脑出血患者微创颅内血肿清除术后肺部 感染的影响因素分析及预测模型构建.

Objective To investigate the influencing factors of pulmonary infection during hospitalization after minimally invasive intracranial hematoma removal in patients with intracerebral hemorrhage (ICH) and construct a prediction model, in order to provide guidance for medical staff to evaluate the risk of postoperative pulmonary infection in ICH patients and develop prevention strategies. Methods ICH patients who underwent minimally invasive intracranial hematoma removal at the Department of Neurosurgery, Suzhou Ninth Hospital Affiliated to Soochow University from January 2018 to July 2023 were continuously included. The ICH patients were divided into pulmonary infection group and non-pulmonary infection group according to whether they had pulmonary infection during hospitalization. The clinical data of the two groups were compared. Multivariate logistic regression analysis was used to explore the influencing factors of pulmonary infection after minimally invasive intracranial hematoma removal in ICH patients, and the logistic regression model was constructed. At the same time, the gradient boosting machine (GBM) algorithm of R was used to construct a GBM prediction model for pulmonary infection after minimally invasive intracranial hematoma removal in ICH patients. The prediction efficiency of the two models was analyzed by ROC curve and compared by Delong test. Results A total of 297 ICH patients who underwent minimally invasive intracranial hematoma removal were included in the study. Among them, 52 cases (17.5%) occurred pulmonary infection during postoperative hospitalization. Multivariate analysis showed that malnutrition (OR 2.737, 95%CI 1.249-5.998, P=0.012), tracheotomy (OR 2.716, 95%CI 1.296-5.690, P =0.008), and indwelling gastric tube (OR 3.521, 95%CI 1.724-7.193, P <0.001) were independent risk factors for pulmonary infection in ICH patients after minimally invasive intracranial hematoma removal. High preoperative GCS score (OR 0.622, 95%CI 0.515-0.752, P<0.001) and oral care (OR 0.105, 95%CI 0.028-0.390, P<0.001) were protective factors. According to ROC curve analysis, the AUC of the logistic regression model was 0.837, and the AUC of the GBM prediction model was 0.861. Delong test showed that the efficiency of GBM prediction model was better than that of logistic regression model (Z=2.318, P=0.021). Conclusions Malnutrition, tracheotomy and indwelling gastric tube were the risk factors of pulmonary infection in ICH patients after minimally invasive intracranial hematoma removal, while high preoperative GCS score and oral care were protective factors. The efficiency of GBM model based on the above indicators was better than logistic model. [ABSTRACT FROM AUTHOR]