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基于手势算法的自动胰岛素输送系统及自动餐食推注功能。

An Automated Insulin Delivery System with Automatic Meal Bolus Based on a Hand-Gesturing Algorithm.

机构信息

Medtronic Diabetes, Northridge, California, USA.

Division of Endocrinology, Diabetes, and Metabolism, Sheba Medical Center and Tel-Aviv University School of Medicine, Tel-Aviv, Israel.

出版信息

Diabetes Technol Ther. 2024 Sep;26(9):633-643. doi: 10.1089/dia.2023.0529. Epub 2024 Mar 12.

Abstract

Carbohydrate counting (CC) and meal announcements, before eating, introduce a significant burden for individuals managing type 1 diabetes (T1D). An automated insulin delivery system with automatic bolusing that eliminates the need for CC and premeal bolusing (i.e., a hands-free closed-loop [HFCL] system) was assessed in a feasibility trial of adults with T1D. The system included the MiniMed™ 780G pump and a smartphone-paired smartwatch with the Klue application (Klue, Inc.) that detects eating and drinking gestures. A smartphone algorithm converted gestures into carb amounts that were transmitted to the pump for automatic bolusing. For 5 days, participants ( = 17, 18-75 years of age) used the system at home with meal announcements based on traditional CC, with the Klue application disabled (Home-stay phase). Thereafter, participants moved to a supervised hotel setting, where the Klue application was enabled for 5 days and meals were not announced (Hotel-stay phase). Participants consumed the same eight test meals (six solid and two liquid) of varying caloric and carb size at the same time and day of the week for both phases, and glycemic metrics were compared. Otherwise, there were no other meal restrictions. The overall time in range (70-180 mg/dL) was 83.4% ± 7.0% and 80.6% ± 6.7% for the Home-stay and Hotel-stay, respectively ( = 0.08). The average time at <70 mg/dL was 3.1% and 3.0% ( = 0.9144), respectively, and the average time at >180 mg/dL was 13.5% and 16.3% ( = 0.1046), respectively. Postprandial glycemia following low-carb test meals was similar between the two phases. The system's ability to accommodate high-carb meals was somewhat limited. There were no episodes of severe hypoglycemia or diabetic ketoacidosis. Preliminary findings show that a HFCL system was safe and maintained overall glycemic control, similar to that observed with traditional CC and manual meal bolusing. By eliminating these daily T1D burdens, a HFCL system may improve quality of life for individuals with T1D. ClinicalTrials.gov number: NCT04964128.

摘要

碳水化合物计数 (CC) 和餐前告知是 1 型糖尿病 (T1D) 患者管理血糖的重要手段。本研究旨在评估一种自动胰岛素输送系统(无需 CC 且无需餐前推注,即无接触闭环 [HFCL] 系统)的可行性,该系统包含 MiniMed™ 780G 泵和一个与 Klue 应用程序配对的智能手机智能手表,该手表可以检测进食和饮水动作。智能手机算法将动作转换为碳水化合物量,并将其传输至泵以实现自动推注。在为期 5 天的居家研究期间,参与者( = 17 名年龄 18-75 岁的 T1D 患者)使用该系统,按照传统 CC 进行餐前告知(居家研究阶段),同时 Klue 应用程序被禁用。之后,参与者被转移到一个经过监督的酒店环境中,在那里启用 Klue 应用程序 5 天,且不进行餐前告知(酒店研究阶段)。在两个阶段,参与者在同一周的同一时间进食相同的八种测试餐(六种固体和两种液体),并比较血糖指标。此外,不限制其他饮食。整体血糖达标时间(70-180mg/dL)分别为 83.4% ± 7.0%和 80.6% ± 6.7%( = 0.08)。血糖<70mg/dL 的平均时间分别为 3.1%和 3.0%( = 0.9144),血糖>180mg/dL 的平均时间分别为 13.5%和 16.3%( = 0.1046)。低碳水化合物测试餐后的餐后血糖在两个阶段相似。该系统适应高碳水化合物餐的能力有些受限。没有发生严重低血糖或糖尿病酮症酸中毒的情况。初步结果表明,HFCL 系统是安全的,能够维持整体血糖控制,与传统 CC 和手动餐前推注相似。通过消除这些日常的 T1D 负担,HFCL 系统可能会提高 T1D 患者的生活质量。临床试验注册号:NCT04964128。

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