Machine learning prediction models for mortality risk in sepsis-associated acute kidney injury: evaluating early versus late CRRT initiation

Machine learning prediction models for mortality risk in sepsis-associated acute kidney injury: evaluating early versus late CRRT initiation

BackgroundSepsis-associated acute kidney injury (S-AKI) has a significant impact on patient survival, with continuous renal replacement therapy (CRRT) being a crucial intervention. However, the optimal timing for CRRT initiation remains controversial.MethodsUsing the MIMIC-IV database for model deve...

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Bibliographic Details
Main Authors: Chuanren Zhuang, Ruomeng Hu, Ke Li, Zhengshuang Liu, Songjie Bai, Sheng Zhang, Xuehuan Wen
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-01-01
Series:Frontiers in Medicine
Subjects:
sepsis
acute kidney injury
continuous renal replacement therapy
machine learning
mortality
CRRT timing
Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2024.1483710/full
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https://www.frontiersin.org/articles/10.3389/fmed.2024.1483710/full

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