借助Clin-STAR围绕赤道开展研究:衰老研究中基于人工智能的随机对照试验的挑战与机遇
Around the EQUATOR With Clin-STAR: AI-Based Randomized Controlled Trial Challenges and Opportunities in Aging Research.
作者信息
Yang Betsy, Park Caroline, Lin Steven, Muralidharan Vijaytha, Kado Deborah M
机构信息
Section of Geriatric Medicine, Division of Primary Care and Population Health, Department of Medicine, Stanford School of Medicine, Palo Alto, California, USA.
Geriatric Research Education Research and Clinical Center (GRECC), Veterans Administration Healthcare System, Palo Alto, California, USA.
出版信息
J Am Geriatr Soc. 2025 May;73(5):1365-1375. doi: 10.1111/jgs.19362. Epub 2025 Feb 5.
The CONSORT 2010 statement is a guideline that provides an evidence-based checklist of minimum reporting standards for randomized trials. With the rapid growth of Artificial Intelligence (AI) based interventions in the past 10 years, the CONSORT-AI extension was created in 2020 to provide guidelines for AI-based randomized controlled trials (RCT). The Clin-STAR "Around the EQUATOR" series features existing reported standards while also highlighting the inherent complexities of research involving research of older participants. In this work, we propose that when designing AI-based RCTs involving older adults, researchers adopt a conceptual framework (CONSORT-AI-5Ms) designed around the 5Ms (Mind, Mobility, Medications, Matters most, and Multi-complexity) of Age-Friendly Healthcare Systems. Employing the 5Ms in this context, we provide a detailed rationale and include specific examples of challenges and potential solutions to maximize the impact and value of AI RCTs in an older adult population. By combining the original intent of CONSORT-AI with the 5Ms framework, CONSORT-AI-5Ms provides a patient-centered and equitable perspective to consider when designing AI-based RCTs to address the diverse needs and challenges associated with geriatric care.
CONSORT 2010声明是一项指南,它提供了基于证据的随机试验最低报告标准清单。在过去10年中,基于人工智能(AI)的干预措施迅速发展,因此在2020年创建了CONSORT-AI扩展版,以为基于AI的随机对照试验(RCT)提供指导方针。Clin-STAR“围绕赤道”系列介绍了现有的报告标准,同时也强调了涉及老年参与者研究的内在复杂性。在这项工作中,我们建议在设计涉及老年人的基于AI的RCT时,研究人员采用围绕老年友好型医疗保健系统的5M(思维、行动能力、药物、最重要的事和多重复杂性)设计的概念框架(CONSORT-AI-5M)。在这种情况下运用5M,我们提供了详细的基本原理,并包括挑战和潜在解决方案的具体示例,以最大化AI RCT在老年人群体中的影响和价值。通过将CONSORT-AI的原始意图与5M框架相结合,CONSORT-AI-5M为设计基于AI的RCT以满足与老年护理相关的各种需求和挑战时提供了以患者为中心且公平的视角。