Clinical subtypes identification and feature recognition of sepsis leukocyte trajectories based on machine learning

Clinical subtypes identification and feature recognition of sepsis leukocyte trajectories based on machine learning

Abstract Sepsis is a highly variable condition, and tracking leukocyte patterns may offer insights for tailored treatment and prognosis. We used the MIMIC-IV database to analyze patients diagnosed with Sepsis-3 within 24 h of ICU admission. Latent class mixed models (LCMM) were applied to leukocyte...

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Bibliographic Details
Main Authors: ShengHui Miao, YiJing Liu, Min Li, Jing Yan
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Scientific Reports
Subjects:
Sepsis
Clinical subtypes
Leukocyte trajectories
Machine learning
Latent class analysis
Online Access:https://doi.org/10.1038/s41598-025-96718-9
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https://doi.org/10.1038/s41598-025-96718-9

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