Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Department of Neurosurgery, Chengdu Fifth People's Hospital/Affiliated Fifth People's Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.
Acta Neurochir (Wien). 2023 Nov;165(11):3255-3266. doi: 10.1007/s00701-023-05771-8. Epub 2023 Sep 11.
External ventricular drainage (EVD) is a life-saving neurosurgical procedure, of which the most concerning complication is EVD-related infection (ERI). We aimed to construct and validate an ERI risk model and establish a monographic chart.
We retrospectively analyzed the adult EVD patients in four medical centers and split the data into a training and a validation set. We selected features via single-factor logistic regression and trained the ERI risk model using multi-factor logistic regression. We further evaluated the model discrimination, calibration, and clinical usefulness, with internal and external validation to assess the reproducibility and generalizability. We finally visualized the model as a nomogram and created an online calculator (dynamic nomogram).
Our research enrolled 439 EVD patients and found 75 cases (17.1%) had ERI. Diabetes, drainage duration, site leakage, and other infections were independent risk factors that we used to fit the ERI risk model. The area under the receiver operating characteristic curve (AUC) and the Brier score of the model were 0.758 and 0.118, and these indicators' values were similar when internally validated. In external validation, the model discrimination had a moderate decline, of which the AUC was 0.720. However, the Brier score was 0.114, suggesting no degradation in overall performance. Spiegelhalter's Z-test indicated that the model had adequate calibration when validated internally or externally (P = 0.464 vs. P = 0.612). The model was transformed into a nomogram with an online calculator built, which is available through the website: https://wang-cdutcm.shinyapps.io/DynNomapp/ .
The present study developed an infection risk model for EVD patients, which is freely accessible and may serve as a simple decision tool in the clinic.
脑室外引流（EVD）是一种挽救生命的神经外科手术，其中最令人担忧的并发症是与 EVD 相关的感染（ERI）。我们旨在构建和验证 ERI 风险模型，并建立专题图表。
我们回顾性分析了四个医疗中心的成人 EVD 患者，并将数据分为训练集和验证集。我们通过单因素逻辑回归选择特征，并使用多因素逻辑回归训练 ERI 风险模型。我们进一步评估了模型的判别能力、校准能力和临床实用性，内部和外部验证评估可重复性和通用性。我们最终将模型可视化作为诺模图，并创建了一个在线计算器（动态诺模图）。
我们的研究纳入了 439 名 EVD 患者，发现 75 例（17.1%）发生了 ERI。糖尿病、引流时间、部位渗漏和其他感染是我们用来拟合 ERI 风险模型的独立危险因素。模型的受试者工作特征曲线下面积（AUC）和 Brier 评分分别为 0.758 和 0.118，内部验证时这些指标的值相似。外部验证时，模型的判别能力略有下降，AUC 为 0.720。然而，Brier 评分是 0.114，表明整体性能没有下降。Spiegelhalter 的 Z 检验表明，内部或外部验证时模型具有足够的校准（P=0.464 与 P=0.612）。该模型转化为一个带有在线计算器的诺模图，可通过网站访问：https://wang-cdutcm.shinyapps.io/DynNomapp/ 。
本研究开发了一种 EVD 患者感染风险模型，该模型可免费获取，并可在临床中作为简单的决策工具。
