从筛查到防控:国际运动前健康筛查经验与中国一体化运动风险防控体系构建

    From Screening to Prevention: International Experience in Pre-participation Health Screening and the Construction of an Integrated Exercise Risk Management System in China

    • 摘要: 通过科学运动降低身体活动不足相关的心血管疾病负担与全因死亡率,已成为全球公共卫生界的共识。然而,运动本身也可能诱发严重的心血管事件,为此需在融合人工智能(artificial intelligence,AI)等技术的基础上,借鉴国际运动前健康筛查经验,构建适用于我国健身人群与专业运动员的运动风险防控体系。研究系统梳理了6种国际主流运动前健康风险筛查工具,分别为身体活动准备问卷(physical activity readiness questionnaire ,PAR-Q)及其全人群版本(physical activity readiness questionnaire for everyone, PAR-Q+)、美国心脏协会(American Heart Association,AHA)指南、欧洲心血管预防与康复协会(European Association of Cardiovascular Prevention and Rehabilitation,EACPR)指南、美国运动医学学会(American College of Sports Medicine,ACSM)2015年前后修订的第9版与第10版指南,发现其演进均呈现从“限制运动”的保守模式向“允许运动”的包容模式转变的趋势。在分析各工具适用对象、核心内容及使用有效性的基础上,基于“是否具有规律运动习惯”“是否存在心血管、代谢或肾脏疾病及相关症状”以及“运动项目风险特点”3个维度,提出分层筛查建议:1)健康大众健身人群从事中低强度运动时,可直接参与;若患有心血管疾病但无症状且无运动习惯,需经获取医学许可或使用PAR-Q+初筛后决定运动强度;运动中若出现症状应立即停止运动并进行评估。2)马拉松等高强度/大运动量项目仅推荐有训练基础者参与,且需提前评估。3)竞技运动员则应采用AHA指南筛查结合静息心电图及超声心动图的联合策略进行筛查。基于我国AI、大数据及移动网络技术快速发展的背景,研究进一步提出构建我国运动风险防控体系的4项建议:1)通过运动风险教育提升公众防范意识;2)普及、验证并规范应用现有的成熟筛查工具;3)推动建立基于人工智能与大数据的智能筛查与预警新模式;4)依托智能可穿戴设备实现运动过程中风险的动态监测与即时干预。通过整合运动前风险教育、精准筛查评估与运动中风险实时管控,最终构建出具有“教育−筛查−管控”三位一体特征的运动健康风险防控体系。

       

      Abstract: Promoting scientific physical activity to reduce the burden of cardiovascular diseases and all-cause mortality associated with physical inactivity has become a global consensus in public health. However, exercise itself may also induce severe cardiovascular events, highlighting the urgent need to establish a comprehensive exercise risk prevention and control system in China, applicable to both general fitness participants and professional athletes. The system requires international experience and should integrate advanced technologies such as artificial intelligence. This study systematically reviewed six internationally mainstream pre-exercise health risk screening tools: the PAR-Q and PAR-Q+ questionnaires, the AHA guidelines, the EACPR guidelines, and the 9th and 10th editions of the ACSM guidelines revised around 2015, and found that their evolution has consistently shifted from a restrictive, “exercise-limiting” model toward a more inclusive, “exercise-permitting” approach. Based on an analysis of their target populations, core content, and effectiveness, and considering three key dimensions of“whether the individual has a regular exercise habit”“presence of cardiovascular, metabolic, or renal diseases and any related symptoms” and “risk characteristics of the exercise activity”, three stratified screening recommendations were proposed: 1) For the general healthy population engaging in low-to-moderate intensity exercise, direct participation is acceptable. Individuals with diagnosed cardiovascular disease but no symptoms and no exercise habit should undergo initial screening using PAR-Q+ to determine appropriate exercise intensity or obtain medical clearance. Exercise should be stopped immediately and assessed if symptoms appear during activity. 2) High-intensity activities like marathons are only recommended for those with a solid training foundation and require prior evaluation. 3) Competitive athletes should adopt a combined screening strategy utilizing the AHA 14-element screening guidelines along with resting electrocardiography and echocardiography. Furthermore, combining the rapid advancements in artificial intelligence, big data, and mobile network technology in China, the study puts forward three key recommendations for constructing a national exercise risk prevention and control system: 1) Enhance public awareness of risk prevention through exercise risk education; 2) Popularize, validate, and standardize the application of existing mature screening tools; 3) Promote the establishment of a new intelligent screening and early-warning model based on AI and big data; and 4) Utilize smart wearable devices to enable dynamic monitoring and real-time intervention for risks during exercise. By integrating pre-participation risk education, precise screening assessment, and real-time risk management during activity, the study ultimately proposes the construction of an integrated “Education-Screening-Control” exercise health risk prevention and control system.

       

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