Development and external validation of a nomogram for predicting postoperative pneumonia in aneurysmal subarachnoid hemorrhage

医学 列线图 蛛网膜下腔出血 格拉斯哥昏迷指数 接收机工作特性 逻辑回归 队列 机械通风 急诊医学 内科学 外科
作者
Jin Xiao,Shijia Wang,Chengwei Zhang,Song Yang,Lejing Lou,Shuyao Xu,Chang Cai
出处
期刊:Frontiers in Neurology [Frontiers Media SA]
卷期号:14 被引量:5
标识
DOI:10.3389/fneur.2023.1251570
摘要

Background Postoperative pneumonia (POP) is a common complication after aneurysmal subarachnoid hemorrhage (aSAH) associated with increased mortality rates, prolonged hospitalization, and high medical costs. It is currently understood that identifying pneumonia early and implementing aggressive treatment can significantly improve patients' outcomes. The primary objective of this study was to explore risk factors and develop a logistic regression model that assesses the risks of POP. Methods An internal cohort of 613 inpatients with aSAH who underwent surgery at the Neurosurgical Department of First Affiliated Hospital of Wenzhou Medical University was retrospectively analyzed to develop a nomogram for predicting POP. We assessed the discriminative power, accuracy, and clinical validity of the predictions by using the area under the receiver operating characteristic curve (AUC), the calibration curve, and decision curve analysis (DCA). The final model was validated using an external validation set of 97 samples from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Results Among patients in our internal cohort, 15.66% ( n = 96/613) of patients had POP. The least absolute shrinkage and selection operator (LASSO) regression analysis identified the Glasgow Coma Scale (GCS), mechanical ventilation time (MVT), albumin, C-reactive protein (CRP), smoking, and delayed cerebral ischemia (DCI) as potential predictors of POP. We then used multivariable logistic regression analysis to evaluate the effects of these predictors and create a final model. Eighty percentage of patients in the internal cohort were randomly assigned to the training set for model development, while the remaining 20% of patients were allocated to the internal validation set. The AUC values for the training, internal, and external validation sets were 0.914, 0.856, and 0.851, and the corresponding Brier scores were 0.084, 0.098, and 0.143, respectively. Conclusion We found that GCS, MVT, albumin, CRP, smoking, and DCI are independent predictors for the development of POP in patients with aSAH. Overall, our nomogram represents a reliable and convenient approach to predict POP in the patient population.
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