학술논문

Pediatric Sepsis Phenotyping Using Vital Sign Trajectories
Document Type
Conference
Source
2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) Bioinformatics and Biomedicine (BIBM), 2023 IEEE International Conference on. :4297-4303 Dec, 2023
Subject
Bioengineering
Computing and Processing
Engineering Profession
Robotics and Control Systems
Signal Processing and Analysis
Analytical models
Hospitals
Biological systems
Sepsis
Hazards
Blood pressure
Trajectory
Machine Learning
Time-series Analysis
Pediatrics
Mortality Prediction
Language
ISSN
2156-1133
Abstract
Sepsis can be life-threatening, which highlights the need to understand the condition's diverse phenotypes to enhance treatment effectiveness. Sepsis phenotypes are derived from 12-hour vital sign trajectories of children (N=12,824) with multiple organ dysfunction syndrome from 13 U.S. hospitals. Survival analysis of the two subgroups produced by hierarchical clustering (HAC) on pairwise trajectory similarity matrix from dynamic time warping (DTW) showed a hazards ratio of 4.7 for 30-day mortality, which was better than the stratification of subgroups from group-based trajectory modeling. The higher mortality subgroup from HAC on DTW displayed higher blood pressure and pulse but lower temperature, in addition to acidosis. This comprehensive analysis of phenotypes can greatly aid in early risk evaluation, tailored treatment approaches, and improved outcomes for pediatric sepsis patients.