An admission bioclinical score to predict 1-year outcomes in patients undergoing aneurysm coiling.

Abstract

A number of scores were developed to predict outcomes after clipping for subarachnoid hemorrhages, yet there is no score for patients undergoing endovascular treatment. Our goal was to develop, compare, and validate a predictive score for 1-year outcomes in patients with coiled subarachnoid hemorrhage. We studied 526 patients for 1 year after intensive care unit discharge. We developed an admission bioclinical score (ABC score), which integrated biomarkers such as troponin I and S100β, with the Glasgow Coma Scale. Using the receiver operating characteristic curve (95% CI), the ABC score was compared with the Glasgow Coma Scale, World Federation of Neurosurgical Societies score, and Fisher score in the derivation cohort and further validated in an independent cohort. In the derivation cohort (from 2003-2007, n=368), multivariate logistic regression analysis showed that only Glasgow Coma Scale (P<0.001), high S100β (P<0.001), and high troponin (P<0.02) were independently associated with 1-year mortality. Troponin, S100β, and Glasgow Coma Scale were thus integrated to derive the ABC score. In the derivation cohort, the ABC score reached an receiver operating characteristic curve of 0.82 (0.77-0.88, P<0.001) and was significantly greater than the receiver operating characteristic curves of the Glasgow Coma Scale, World Federation of Neurosurgical Societies, and Fisher scores for predicting 1-year mortality. In the validation cohort (from 2008-2009, n=158), the ABC score's receiver operating characteristic curve of 0.76 (0.67-0.86, P<0.001) remained superior to the 3 other scores for predicting 1-year mortality. The ABC score improves 1-year outcome prediction at admission for patients with coiled subarachnoid hemorrhage. Our study provides large cohort-based evidence supporting integration of individual biomarkers and clinical characteristics to predict outcomes. Clinical Trial Registration- URL: www.clinicaltrials.gov. Unique identifier: NCT01357057.