operating characteristic (ROC) curve evaluation of the performance of immune scores in identifying COVID-19 patients needing ICU admission in the internal test set. f Comparison of immune scores between the non-ICU and ICU patients in training and internal test sets. The arrows indicate patients who were transferred to ICU wards during the follow-up period. r, Spearman’s correlation coefficient. g ROC curve evaluation of the performance of immune scores in identifying COVID-19 patients needing ICU admission in the external test set. h Comparison of immune scores between the non-ICU and ICU patients in the external test sets. i Spearman’s correlation analyses of the MCP-3/IL-8 immune score and peak CT value. j Different outcomes (dead and alive) of ICU patients with significant differences in MCP-3/IL-8 immune scores. **P < 0.01; ****P < 0.0001. A U test was used