Department of Neurosurgery, Sheffield Teaching Hospital NHS Foundation Trust, Sheffield, United Kingdom.
Department of Neurosurgery, Sheffield Teaching Hospital NHS Foundation Trust, Sheffield, United Kingdom.
World Neurosurg. 2021 Feb;146:e1255-e1261. doi: 10.1016/j.wneu.2020.11.146. Epub 2020 Dec 1.
The current study is an external validation of 4 scoring models proposed in the literature for predicting ventriculoperitoneal shunt insertion after aneurysmal subarachnoid hemorrhage (aSAH) using retrospective patient data from Sheffield Teaching Hospital (STH).
Data were collected on various demographics, and patients were individually scored using the 4 scoring models. Models were compared with each other using receiver-operator characteristic curves. The best model had the highest area under the curve.
A total of 301 aSAH patients were referred to the neurosurgery department in STH between 1 January 2014 and 31 December 2017. Scoring model 4 also had the largest area under the curve of 0.853 (P < 0.001), and scoring model 3 had the lowest area under the curve of 0.654 (P = 0.036).
Scoring model 4 was found to be the best scoring model out of the 4 scoring models externally validated to predict shunt dependency after an aSAH in STH patients. Scoring model 4 is less applicable in modern practice due to a higher proportion of coiling and use of the Hunt and Hess scale grade. A new scoring model is needed to predict shunt insertion in modern practice.
本研究是对文献中提出的 4 种评分模型在使用谢菲尔德教学医院（STH）回顾性患者数据预测蛛网膜下腔出血（aSAH）后行脑室-腹腔分流术的外部验证。
收集了各种人口统计学数据，并使用 4 种评分模型对每位患者进行评分。使用接收者操作特征曲线对模型进行比较。最佳模型的曲线下面积最高。
2014 年 1 月 1 日至 2017 年 12 月 31 日期间，共有 301 例 aSAH 患者被转诊至 STH 神经外科。评分模型 4 的曲线下面积也最大，为 0.853（P < 0.001），评分模型 3 的曲线下面积最小，为 0.654（P = 0.036）。
评分模型 4 被发现是在 STH 患者中对 aSAH 后分流依赖进行外部验证的 4 种评分模型中最好的评分模型。由于 coil 应用比例较高和 Hunt 和 Hess 分级的使用，评分模型 4 在现代实践中应用较少。需要一种新的评分模型来预测现代实践中的分流术。
