Development of Multimodal Explainable AI (XAI) using Imaging and Blood Biomarkers for Predicting Post-Stroke Sarcopenia and Long-term Prognosis

Kyung Hee University Hospital0 个研究点目标入组 140 人开始时间: 2026年6月30日最近更新: 2026年8月3日

适应症

试验速览

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研究类型: Observational
观察模型: Cohort, Time Perspective : Prospective, Enrollment : 140, Biospecimen Retention : Collect & Archive- Sample with DNA, Biospecimen Description : plasma, serum

•Patients aged 50 years or older with acute stroke
•Patients who underwent brain MRI or CT within 1 week of stroke onset
•Patients who are able to undergo handgrip strength testing and body composition assessment using InBody S10 bioelectrical impedance analysis (BIA) within 1 month after stroke onset
•Patients who are available for follow-up evaluations at 1, 3, and 12 months after stroke onset through outpatient visits or telephone interviews
•Patients who provide written informed consent to participate in the study

•Patients with severe pre-stroke disability (modified Rankin Scale > 2)
•Patients with conditions that may independently affect sarcopenia, including end-stage cancer, dialysis-dependent chronic kidney disease, or neuromuscular disorders
•Patients with contraindications to bioelectrical impedance analysis (BIA), such as pacemakers or implantable cardioverter-defibrillators
•Patients with anatomical abnormalities of the temporalis muscle or a history of temporalis muscle surgery
•Patients with poor-quality MRI or CT images that preclude accurate measurement of temporalis muscle thickness
•Pregnant women or women for whom pregnancy cannot be excluded

发起方

Kyung Hee University Hospital