Diagnostic utility of the Covichem score in predicting COVID-19 disease

BACKGROUND: Identifying which patients with COVİD-19 have a high risk of severe illness is essential to optimizing management and resource utilization strategies. OBJECTIVES: The aim of this study was to externally validate the diagnostic utility of the Covichem score for predicting COVID-19 disease severity, and secondarily to evaluate its utility in predicting intensive care unit (ICU) admission, and in-hospital mortality. METHODS: All consecutive COVID-19 patients who presented to the emergency department (ED) were included, and patients' demographic data, comorbidities, vital signs, oxygen requirement, and laboratory results were recorded. We calculated patients' Covichem scores and estimates (using a threshold of 0.5) and evaluated the utility of the Covichem score for predicting disease severity, ICU admission, and mortality. RESULTS: The median Covichem score was significantly higher for patients with severe illness (Covichem score: 0.170, IQR: 0.298, n = 300 vs. Covichem score: 0.026, IQR: 0.065, n: 191; p < 0.001). Based on their Covichem scores, 12.4% (61/491) of the patients were predicted to experience severe illness (threshold: 0.5), the accuracy of the Covichem score was poor, as the area under curve (AUC) was 48.5% (18.1% sensitivity and 93.8% specificity). When we calculated a new ideal threshold, the AUC reached 82%, but the sensitivity was 79.9% and the specificity was 71.2%. CONCLUSION: In this external validation of the Covichem score, we found that it performed worse than in the original derivation and validation study, even with the assistance of a new cutoff.