 Statistical methods The performance of prediction models and clinicians will be evaluated and compared in terms of discrimination, calibration and reclassification. First, the scores obtained from the prediction models will be used to assign patients to green, yellow, orange or red categories. Discrimination will then be assessed by calculating the area under the receiver operating characteristics curve for both the original scores and the color groupings based on the scores. Calibration will be assessed by calculating the mortality in each color group, assuming a linear association between increased severity and higher mortality. Finally, reclassification will be assessed by comparing what patients end up in which group, depending on whether the grouping is based on prediction models or clinicians. Only patients with complete data will be analysed. All analyses will be conducted using the R statistical environment, using standard 95 confidence intervals and a 5 significance level. 