Publication: APPLICATION OF SUPERVISED MACHINE LEARNING ON PREDICTION OF DEATH AMONG SEVERE DENGUE CASES
Date
2023
Authors
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Journal ISSN
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Publisher
International Medical University
Abstract
Although various predictive models exist for dengue, only four models exist for
predicting mortality in severe dengue cases. However, none of the existing models
consider the timing of events during model development. To address this gap, a
multicentre retrospective cohort study was conducted to create a predictive model for
deaths in severe dengue. The study aimed to provide a more comprehensive and
effective approach to predicting mortality rates in such cases.
The study focused on patients diagnosed with severe dengue based on the
classification provided by WHO 2009 and gathered a total of 18 predictor variables
comprising demographic, clinical, and laboratory data. We used LASSO for variable
selection and model-building and conducted a ten-fold cross-validation for internal
validation. The analysis was conducted on a cohort of 786 severe dengue cases, out
of which 35 (4%) resulted in fatalities. Furthermore, 575 out of 786 severe dengue
patients (73.2%) were diagnosed with severe dengue during the febrile phase.
LASSO model identified Body Mass Index (BMI), vomiting, third space fluid
accumulation, respiratory rate, white cell count, platelet count, AST, serum albumin,
bicarbonate, and lactate at diagnosis of severe dengue as the predictor variables. The
LASSO model's accuracy was 0.96 (95%CI: 0.91 to 0.98), with low sensitivity of
0.29 (95%CI: 0.15 – 0.46), high specificity of 1.00 (95%CI: 0.99 – 1.00).
We have developed a high-performance dengue mortality prediction model based on
timing of the event, clinical and laboratory data. We will deploy an open-access web
tool for local validation and to stratify severe dengue patients. However, further investigations are required as 2/3 of the study population were diagnosed with severe
dengue fever during the febrile phase, as this contradicts the current guideline.
Description
Keywords
Dengue, Machine Learning, Mortality, Cohort Studies, Guideline