Journal of neurointerventional surgery
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Comparative Study
Frequency, predictors, and outcomes of readmission to index versus non-index hospitals after mechanical thrombectomy in patients with ischemic stroke.
Stroke systems of care employ a hub-and-spoke model, with fewer centers performing mechanical thrombectomy (MT) compared with stroke-receiving centers, where a higher number offer high-level, centralized treatment to a large number of patients. ⋯ One-quarter of patients with a stroke treated with MT were readmitted within 90 days, and one quarter of these patients were readmitted to non-index hospitals. Readmission to a non-index hospital was not associated with mortality or increased complication rates. In a hub-and-spoke model it is important that follow-up care for a specialized procedure can be performed effectively at a vast number of non-index hospitals covering a large geographic area.
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Acute stroke caused by large vessel occlusions (LVOs) requires emergent detection and treatment by endovascular thrombectomy. However, radiologic LVO detection and treatment is subject to variable delays and human expertise, resulting in morbidity. Imaging software using artificial intelligence (AI) and machine learning (ML), a branch of AI, may improve rapid frontline detection of LVO strokes. This report is a systematic review of AI in acute LVO stroke identification and triage, and characterizes LVO detection software. ⋯ AI may improve LVO stroke detection and rapid triage necessary for expedited treatment. Standardization of performance assessment is needed in future studies.