ArticleJournal of nursing management2025
Construction and Validation of a Risk Prediction Model for Ventilator-Associated Pneumonia in Mechanically Ventilated Pediatric Patients.
Article in Journal of nursing management, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Aim: 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. Background: MV supports critically ill pediatric patients by improving oxygenation but may induce lung injury and increase VAP incidence. Methods: 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. Results: 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 ( Conclusions: This validated model effectively stratifies VAP risk in MV children, enabling early identification of high-risk patients and facilitating targeted nursing strategies. Implications for Nursing Management: The model allows rapid clinical screening for high-risk pediatric VAP cases. Interventions focused on modifiable risk factors may reduce VAP incidence.
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