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自适应生物行为控制:1 型糖尿病人机共适应的初步分析。

Adaptive Biobehavioral Control: A Pilot Analysis of Human-Machine Coadaptation in Type 1 Diabetes.

机构信息

Center for Diabetes Technology, University of Virginia, Charlottesville, Virginia, USA.

Dexcom Inc, San Diego, California, USA.

出版信息

Diabetes Technol Ther. 2024 Sep;26(9):644-651. doi: 10.1089/dia.2023.0399. Epub 2024 Apr 30.

Abstract

While it is well recognized that an automated insulin delivery (AID) algorithm should adapt to changes in physiology, it is less understood that the individual would also have to adapt to the AID system. The adaptive biobehavioral control (ABC) method presented here attempts to compensate for this deficiency by including AID into an information cloud-based ecosystem. The Web Information Tool (WIT) implements the ABC concept via the following: (1) a Physiological Adaptation Module (PAM) that tracks metabolic changes and adapts AID parameters accordingly and (2) a Behavioral Adaptation Module (BAM) that provides information feedback. The safety of WIT (primary outcome) was assessed in an 8-week randomized, two-arm parallel pilot study. All participants used the Control-IQ AID system enhanced with PAM, but only those in the Experimental group had access to BAM. Secondary glycemic outcomes were computed using the 2-week baseline period and the last 2 weeks of treatment. Thirty participants with type 1 diabetes (T1D) completed all study procedures (17 female/13 male; age: 40 ± 14 years; HbA1c: 6.6% ± 0.5%). No severe hypoglycemia, DKA, or other serious adverse events were reported. Comparing the Experimental and Control groups, no significant difference was observed in time in range (70-180 mg/dL): 74.6% vs 73.8%, adjusted mean difference: 2.65%, 95% CI (-1.12%,6.41%), = 0.161. Time in 70-140 mg/dL was significantly higher in the Experimental group: 50.7% vs 49.2%, 5.71% (0.44%,10.97%), = 0.035, without increased time below range: 0.54% (-0.09%,1.17%), = 0.089. The results demonstrate that it is safe to integrate an AID system into the WIT ecosystem. Validation in a full-scale study is ongoing.

摘要

虽然人们普遍认识到自动化胰岛素输送(AID)算法应该适应生理变化,但人们对个体也必须适应 AID 系统的认识还不够。本文提出的自适应生物行为控制(ABC)方法试图通过将 AID 纳入基于信息云的生态系统来弥补这一不足。Web 信息工具(WIT)通过以下方式实现 ABC 概念:(1)生理适应模块(PAM),跟踪代谢变化并相应调整 AID 参数,(2)行为适应模块(BAM),提供信息反馈。WIT 的安全性(主要结果)在一项为期 8 周的随机、双臂平行试点研究中进行了评估。所有参与者都使用了增强了 PAM 的 Control-IQ AID 系统,但只有实验组可以访问 BAM。次要血糖结果使用 2 周的基线期和治疗的最后 2 周计算。30 名 1 型糖尿病(T1D)患者完成了所有研究程序(17 名女性/13 名男性;年龄:40±14 岁;HbA1c:6.6%±0.5%)。没有报告严重低血糖、DKA 或其他严重不良事件。比较实验组和对照组,时间在范围内(70-180mg/dL)没有显著差异:74.6%对 73.8%,调整后的平均差异:2.65%,95%CI(-1.12%,6.41%),=0.161。实验组时间在 70-140mg/dL 显著更高:50.7%对 49.2%,5.71%(0.44%,10.97%),=0.035,没有增加低于范围的时间:0.54%(-0.09%,1.17%),=0.089。结果表明,将 AID 系统集成到 WIT 生态系统中是安全的。正在进行全面研究的验证。

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