COVID-19: Development and Validation of a New Mortality Risk Score

Objectives: to develop and validate a scoring system to identify which patients with COVID-19 are at high mortality risk upon hospital admission. Methods: a retrospective analysis was performed in two Italian University Hospitals. 388 patients (10.31% deceased) formed the derivation cohort, and 1357 patients (7.68% deceased) formed the external cohort. A multivariable logistic model was used to select variables associated with in-hospital death. Results: seven variables (age, baseline oxygen saturation, haemoglobin value, white blood cell count, percentage of neutrophils, platelet count, and creatinine value) were identified and used to develop the risk score. The model achieved a cumulative AUC value of 0.924 (95%CI: 0.893-0.944). Internal and external validation was successfully performed being the cumulative AUC value of the external cohort 0.808 (95%CI: 0.886-0.828). Conclusions: a risk score based on seven objective variables always available in all patients was obtained; it is easy to calculate; it performs better than all the other scores to evaluate the predictability of dying. This score could help all physicians who treat COVID-19 patients by identifying those patients who require more attention to provide better therapeutic regimens and reduce healthcare costs.