# Construction and Validation of a Risk Prediction Model for Ventilator-Associated Pneumonia in Mechanically Ventilated Pediatric Patients

## TL;DR

This study creates a model to predict ventilator-associated pneumonia risk in children on ventilators, helping nurses target interventions to reduce infections.

## Contribution

A novel risk prediction model for ventilator-associated pneumonia in pediatric patients is developed and validated.

## Key findings

- Absence of early enteral nutrition, duration of mechanical ventilation, and antibiotic use are significant VAP risk factors.
- The model showed strong discrimination with an ROC-AUC of 0.870 in the derivation cohort.
- Calibration was confirmed with p-values of 0.970 and 0.524 for derivation and validation cohorts.

## Abstract

This study identified risk factors for ventilator-associated pneumonia (VAP) in mechanically ventilated (MV) children and developed a risk prediction model to guide precision nursing interventions.

MV supports critically ill pediatric patients by improving oxygenation but may induce lung injury and increase VAP incidence.

We retrospectively analyzed pediatric MV patients admitted to the Pediatric Intensive Care Unit (PICU) at Shengjing Hospital, China Medical University. Independent VAP risk factors were identified using binary logistic regression, and a prediction model was developed/validated with R software.

Absence of early enteral nutrition (EEN), duration of MV, frequency of endotracheal suctioning, central venous catheterization, and the types of antibiotics used were independent VAP risk factors (p < 0.05). The model demonstrated strong discrimination, with ROC-AUCs of 0.870 (95% CI: 0.816–0.924) and 0.761 (95% CI: 0.653–0.868) for derivation and validation cohorts, respectively. Hosmer–Lemeshow tests confirmed calibration (p=0.970 and p=0.524).

This validated model effectively stratifies VAP risk in MV children, enabling early identification of high-risk patients and facilitating targeted nursing strategies.

The model allows rapid clinical screening for high-risk pediatric VAP cases. Interventions focused on modifiable risk factors may reduce VAP incidence.