A predictive score for severity in patients with confirmed dengue fever in a tertiary care hospital in Kerala, India

Abstract

ABSTRACT Background The study aimed to identify predictors of severe dengue during the 2017 epidemic and to develop and validate a simple predictive score for severity. Methods A retrospective analytical study was conducted using clinical and laboratory data from adult dengue patients with a confirmed microbiological diagnosis. The study included patients who presented to a tertiary care centre in Kerala, India, during the febrile phase (≤4 d) between June 2017 and February 2019. Using appropriate statistical tests, we derived predictors of severe disease and computed a risk score model. Results Of the 153 patients (mean age 50±17 y; 64% males), 31 (20%) had severe dengue and 4 (3%) died. Petechial lesions, hypoalbuminemia (<3.5 g/dl), elevated alanine aminotransferase (>40 IU/l) and urea >40 IU/l were significant predictors. Our scoring system (cut-off: 2) showed excellent performance, with an area under the receiver operating characteristics curve of 0.9741, sensitivity of 100%, specificity of 96% and accuracy of 98%. The risk score was secondarily validated on 48 patients hospitalized from March 2019 to June 2019. Conclusion Our scoring system is easy to implement and will help primary healthcare practitioners in promptly identifying severe dengue cases upon hospital presentation.