A machine learning model for predicting acute respiratory distress syndrome risk in patients with sepsis using circulating immune cell parameters: a retrospective study

A machine learning model for predicting acute respiratory distress syndrome risk in patients with sepsis using circulating immune cell parameters: a retrospective study

Abstract Background Acute respiratory distress syndrome (ARDS) is a severe complication associated with a high mortality rate in patients with sepsis. Early identification of patients with sepsis at high risk of developing ARDS is crucial for timely intervention, optimization of treatment strategies...

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Main Authors: Kaihuan Zhou, Lian Qin, Yin Chen, Hanming Gao, Yicong Ling, Qianqian Qin, Chenglin Mou, Tao Qin, Junyu Lu
Format: Article
Language:English
Published: BMC 2025-04-01
Series:BMC Infectious Diseases
Subjects:
ARDS
Sepsis
Machine learning
Prediction model
MIMIC-IV database
Online Access:https://doi.org/10.1186/s12879-025-10974-8
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https://doi.org/10.1186/s12879-025-10974-8

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