Early Predictors of Long-Term Outcome in Basilar Artery Occlusion: A Post Hoc Analysis of the ATTENTION Trial
Year: 2026
Type: article
Abstract: BACKGROUND AND PURPOSE: Accurately predicting long-term functional outcomes of basilar artery occlusion (BAO) remains challenging. We compared the predictive performance of the baseline, 24-hour, and 72-hour National Institutes of Health Stroke Scale (NIHSS) scores for 90-day BAO functional outcomes using the Acute Basilar Artery Occlusion: Endovascular Thrombectomy versus Standard Medical Treatment (ATTENTION) trial data. We identified the optimal assessment time point, determined treatment-specific NIHSS cutoff values, and explored the role of early neurological function in treatment effects. METHODS: This retrospective post hoc analysis included 324 patients with acute BAO with baseline NIHSS scores ≥10 and complete NIHSS assessments at each time point. The primary outcome was a favorable 90-day functional outcome (modified Rankin Scale score, 0-3). Receiver operating characteristic curve analysis was used to assess the predictive ability of NIHSS scores. The optimal 72-hour NIHSS predictive cutoff values were determined for the endovascular treatment (EVT) and best medical management (BMM) subgroups. RESULTS: The 72-hour NIHSS score showed the highest predictive accuracy for the primary outcome (area under the receiver operating characteristic curve [AUC]: 0.954), outperforming the 24-hour (AUC: 0.903) and baseline (AUC: 0.688) scores; its optimal predictive cut-off value was ≤11 in the EVT group (sensitivity: 85.6%, specificity: 92.9%, positive predictive value [PPV]: 91.8%, negative predictive value [NPV]: 87.4%) and ≤9 in the BMM group (sensitivity: 84.6%, specificity: 95.1%, PPV: 84.6%, NPV: 95.1%). CONCLUSIONS: The 72-hour NIHSS score outperformed the baseline and 24-hour scores in predicting 90-day functional outcomes and mediating the effects of EVT. Treatment-specific 72-hour NIHSS cut-off values may guide early risk stratification and prognostic assessments.
Source: Journal of Stroke
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
Funder: Central Universities in China
Award: G2780559444
OpenAlex ID: W7126081254
