External Validation of an Extreme Gradient Boosting Model for Prediction of Delayed Cerebral Ischemia After Aneurysmal Subarachnoid Hemorrhage

Introduction: Delayed cerebral ischemia (DCI) may significantly worsen the functional status of patients with aneurysmal subarachnoid hemorrhage (aSAH). Several authors have designed predictive models for early identification of patients at risk of post-aSAH DCI. Alexopoulos et al. have recently introduced a new forecasting algorithm for post-aSAH DCI prediction. We externally validated the extreme gradient boosting (EGB) forecasting model for post-aSAH DCI prediction proposed by Alexopoulos et al.

Methods: A 9-year institutional retrospective review of patients with aSAH was performed. Patients were included if they underwent surgical or endovascular treatment and had available follow-up data. DCI was diagnosed as new onset neurological deficits at 4-12 days after aneurysm rupture, defined as worsening GCS for ≥2 points, and new ischemic infarcts at imaging.

Results: 267 patients with aSAH were collected. At admission, median Hunt-Hess score was 2 (range, 1-5), median Fischer score 3 (range, 1-4), and median modified Fischer score 3 (range, 1-4). 145 patients underwent EVD placement for hydrocephalus (54.3%). The ruptured aneurysms were treated with clipping (64%), coiling (34.8%), and stent-assisted coiling (1.1%). 58 patients (21.7%) were diagnosed with clinical DCI and 82 (30.7%) with asymptomatic imaging vasospasm. The EGB classifier correctly predicted 19 cases of DCI (7.1%) and 154 cases of no-DCI (57.7%), achieving sensitivity of 32.76% and specificity of 73.68%. The calculated F1-score and accuracy were 0.288 and 64.8%, respectively.

Conclusion : In this study, we confirm that the EGB model may be simply and effectively used in routine practice as an assistant to predict post-aSAH DCI. Future research should investigate the underlying pathophysiology of DCI to allow the development of high-performing forecasting models.