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实时AI辅助胰岛素定位系统用于2型糖尿病患者的葡萄糖控制:一项随机临床试验
Zhen Ying1, Yujuan Fan2, Congling Chen1
1Ministry of Education Key Laboratory of Metabolism and Molecular Medicine, Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai, China.
JAMA network open
|May 7, 2025
概括
一个用于2型糖尿病 (T2D) 胰岛素定位的人工智能系统显示结果与医生不逊色. 这种人工智能工具为改善住院T2D患者的血糖控制提供了有希望的方法.
科学领域:
- 内分泌学 在内分泌学.
- 人工智能的人工智能
- 临床决策支持系统 临床决策支持系统
背景情况:
- 2型糖尿病 (T2D) 是一个全球性的健康挑战,需要有效的血糖控制.
- 胰岛素定位对于T2D管理至关重要,但往往缺乏个性化的实时工具.
- 目前在住院患者的胰岛素调整方法可能不是最佳的.
研究的目的:
- 评估基于人工智能的胰岛素临床决策支持系统 (iNCDSS) 与高级医生相比,在住院T2D患者中进行胰岛素定位的非劣势.
- 评估人工智能引导胰岛素治疗的疗效和安全性.
主要方法:
- 一个多中心,单盲,并行随机临床试验 (RCT) 涉及149名成年T2D患者.
- 参与者被随机分为1:1接受通过iNCDSS或高级内分泌医生为期5天的胰岛素定位.
- 主要结局是时间在目标葡萄糖范围 (70-180 mg/dL) 内的比例.
主要成果:
- iNCDSS组在目标葡萄糖范围的平均时间达到76.4%,而医生组的平均时间为73.6%,符合非劣等性标准.
- 在iNCDSS和医生组之间没有观察到不良事件的显著差异.
- 医生对iNCDSS表示满意,并指出其清晰度,节省时间,有效性和安全性.
结论:
- 在入院T2D患者的胰岛素定位方面,iNCDSS证明了与专家医生管理的非劣势.
- 这种由人工智能驱动的系统显示出作为优化胰岛素治疗和血糖控制的宝贵工具的潜力.
- 这些发现支持将AI决策支持系统集成到T2D管理的临床实践中.
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