纳减少计划 结合遗传特征和基于人工智能的应用程序:一个随机临床试验
Koryu Sato1,2, Kosuke Inoue2,3, Taihei Yamaguchi4
1Faculty of Policy Management, Keio University, Kanagawa, Japan.
JAMA network open
|October 16, 2025
概括
一项研究发现,将遗传特征与人工智能应用程序相结合并没有降低患有高血压的成年人的盐摄入量. 个性化数字干预在促进高血压管理的饮食行为改变方面面临挑战.
科学领域:
- 心血管疾病研究研究
- 遗传学和个性化医学
- 数字健康干预措施 数字健康干预措施
背景情况:
- 过度摄入盐是高血压和心血管疾病的关键危险因素.
- 使用遗传信息和数字工具的个性化干预表明减少的潜力,但需要更多证据.
研究的目的:
- 用遗传特征和基于人工智能的移动应用程序来评估减少的计划的有效性.
- 评估这种干预措施在患有高血压和对敏感基因型的成年人.
主要方法:
- 一个三臂随机临床试验,涉及312名年龄在20-65岁的员工,患有高血压和AGT M235T基因型.
- 干预包括使用人工智能应用程序的遗传特征,没有干预 (控制) 或仅使用应用程序.
- 每天的盐摄入量用点滴尿样和INTERSALT公式来测量.
主要成果:
- 3个月后,治疗组和对照组之间没有观察到每日盐摄入量的显著差异.
- 治疗组的盐摄入量也没有显著差异,与仅服用的组相比.
- 二次结果,包括血压和行为意图,在各组之间没有显著差异.
结论:
- 结合遗传特征和基于人工智能的应用程序的减少的计划并没有显著减少这一群体的盐摄入量.
- 这些发现表明,通过高血压的综合遗传和数字干预来实现饮食行为变化的挑战.
- 需要进行进一步的研究,以优化个人化降和预防心血管疾病的策略.
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