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一种用于预测动脉瘤性蛛网膜下腔出血术后肺炎的列线图的开发与外部验证

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

作者信息

Jin Xiao, Wang Shijia, Zhang Chengwei, Yang Song, Lou Lejing, Xu Shuyao, Cai Chang

机构信息

Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.

Department of Neurosurgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.

出版信息

Front Neurol. 2023 Sep 4;14:1251570. doi: 10.3389/fneur.2023.1251570. eCollection 2023.

Abstract

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% ( = 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.

摘要

背景

术后肺炎(POP)是动脉瘤性蛛网膜下腔出血(aSAH)后的常见并发症,与死亡率增加、住院时间延长及医疗费用高昂相关。目前认为,早期识别肺炎并实施积极治疗可显著改善患者预后。本研究的主要目的是探讨危险因素并建立评估POP风险的逻辑回归模型。

方法

对温州医科大学附属第一医院神经外科接受手术的613例aSAH住院患者的内部队列进行回顾性分析,以制定预测POP的列线图。我们通过使用受试者操作特征曲线(AUC)下的面积、校准曲线和决策曲线分析(DCA)来评估预测的辨别力、准确性和临床有效性。最终模型使用来自重症监护医学信息数据库IV(MIMIC-IV)的97个样本的外部验证集进行验证。

结果

在我们的内部队列患者中,15.66%(=96/613)的患者发生了POP。最小绝对收缩和选择算子(LASSO)回归分析确定格拉斯哥昏迷量表(GCS)、机械通气时间(MVT)、白蛋白、C反应蛋白(CRP)、吸烟和延迟性脑缺血(DCI)为POP的潜在预测因素。然后,我们使用多变量逻辑回归分析来评估这些预测因素的影响并创建最终模型。内部队列中80%的患者被随机分配到用于模型开发的训练集,而其余20%的患者被分配到内部验证集。训练集、内部验证集和外部验证集的AUC值分别为0.914、0.856和0.851,相应的Brier评分分别为0.084、0.098和0.143。

结论

我们发现GCS、MVT、白蛋白、CRP、吸烟和DCI是aSAH患者发生POP的独立预测因素。总体而言,我们的列线图是预测该患者群体中POP的一种可靠且便捷的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8da2/10513064/0514ef8071a5/fneur-14-1251570-g0001.jpg

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