Dynamic dengue haemorrhagic fever calculators as clinical decision support tools in adult dengue. (15th November 2019)

• Record Type: Journal Article
• Authors: Tan, Ken Wei; Tan, Ben; Thein, Tun L; Leo, Yee-Sin; Lye, David C; Dickens, Borame L; Wong, Joshua Guo Xian; Cook, Alex R
• Is Part Of: Transactions of the Royal Society of Tropical Medicine and Hygiene. Volume 114:Number 1(2020)
• Page Start: 7
• Page End: 15
• Publication Date: 2019-11-15
• Subjects: Clinical Decision Support Tools -- Dengue -- Machine Learning; Tropical medicine -- Periodicals; 616.9883
• DOI: 10.1093/trstmh/trz099
• Languages: English
• ISSNs: 0035-9203

Abstract

Abstract: Background: The objective of this study was to develop multiple prediction tools that calculate the risk of developing dengue haemorrhagic fever. Methods: Training data consisted of 1771 individuals from 2006–2008 admitted with dengue fever whereby 304 developed dengue haemorrhagic fever during hospitalisation. Least absolute shrinkage and selection operator regression was used to construct three types of calculators, static admission calculators and dynamic calculators that predict the risk of developing dengue haemorrhagic fever for a subsequent day (DAily Risk Tomorrow [DART]) or for any future point after a specific day since fever onset (DAily Risk Ever [DARE]). Results: From 119 admission covariates, 35 were in at least one of the calculators, which reported area under the curve (AUC) values of at least 0.72. Addition of person-time data for DART improved AUC to 0.76. DARE calculators displayed a large increase in AUC to 0.79 past day 7 with the inclusion of a strong predictor, maximum temperature on day 6 since onset, indicative of a saddleback fever. Conclusions: All calculators performed well when validated with 2005 data. Addition of daily variables further improved the accuracy. These calculators can be used in tandem to assess the risk of dengue haemorrhagic fever upon admission and updated daily to obtain more precise risk estimates.