A Supplementary Grading Scale for Selecting Patients With Brain Arteriovenous Malformations for Surgery

医学 改良兰金量表 接收机工作特性 分级比例尺 分级(工程) 逻辑回归 动静脉畸形 多元微积分 梅尔克松-罗森塔尔综合征 放射科 颅内动静脉畸形 试验预测值 外科 脑血管造影 血管造影 内科学 土木工程 缺血性中风 缺血 控制工程 工程类
作者
Michael T. Lawton,Helen Kim,Charles E. McCulloch,Bahar Mikhak,William L. Young
出处
期刊:Neurosurgery [Oxford University Press]
卷期号:66 (4): 702-713 被引量:347
标识
DOI:10.1227/01.neu.0000367555.16733.e1
摘要

Patient age, hemorrhagic presentation, nidal diffuseness, and deep perforating artery supply are important factors when selecting patients with brain arteriovenous malformations (AVMs) for surgery.We hypothesized that these factors outside of the Spetzler-Martin grading system could be combined into a simple, supplementary grading system that would accurately predict neurologic outcome and refine patient selection.A consecutive, single-surgeon series of 300 patients with AVMs treated microsurgically was analyzed in terms of change between preoperative and final postoperative modified Rankin Scale scores. Three different multivariable logistic models (full, Spetzler-Martin, and supplementary models) were constructed to test the association of combined predictor variables with the change in modified Rankin Scale score. A simplified supplementary grading system was developed from the data with points assigned according to each variable and added together for a supplementary AVM grade.Predictive accuracy was highest for the full multivariable model (receiver operating characteristic curve area, 0.78), followed by the supplementary model (0.73), and least for the Spetzler-Martin model (0.66). Predictive accuracy of the simplified supplementary grade was significantly better than that of the Spetzler-Martin grade (P = .042), with receiver operating characteristic curve areas of 0.73 and 0.65, respectively.This new AVM grading system supplements rather than replaces the well-established Spetzler-Martin grading system and is a better predictor of neurologic outcomes after AVM surgery. The supplementary grading scale has high predictive accuracy on its own and stratifies surgical risk more evenly. The supplementary grading system is easily applicable at the bedside, where it is intended to improve preoperative risk prediction and patient selection for surgery.

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