BACKGROUND: We investigated whether the cerebral blood volume (CBV) index and pretreatment systemic inflammatory indices (SIIs) provide complementary prognostic information for 90-day functional outcomes after successful endovascular therapy (EVT) for anterior circulation large vessel occlusion and evaluated the advantages of machine learning models in terms of prognostic outcomes and quantified adverse outcomes using the population attributable fraction (PAF). METHODS: This retrospective analysis of a prospective registry included 474 patients who were treated between November 2020 and June 2024. An independent 53-patient multicenter cohort was used for external validation. SIIs were calculated from the first venous sample obtained at presentation, before intravenous thrombolysis, and before arterial puncture for EVT. Multivariate logistic regression and eight predictive algorithms were evaluated. PAF estimates were considered exploratory. RESULTS: Among 474 patients, 41.6% and 28.5% achieved favorable and excellent outcomes, respectively. Higher CBV indices were more frequent among patients with favorable outcomes, whereas higher inflammatory indices were associated with worse outcomes. Logistic regression showed the highest AUC for mRS 0-2 (0.868, 95% CI 0.806-0.929), while SVM had the highest AUC for mRS 0-1 (0.839, 95% CI 0.764-0.915). The external validation AUCs were 0.816 and 0.802. PAF analysis indicated that improving the CBV index increased favorable and excellent outcomes by 97.2% and 74.8%, respectively, whereas reducing inflammatory overactivation improved them by 22.4%-39.7% and 51.2%-59.5%, respectively. CONCLUSION: Baseline CBV index and pretreatment SII values provided complementary prognostic information after successful EVT. However, prospective validation in a broader population is required before clinical implementation.
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Liu et al. (2026) studied this question.
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