A Discriminative Prediction Model of Neurological Outcome for Patients Undergoing Surgery of Brain Arteriovenous Malformations

Abstract

Background and Purpose— To develop and validate a discriminative model for predicting neurological morbidity after brain arteriovenous malformation (bAVM) surgery. Methods— Of 233 consecutive, prospectively enrolled patients undergoing bAVM surgery, the first 175 were used to derive, and the last 58 to validate, the prediction model. Demographic and angiographic factors were related to modified Rankin Scale scores assigned before, within 72 hours, at 7 days and at ≥1 year after surgery to seek predictors of postoperative neurological deficits (modified Rankin Scale score ≥3). These factors included nidus size, eloquence, venous drainage, diffuseness, white matter configuration, arterial perforator supply and associated aneurysms. Results— Brain eloquence, diffuse nidus and deep venous drainage were significant predictors of early disabling neurological deficits (odds ratios of 4.33, 3.49 and 2.38, respectively). The rounded odds ratios form a weighted 9-point prediction model (maximum scores for eloquence+diffuseness+deep drainage=4+3+2). The score discriminated the probability of experiencing both early (first week) and permanently (at ≥1 year) disabling neurological deficits as follows: 0 to 2: 1.8%, 3 to 5: 17.4%, 6 to 7: 31.6%, >7: 52.9% for early and 0 to 2: 1.8%, 3 to 5: 4.4%, 6 to 7: 18.4%, >7: 32.4% for permanently disabling outcomes. The discrimination of the model was 0.80 with 2.8% optimism. Validation in the second patient cohort revealed good performance at risk stratification. Conclusions— Relative weights assigned to brain eloquence, diffuse nidus morphology and deep venous drainage of a bAVM provide a simple and discriminative prediction model for neurological outcome after bAVM surgery.