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

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.