关键词: 列线图, 呼吸机相关性肺炎, 急性大血管闭塞性脑梗死, 血管内治疗, 机械通气, 预后预测模型

Abstract:

Objective To analyze the clinical characteristics of the patients with poor prognosis after ventilator associated pneumonia （VAP） following endovascular treatment for acute cerebral infarction， and to construct a prognostic nomogram and validate its clinical application. Methods The clinical data of 105 patients diagnosed with acute large vessel occlusion cerebral infarction （AIS-LVO） who developed postoperative VAP after undergoing endovascular treatment under general anesthesia with endotracheal intubation were retrospectively analyzed. According to the 90 d modified Rankin Scale （mRS） score， the patients were divided into good prognosis group （43 cases） and poor prognosis group （62 cases）. LASSO regression analysis was used to screen the predictive factors， and multivariate Logistic regression analysis was performed to construct the prognostic prediction model and generate a nomogram. The discrimination， calibration， and clinical utility of the model were evaluated using receiver operating characteristic （ROC） curve， calibration curve， and decision curve analysis （DCA）. Results A total of 105 patients with VAP after ventilator-associated pneumonia were included. According to the 90 d mRS score， all postoperative VAP patients were divided into good prognosis group and poor prognosis group， with good prognosis rate of 40.95%（43/105）， poor prognosis rate of 59.05%（62/105）， and mortality rate of 11.43%（12/105）. The LASSO regression analysis screened out 9 variables， including male， age， history of coronary heart disease， mechanical thrombectomy， balloon angioplasty， systemic inflammatory response index （SIRI）， swallowing dysfunction， admission mRS score， and intensive care unit （ICU） length of stay. The predictive factors screened by LASSO regression were incorporated into multivariate Logistic regression analysis， and male ［odds ratio（OR）=0.287， 95% confidence interval （CI）： 0.089-0.838， P=0.028］， ICU length of stay （OR=1.238， 95%CI： 1.064-1.498， P=0.014）， swallowing dysfunction （OR=3.347， 95%CI： 1.336-8.918， P=0.012）， and SIRI （OR=1.168， 95%CI： 1.022-1.399， P=0.044） were identified as independent risk factors for poor prognosis in the VAP patients after endovascular treatment for cerebral infarction. A prognostic prediction model was constructed based on these 4 indicators， with the formula： Logit （P）=-0.613-1.250×sex （male）+1.208×swallowing dysfunction+0.155×SIRI+0.214×ICU length of stay. The area under the ROC curve （AUC） of the prediction model was 0.806 （95%CI： 0.804-0.910， P<0.05）. The internal validation was performed using 1 000 bootstrap resampling， and the calibration curve was close to the ideal line， indicating good model accuracy. DCA demonstrated favorable clinical net benefit of the nomogram. Conclusion The prognostic prediction model constructed based on male， ICU length of stay， swallowing dysfunction， and SIRI has good predictive value for poor prognosis in the VAP patients after endovascular treatment for acute cerebral infarction， which can assist the clinicians in early identification and intervention.

Key words: Nomogram, Ventilator-associated pneumonia, Acute large vessel occlusion cerebral infarction, Endovascular treatment, Mechanical ventilation, Prognostic prediction model