Abstract:

Objective To systematically evaluate risk prediction models for ventilator-associated pneumonia （VAP） in ICU mechanically ventilated patients，so as to provide references for clinical doctors and nurses to develop or select appropriate risk prediction model. Methods We systematically searched CNKI，Wanfang，VIP，CBM，PubMed，EMbase，Web of Science，CINAHL，and Cochrane Library for relevant studies published before April 30，2025. Two investigators independently screened the literature and extracted data，and evaluated the quality. Results 21 studies were included，involving 27 models with an area under the subject working characteristic curve of 0.722~1.00. The overall risk of bias in 21 studies were high，and the applicability in 13 studies was good. The bias risks were mainly due to failure to select appropriate data sources，insufficient sample sizes，improper handling of independent variables and missing data，screening predictors based on univariate analysis，and incomplete model performance evaluation. The most frequently reported predictors were ICU length of stay，duration of mechanical ventilation，APACHE Ⅱ score，tracheostomy，and combined antibiotic use. Conclusion Existing VAP risk prediction models demonstrate satisfactory predictive performance but exhibit high bias risks. Future research should prioritize methodological rigor in study design and standardized reporting to enhance model validity for clinical implementation.

Key words: Intensive Care Units, Ventilator-Associated Pneumonia, Risk, Prediction Model, Systematic Review