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New research · Pulmonology & Critical Care
BMC pulmonary medicine · 2d
Cohort studyBMC pulmonary medicine · 2026

Bayesian network model for identification of factors associated with ventilator-associated pneumonia in mechanically ventilated patients in the ICU: retrospective cohort study.

Liyu Zhang, Cailing Wang, Jing He … Yinghui Zhang
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Pulmonology & Critical CareCohort study

Bayesian network model showed good performance for identifying VAP risk.

Bayesian network model for identification of factors associated with ventilator-associated pneumonia in mechanically ventilated patients in the ICU: retrospective cohort study.

Liyu Zhang et al. · BMC pulmonary medicine · 2026
Background

Ventilator-associated pneumonia (VAP) represents a complication occurring in patients undergoing mechanical ventilation.

Purpose

This study aimed to develop a Bayesian network model to identify factors associated with the occurrence of VAP.

Methods

A retrospective cohort analysis was conducted using data from patients aged ≥ 60 years who underwent mechanical ventilation in the Department of Intensive care unit at the Second Hospital of Shanxi Medical University between June 2018 and June 2022.

n = 502 patients
0.84
Results
the model performed well in identifying patients at higher risk for ventilator-associated pneumonia
n = 502 patients
More results

The prevalence of VAP was 9.6% (48/502 patients).

The constructed Bayesian network included 10 nodes and 17 directed edges.

Direct associations with VAP were identified for antibiotic use exceeding three agents, reintubation, mechanical ventilation methods, and an Acute Physiology and Chronic Health Evaluation II (APACHE II) score ≥ 15.

“
Conclusion · 1 of 2

The Bayesian network model elucidates the interrelationships among multiple factors associated with VAP.

Conclusion · 2 of 2

The model may provide ancillary information to help clinicians identify patient profiles associated with higher VAP risk and facilitate the implementation of early during mechanical ventilation.

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