Fig. 2

Model discrimination and decision curve analysis. a Overall ROC curves for the RF and LR models and the NEWS. We placed two landmarks for a NEW score of 5 and 7, i.e., the recommended trigger thresholds for an urgent and emergency response. We calculated both the pAUC between a false positive rate of 0 and 0.33 (grey area) and the complete AUC. Shaded areas around each point in the ROC curves represent the 95% bootstrap percentile CIs²⁵ (with 1000 bootstrap replications stratified for positive and negative samples). b Hospital-specific pAUCs. The error bars represent the 95% bootstrap percentile CIs²⁵ (with 1000 bootstrap replications stratified for positive and negative samples). P-values, calculated as described in Additional file 1: appendix F.4, are shown for the difference in pAUC between the RF models and NEWS (upper bar), between the RF and LR models (middle bar) and between the LR models and NEWS (lower bar). c Overall decision curve analysis results. The standardized net benefit is plotted over a range of clinically relevant probability thresholds with corresponding odds. The ‘Intervention for all’ line indicates the NB if a (urgent or emergency) response would always be triggered