Imaging-Based Brain Frailty Predicts Unfavorable Outcomes in Acute Ischemic Stroke

基于影像学的脑脆弱性可预测急性缺血性卒中的不良预后

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Abstract

BACKGROUND: Brain frailty is characterized by imaging biomarkers of chronic cerebrovascular injury. Whether brain frailty improves the prediction of acute ischemic stroke complications and prognosis requires further study. METHODS: This multicenter, retrospective study included patients with acute ischemic stroke due to large-vessel occlusion in the anterior circulation. All patients underwent magnetic resonance imaging within 7 days of stroke onset, measuring subcortical and cortical atrophy and white matter hyperintensity as indicators of brain frailty. Multivariable logistic regression analyses and receiver operating characteristic curve analyses were used to assess the association and predictive value of brain frailty with complications and unfavorable clinical outcome (90-day modified Rankin Scale score, 3-6). RESULTS: The study included 1090 patients with a median age of 64 (interquartile range, 55-73) years and a median National Institutes of Health Stroke Scale score of 9 (interquartile range, 4.5-15). Multivariable logistic regression analysis showed that independent risk factors for the unfavorable clinical outcome included: National Institutes of Health Stroke Scale score (odds ratio [OR], 1.09 [95% CI, 1.06-1.11]), blood glucose (OR, 1.18 [95% CI, 1.11-1.26]), infarct volume (OR, 1.43 [95% CI, 1.29-1.60]), subcortical atrophy (OR, 1.16 [95% CI, 1.10-1.23]), severe cortical atrophy (OR, 2.31 [95% CI, 1.04-5.15]), and severe white matter hyperintensity (OR, 3.63 [95% CI, 1.91-6.89]). However, brain frailty was not significantly associated with acute ischemic stroke complications (malignant cerebral edema, parenchymal hemorrhage). Including brain frailty indicators in the model significantly improved its unfavorable clinical outcome predictive power (area under the receiver operating characteristic curve increased from 0.762 to 0.822; P<0.001). The results remained stable in subgroup analyses across treatment modalities. CONCLUSIONS: Brain frailty was significantly associated with the unfavorable clinical outcome. Brain frailty indicators contributed to the predictive efficacy, regardless of treatment modality.

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