Synergistic impact of Gram-negative bacterial co-infection on invasive pulmonary aspergillosis in non-neutropenic patients: a machine learning-based risk stratification approach

Gram-negative bacterial co-infection synergistically amplifies IPA risk in non-neutropenic patients. The ensemble ML model integrating seven pragmatic predictors provides accurate, interpretable, and clinically actionable stratification, enabling precision prophylaxis and early antifungal intervention. Prospective multicenter validation is warranted before clinical implementation.

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Publication Details

Journal
Minerva Anestesiologica
Published
2026-02-01
DOI
https://doi.org/10.23736/s0375-9393.25.19541-2
Primary Topic
Antifungal resistance and susceptibility
Type
article
Field-Weighted Citation Impact
0.00
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article

Synergistic impact of Gram-negative bacterial co-infection on invasive pulmonary aspergillosis in non-neutropenic patients: a machine learning-based risk stratification approach

Hui Bai, W. Chen, Jinyuan Zhu, Xiaoya Zhang et al.
Minerva Anestesiologica
Antifungal resistance and susceptibility
article

Synergistic impact of Gram-negative bacterial co-infection on invasive pulmonary aspergillosis in non-neutropenic patients: a machine learning-based risk stratification approach

Hui Bai, W. Chen, Jinyuan Zhu, Xiaoya Zhang, Yonghong Yang, Furui Liu, Ying YANG
article en

Abstract

Gram-negative bacterial co-infection synergistically amplifies IPA risk in non-neutropenic patients. The ensemble ML model integrating seven pragmatic predictors provides accurate, interpretable, and clinically actionable stratification, enabling precision prophylaxis and early antifungal intervention. Prospective multicenter validation is warranted before clinical implementation.

Minerva Anestesiologica
Ningxia Medical University (CN), Ningxia Medical University General Hospital (CN)
Openalex Percentile: Top 64%
Antifungal resistance and susceptibility
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