A new simple score to predict mortality of COVID-19 in the emergency department

Abstract

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic is one of the greatest challenges facing global medical research. The availability of a clinical score that can predict mortality risk at the time of diagnosis could be a valuable tool in the hands of emergency physicians to make clinical decisions. Our study is designed to evaluate clinical and laboratory endpoints associated with mortality and to determine a prognostic score based on clinical and laboratory variables. We retrospectively enrolled 367 patients diagnosed with coronavirus disease 19 (COVID-19) in our emergency department (ED). We evaluated their mortality 60 days after diagnosis. Symptoms, demographic data, concomitant diseases, and various laboratory parameters were obtained from all patients. Variables related to death were assessed using multiple logistic regression analysis. From these, we created a score called ANCOC (Age, blood urea Nitrogen, C-reactive protein, Oxygen saturation, Comorbidities). The area under the receiver operating characteristic (ROC) curve was calculated for the ANCOC and for the 4C score. The 4C score has been described and validated in previous works and can predict mortality in COVID-19 patients. We compared the 2 scores and analysed sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for 60-day mortality for the ANCOC score. The ANCOC and 4C scores accurately predicted death from COVID-19. There were no differences in accuracy between the scores. An ANCOC score <–1 identified patients who will recover with a PPV and sensitivity of 100%, whereas a score ＞3 identified patients at high risk of death. The ANCOC score has very high diagnostic accuracy in predicting the risk of death in patients with COVID-19 diagnosed at ED. The ANCOC score has similar accuracy to the 4C score but is easier to calculate. If validated by external cohorts, this score could be an additional tool in the hands of ED physicians to identify COVID-19 patients at high risk of death.