Combined Predictive Performance Of Age And Neutrophilic Percentage On Admission For Severe Novel Coronavirus Disease 2019

Background Novel coronavirus disease 2019 (COVID-19) poses a huge threat to the global public health. This study aimed to identify predictive indicators of severe COVID-19.Methods We retrospectively collected clinical data on hospital admission of all patients with severe COVID-19 and a control cohort (1:1) of gender- and hospital-matched patients with mild disease from 13 designated hospitals in the Hebei Province between 22 January and 15 April 2020.Results A total of 104 patients (52 with severe COVID-19 and 52 with mild disease) were included. Only age, fever, duration from symptom onset to confirmation, respiratory rate, percutaneous oxygen saturation (SpO(2)) and neutrophilic percentage were independent predictors of severe COVID-19. Age and neutrophilic percentage performed best in predicting severe COVID-19, followed by SpO(2). 'Age + neutrophilic percentage' (the sum of age and neutrophilic percentage) (area under the curve [AUC] 0.900, 95% confidence interval [CI] 0.825-0.950, P < .001) and 'age and neutrophilic percentage' (the prediction probability of age and neutrophilic percentage for severe type obtained by logistic regression analysis) (AUC 0.899, 95% CI 0.824-0.949, P < .001) had excellent predictive performance for severe type. The optimal cut-off for 'age + neutrophilic percentage' was >119.1 (sensitivity, 86.5%; specificity, 84.6%; Youden index, 0.712).Conclusion The combination of age and neutrophil percentage could effectively predict severe COVID-19. The sum of age and neutrophil percentage was recommended for clinical application because of its excellent predictive value and practicability.Trail registration China Clinical Trial Registry, number ChiCTR2000030226. Registered 26 February 2020-Retrospectively registered,