Development of a clinical risk score to predict death in patients with COVID-19

Abstract

Objective: To build a clinical risk score to aid risk stratification among hospitalised COVID-19 patients.

Methods: The score was built using data of 417 consecutive COVID-19 in patients from Kuwait. Risk factors for COVID-19 mortality were identified by multivariate logistic regressions and assigned weighted points proportional to their beta coefficient values. A final score was obtained for each patient and tested against death to calculate an Receiver-operating characteristic curve. Youden's index was used to determine the cut-off value for death prediction risk. The score was internally validated using another COVID-19 Kuwaiti-patient cohort of 923 patients. External validation was carried out using 178 patients from the Italian CoViDiab cohort.

Results: Deceased COVID-19 patients more likely showed glucose levels of 7.0-11.1 mmol/L (34.4%, p < 0.0001) or >11.1 mmol/L (44.3%, p < 0.0001), and comorbidities such as diabetes and hypertension compared to those who survived (39.3% vs. 20.4% [p = 0.0027] and 45.9% vs. 26.6% [p = 0.0036], respectively). The risk factors for in-hospital mortality in the final model were gender, nationality, asthma, and glucose categories (<5.0, 5.5-6.9, 7.0-11.1, or 11.1 > mmol/L). A score of ≥5.5 points predicted death with 75% sensitivity and 86.3% specificity (area under the curve (AUC) 0.901). Internal validation resulted in an AUC of 0.826, and external validation showed an AUC of 0.687.

Conclusion: This clinical risk score was built with easy-to-collect data and had good probability of predicting in-hospital death among COVID-19 patients.

Keywords: COVID-19; clinical risk score; comorbidities; glucose control; hyperglycemia; intensive care.