Real-time prediction of HFNC treatment failure in acute hypoxemic respiratory failure using machine learning

Real-time prediction of HFNC treatment failure in acute hypoxemic respiratory failure using machine learning

Abstract Accurate and timely prediction of high-flow nasal cannula (HFNC) treatment failure in patients with acute hypoxemic respiratory failure (AHRF) can lower patient mortality. Previous studies have highlighted inconsistencies in the predictive performance of existing indices, such as ROX and mR...

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Bibliographic Details
Main Authors: Xiaojie Li, Chunliang Jiang, Qingyan Xie, Huiquan Wang, Jiameng Xu, Guanjun Liu, Panpan Chang, Guang Zhang
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Series:Scientific Reports
Subjects:
High-flow nasal cannula
Acute hypoxemic respiratory failure
Machine learning methods
Real-time dynamic alert
ROX index
mROX index
Online Access:https://doi.org/10.1038/s41598-025-16061-x
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