A machine learning-based risk score for prediction of mechanical ventilation in children with dengue shock syndrome: A retrospective cohort study

Nguyen Tat Thanh, Vo Thanh Luan, Do Chau Viet, Trinh Huu Tung and Vu Thien

PLOS ONE, 2024, vol. 19, issue 12, 1-16

Abstract: Background: Patients with severe dengue who develop severe respiratory failure requiring mechanical ventilation (MV) support have significantly increased mortality rates. This study aimed to develop a robust machine learning-based risk score to predict the need for MV in children with dengue shock syndrome (DSS) who developed acute respiratory failure. Methods: This single-institution retrospective study was conducted at a tertiary pediatric hospital in Vietnam between 2013 and 2022. The primary outcome was severe respiratory failure requiring MV in the children with DSS. Key covariables were predetermined by the LASSO method, literature review, and clinical expertise, including age (

Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0315281

DOI: 10.1371/journal.pone.0315281

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