Related Experiment Video
Updated: Jan 12, 2026
A Low Mortality Rat Model to Assess Delayed Cerebral Vasospasm After Experimental Subarachnoid Hemorrhage
Published on: January 17, 2013
Development and Validation of a Predictive Model for Postoperative Pneumonia in Aneurysmal Subarachnoid Hemorrhage
Jinpeng Wu1, Cuiping Mu2, Jiazhong Lao1
1Department of Neurosurgery, The Affiliated Hospital of Qingdao University, Qingdao, China.
Background:
Postoperative pneumonia is a common complication in patients with aneurysmal subarachnoid hemorrhage (aSAH) and significantly affects patient prognosis. Early identification of high-risk patients is crucial to improving treatment outcomes. This study aims to develop and validate a predictive model for assessing the risk of postoperative pneumonia in aSAH patients.
Methods:
A total of 279 aSAH patients were included in this study. Patients were divided into 2 groups based on the occurrence of postoperative pneumonia: The Postoperative Pneumonia Group (75 patients) and The Nonpostoperative Pneumonia Group (204 patients). Baseline clinical characteristics, including gender, age, smoking history, Glasgow Coma Scale score, and Hunt-Hess grade, were collected. Least Absolute Shrinkage and Selection Operator regression was used to select key risk factors associated with postoperative pneumonia, and a predictive model was constructed using multivariate logistic regression. The model's performance was evaluated using receiver operating characteristic curves, calibration curves, and decision curve analysis.
Results:
The final model included age, gender, smoking history, Glasgow Coma Scale score, and Hunt-Hess grade as predictors of postoperative pneumonia. The model demonstrated strong predictive ability with an area under the curve of 0.809, indicating high accuracy. Calibration curves showed good model fit, and decision curve analysis results confirmed significant clinical applicability. A visual nomogram was also developed to assist clinicians in identifying high-risk patients.
Conclusions:
This study successfully developed and validated a predictive model to assess the risk of postoperative pneumonia in aSAH patients, incorporating key clinical variables. The model provides valuable guidance for the early identification of high-risk patients and the formulation of personalized intervention strategies.
