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使用基于人工智能的自动化决策支持系统优化青少年 1 型糖尿病患者的胰岛素剂量。

Insulin dose optimization using an automated artificial intelligence-based decision support system in youths with type 1 diabetes.

机构信息

The Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel.

Department of Endocrinology, Diabetes and Metabolic Diseases, UMC-University Children's Hospital Ljubljana, and Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.

出版信息

Nat Med. 2020 Sep;26(9):1380-1384. doi: 10.1038/s41591-020-1045-7. Epub 2020 Sep 9.

Abstract

Despite the increasing adoption of insulin pumps and continuous glucose monitoring devices, most people with type 1 diabetes do not achieve their glycemic goals. This could be related to a lack of expertise or inadequate time for clinicians to analyze complex sensor-augmented pump data. We tested whether frequent insulin dose adjustments guided by an automated artificial intelligence-based decision support system (AI-DSS) is as effective and safe as those guided by physicians in controlling glucose levels. ADVICE4U was a six-month, multicenter, multinational, parallel, randomized controlled, non-inferiority trial in 108 participants with type 1 diabetes, aged 10-21 years and using insulin pump therapy (ClinicalTrials.gov no. NCT03003806). Participants were randomized 1:1 to receive remote insulin dose adjustment every three weeks guided by either an AI-DSS, (AI-DSS arm, n = 54) or by physicians (physician arm, n = 54). The results for the primary efficacy measure-the percentage of time spent within the target glucose range (70-180 mg dl (3.9-10.0 mmol l))-in the AI-DSS arm were statistically non-inferior to those in the physician arm (50.2 ± 11.1% versus 51.6 ± 11.3%, respectively, P < 1 × 10). The percentage of readings below 54 mg dl (<3.0 mmol l) within the AI-DSS arm was statistically non-inferior to that in the physician arm (1.3 ± 1.4% versus 1.0 ± 0.9%, respectively, P < 0.0001). Three severe adverse events related to diabetes (two severe hypoglycemia, one diabetic ketoacidosis) were reported in the physician arm and none in the AI-DSS arm. In conclusion, use of an automated decision support tool for optimizing insulin pump settings was non-inferior to intensive insulin titration provided by physicians from specialized academic diabetes centers.

摘要

尽管胰岛素泵和连续血糖监测设备的应用日益增多,但大多数 1 型糖尿病患者仍未达到血糖目标。这可能与临床医生缺乏专业知识或分析复杂传感器增强型泵数据的时间不足有关。我们测试了基于自动化人工智能决策支持系统 (AI-DSS) 的频繁胰岛素剂量调整是否与医生指导的剂量调整一样有效和安全,可以控制血糖水平。ADVICE4U 是一项为期 6 个月、多中心、多国、平行、随机对照、非劣效性试验,纳入了 108 名年龄在 10-21 岁、使用胰岛素泵治疗的 1 型糖尿病患者(ClinicalTrials.gov 编号:NCT03003806)。参与者以 1:1 的比例随机分为两组,分别接受每 3 周远程胰岛素剂量调整,一组由 AI-DSS 指导(AI-DSS 组,n=54),另一组由医生指导(医生组,n=54)。主要疗效指标(目标血糖范围内的时间百分比[70-180mg/dl(3.9-10.0mmol/l)])的结果显示,AI-DSS 组与医生组相比具有统计学非劣效性(分别为 50.2±11.1%和 51.6±11.3%,P<1×10)。AI-DSS 组读数低于 54mg/dl(<3.0mmol/l)的百分比与医生组相比具有统计学非劣效性(分别为 1.3±1.4%和 1.0±0.9%,P<0.0001)。医生组报告了 3 例与糖尿病相关的严重不良事件(2 例严重低血糖,1 例糖尿病酮症酸中毒),而 AI-DSS 组无严重不良事件报告。总之,使用自动化决策支持工具优化胰岛素泵设置与来自专门学术糖尿病中心的医生进行的强化胰岛素滴定一样有效。

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