ArticleInfection and drug resistance2025
Analysis of Influencing Factors and Construction of a Column Chart Model for Postoperative Pulmonary Infection in Patients With Severe Traumatic Brain Injury.
Article in Infection and drug resistance, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Interpretable Machine Learning Model for Fungal Infection Prediction: A Real-World Study.Health care science · 2026Article
- The Analysis of Risk Factors of Stroke-Associated Pneumonia in Patients with Acute Stroke Based on Lasso Regression and the Construction of a Nomogram Prediction Model.Infection and drug resistance · 2026Article
- Pathogen profiles and risk factors of hospital-acquired infections in traumatic brain injury patients.Frontiers in public health · 2026Article
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Authors and funding
3 authors.
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Abstract
Objective: To analyze the influencing factors of postoperative pulmonary infection in patients with severe traumatic brain injury, and establish and validate a column chart prediction model. Methods: A retrospective study was conducted on 314 patients with severe traumatic brain injury in our hospital from January 2022 to March 2024. They were separated into an internal validation group of 235 cases and an external validation group of 79 cases randomly. The internal validation group was grouped into an infection group of 73 cases and an non-infection group of 162 cases. All patients underwent pathogen detection and identification. Results: A total of 96 strains of pathogens were isolated from 73 patients with concurrent pulmonary infections. Independent risk factors for postoperative pulmonary infection in patients with severe TBI included age ≥ 60 years, diabetes, tracheotomy, operation time ≥ 4 hours, sputum excretion in the supine position, mechanical ventilation duration ≥ 7 days, and GCS score < 8 points mechanical ventilation duration (P<0.05). The constructed column chart prediction model had high discrimination, calibration, and clinical practical value. Conclusion: The column chart model, incorporating age, diabetes, tracheotomy, operation time, sputum excretion position, mechanical ventilation duration and GCS score, can effectively predict pulmonary infections in severe traumatic brain injury patients.
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