IEEE Trans Biomed Eng. 2018 Mar;65(3):479-488. doi: 10.1109/TBME.2017.2652062. Epub 2017 Jan 11.
Contemporary and future outpatient long-term artificial pancreas (AP) studies need to cope with the well-known large intra- and interday glucose variability occurring in type 1 diabetic (T1D) subjects. Here, we propose an adaptive model predictive control (MPC) strategy to account for it and test it in silico.
A run-to-run (R2R) approach adapts the subcutaneous basal insulin delivery during the night and the carbohydrate-to-insulin ratio (CR) during the day, based on some performance indices calculated from subcutaneous continuous glucose sensor data. In particular, R2R aims, first, to reduce the percentage of time in hypoglycemia and, secondarily, to improve the percentage of time in euglycemia and average glucose. In silico simulations are performed by using the University of Virginia/Padova T1D simulator enriched by incorporating three novel features: intra- and interday variability of insulin sensitivity, different distributions of CR at breakfast, lunch, and dinner, and dawn phenomenon.
After about two months, using the R2R approach with a scenario characterized by a random 30% variation of the nominal insulin sensitivity the time in range and the time in tight range are increased by 11.39% and 44.87%, respectively, and the time spent above 180 mg/dl is reduced by 48.74%.
An adaptive MPC algorithm based on R2R shows in silico great potential to capture intra- and interday glucose variability by improving both overnight and postprandial glucose control without increasing hypoglycemia.
Making an AP adaptive is key for long-term real-life outpatient studies. These good in silico results are very encouraging and worth testing in vivo.
当代和未来的门诊长期人工胰腺（AP）研究需要应对 1 型糖尿病（T1D）患者中众所周知的日内和日间血糖变异性大的问题。在这里，我们提出了一种自适应模型预测控制（MPC）策略来解决这个问题，并在计算机上进行了测试。
基于从皮下连续葡萄糖传感器数据计算得出的一些性能指标，运行到运行（R2R）方法调整夜间的皮下基础胰岛素输送和日间的碳水化合物与胰岛素比值（CR）。特别是，R2R 的目标首先是减少低血糖时间的百分比，其次是提高血糖正常时间的百分比和平均血糖。通过使用包含三个新特征的弗吉尼亚大学/帕多瓦 T1D 模拟器进行了计算机模拟：胰岛素敏感性的日内和日间变异性、早餐、午餐和晚餐时 CR 的不同分布以及黎明现象。
使用 R2R 方法大约两个月后，对于胰岛素敏感性名义值有 30%随机变化的场景，时间在范围内和时间在严格范围内分别增加了 11.39%和 44.87%，而血糖超过 180mg/dl 的时间减少了 48.74%。
基于 R2R 的自适应 MPC 算法具有很大的潜力，可以通过改善夜间和餐后血糖控制来捕捉日内和日间血糖变异性，同时不会增加低血糖。
使 AP 自适应是长期门诊真实生活研究的关键。这些良好的计算机模拟结果非常令人鼓舞，值得在体内进行测试。
