Development of Muscle-specific Multi-modal AI for Sarcopenia Diagnosis: Effects of Rehabilitation Training on Ant-muscle Aging
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 入组人数
- 75
- 主要终点
- AI model performance
研究概览
简要总结
This study aims to develop a muscle-specific multimodal artificial intelligence (AI) model for the diagnosis of sarcopenia and to investigate the effects of rehabilitation training on muscle aging. Clinical, functional, and imaging data will be collected from participants with muscle function decline. Multimodal data, including muscle function measurements and clinical assessments, will be integrated to develop and validate an AI-based diagnostic model for sarcopenia. In addition, the effects of rehabilitation training on muscle function and muscle aging-related outcomes will be evaluated. The results of this study are expected to contribute to the development of digital biomarkers and precision rehabilitation strategies for sarcopenia.
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Single Group
- 主要目的
- Basic Science
- 盲法
- None
入排标准
- 年龄范围
- 65 Years 至 85 Years（Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Adults aged 65 years or older
- •Individuals with reduced muscle function or at risk of sarcopenia
- •Able to participate in rehabilitation training
- •Able to understand the study procedures and provide written informed consent
排除标准
- •Severe cardiovascular, neurological, or musculoskeletal conditions that limit participation in exercise
- •Severe cognitive impairment
- •Participation in other clinical trials that may influence study outcomes
- •Any medical condition judged by the investigator to make participation unsafe
研究组 & 干预措施
Rehabilitation Training
Participants will undergo a structured rehabilitation training program aimed at improving muscle function and reducing muscle aging-related decline.
干预措施: Rehabilitation training (Behavioral)
结局指标
主要结局
AI model performance
时间窗: Baseline to 12 weeks after rehabilitation training
The performance of the muscle-specific multimodal artificial intelligence (AI) model for detecting sarcopenia will be evaluated using the Area Under the Receiver Operating Characteristic Curve (AUC). The AUC evaluates the ability of the AI model to discriminate between participants with and without sarcopenia(e.g., handgrip strength, gait speed, and appendicular skeletal muscle mass). The AUC value ranges from 0.5 to 1.0, where higher values indicate better discrimination performance of the AI model.
次要结局
- Appendicular Skeletal Muscle Mass (DEXA)(Baseline to 12 weeks after rehabilitation training)
- Handgrip Strength(Baseline to 12 weeks after rehabilitation training)
- Five-Times Chair Stand Test (5×STS)(Baseline to 12 weeks after rehabilitation training)
- Gait Speed(Baseline to 12 weeks after rehabilitation training)
- Appendicular Skeletal Muscle Mass (BIA)(Baseline to 12 weeks after rehabilitation training)
- Sarcopenia Screening(Baseline to 12 weeks after rehabilitation training)
- Single Muscle Fiber Contractile Properties(Baseline to 12 weeks after rehabilitation training)
- Short Physical Performance Battery (SPPB)(Time Frame: Baseline to 12 weeks after rehabilitation training)
研究者
Jae-Young Lim
Professor
Seoul National University Bundang Hospital