Development and validation of a laboratory risk score for the early prediction of COVID-19 severity and in-hospital mortality

Bennouar, Salam; Bachir Cherif, Abdelghani; Kessira, Amel; Bennouar, Djamel-Eddine; Abdi, Samia

BACKGROUND AND AIMS: Coronavirus Disease 2019 is characterized by a spectrum of clinical severity. This study aimed to develop a laboratory score system to identify high-risk individuals, to validate this score in a separate cohort, and to test its accuracy in the prediction of in-hospital mortality. METHODS: In this cohort study, biological data from 330 SARS-CoV-2 infected patients were used to develop a risk score to predict progression toward severity. In a second stage, data from 240 additional COVID-19 patients were used to validate this score. Accuracy of the score was measured by the area under the receiver operating characteristic curve (AUC). RESULTS: In the development cohort, a step-wise decrease in the average survival duration was noted with the increment of the risk score (p(ANOVA) < 0.0001). A similar trend was confirmed when analyzing this association in the validation cohort (p < 0.0001). The AUC was 0.74 [0.66–0.82] and 0.90 [0.87–0.94], p < 0.0001, respectively for severity and mortality prediction. CONCLUSION: This study provides a useful risk score based on biological routine parameters assessed at the time of admission, which has proven its effectiveness in predicting both severity and short-term mortality of COVID-19. Improved predictive scores may be generated by including other clinical and radiological features.