Department of Women's and Children's Health, Dunedin School of Medicine, University of Otago, 201 Great King St, Dunedin, Otago, 9016, New Zealand.
Department of Endocrinology and Diabetes, North Shore Hospital, Te Whatu Ora Waitemata , Auckland, New Zealand.
BMC Endocr Disord. 2024 Aug 30;24(1):167. doi: 10.1186/s12902-024-01709-y.
Multiple clinician adjustable parameters impact upon glycemia in people with type 1 diabetes (T1D) using Medtronic Mini Med 780G (MM780G) AHCL. These include glucose targets, carbohydrate ratios (CR), and active insulin time (AIT). Algorithm-based decision support advising upon potential settings adjustments may enhance clinical decision-making.
Single-arm, two-phase exploratory study developing decision support to commence and sustain AHCL. Participants commenced investigational MM780G, then 8 weeks Phase 1-initial optimization tool evaluation, involving algorithm-based decision support with weekly AIT and CR recommendations. Clinicians approved or rejected CR and AIT recommendations based on perceived safety per protocol. Co-design resulted in a refined algorithm evaluated in a further identically configured Phase 2. Phase 2 participants also transitioned to commercial MM780G following "Quick Start" (algorithm-derived tool determining initial AHCL settings using daily insulin dose and weight). We assessed efficacy, safety, and acceptability of decision support using glycemic metrics, and the proportion of accepted CR and AIT settings per phase.
Fifty three participants commenced Phase 1 (mean age 24.4; Hba1c 61.5mmol/7.7%). The proportion of CR and AIT accepted by clinicians increased between Phases 1 and 2 respectively: CR 89.2% vs. 98.6%, p < 0.01; AIT 95.2% vs. 99.3%, p < 0.01. Between Phases, mean glucose percentage time < 3.9mmol (< 70mg/dl) reduced (2.1% vs. 1.4%, p = 0.04); change in mean TIR 3.9-10mmol/L (70-180mg/dl) was not statistically significant: 72.9% ± 7.8 and 73.5% ± 8.6. Quick start resulted in stable TIR, and glycemic metrics compared to international guidelines.
The co-designed decision support tools were able to deliver safe and effective therapy. They can potentially reduce the burden of diabetes management related decision making for both health care practitioners and patients.
Prospectively registered with Australia/New Zealand Clinical Trials Registry(ANZCTR) on 30th March 2021 as study ACTRN12621000360819.
使用美敦力 MiniMed 780G（MM780G）自动皮下输注（AHCL）的 1 型糖尿病（T1D）患者，多个临床医生可调节参数会影响血糖。这些参数包括血糖目标、碳水化合物比值（CR）和活跃胰岛素时间（AIT）。基于算法的决策支持可以为潜在的设置调整提供建议，从而增强临床决策。
这项单臂、两阶段的探索性研究旨在开发启动和维持 AHCL 的决策支持工具。参与者开始使用研究性的 MM780G，然后进行 8 周的第 1 阶段-初始优化工具评估，涉及基于算法的决策支持，每周提供 AIT 和 CR 建议。临床医生根据协议规定的安全性，批准或拒绝 CR 和 AIT 建议。共同设计产生了一种经过改进的算法，在进一步相同配置的第 2 阶段进行评估。第 2 阶段的参与者在“快速启动”（使用每日胰岛素剂量和体重确定初始 AHCL 设置的算法驱动工具）后也转换为商业 MM780G。我们使用血糖指标评估决策支持的疗效、安全性和可接受性，并评估每个阶段接受的 CR 和 AIT 设置的比例。
53 名参与者开始进入第 1 阶段（平均年龄 24.4 岁；HbA1c 61.5mmol/7.7%）。临床医生接受的 CR 和 AIT 比例在第 1 阶段和第 2 阶段分别增加：CR 分别为 89.2%和 98.6%，p<0.01；AIT 分别为 95.2%和 99.3%，p<0.01。在两个阶段之间，血糖百分比时间<3.9mmol（<70mg/dl）的平均值减少（2.1%比 1.4%，p=0.04）；3.9-10mmol/L（70-180mg/dl）的平均 TIR 变化无统计学意义：72.9%±7.8%和 73.5%±8.6%。与国际指南相比，快速启动可使 TIR 和血糖指标稳定。
共同设计的决策支持工具能够提供安全有效的治疗。它们可以减少医疗保健从业者和患者在糖尿病管理相关决策方面的负担。
2021 年 3 月 30 日在澳大利亚/新西兰临床试验注册中心（ANZCTR）前瞻性注册，注册号为 ACTRN12621000360819。
