Fushimi Emilia, Colmegna Patricio, De Battista Hernán, Garelli Fabricio, Sánchez-Peña Ricardo
Grupo de Control Aplicado (GCA), Instituto LEICI (UNLP-CONICET), Facultad de Ingeniería, Universidad Nacional de La Plata (UNLP), Argentina.
Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) Argentina.
J Diabetes Sci Technol. 2019 Nov;13(6):1035-1043. doi: 10.1177/1932296819864585. Epub 2019 Jul 24.
Either under standard basal-bolus treatment or hybrid closed-loop control, subjects with type 1 diabetes are required to count carbohydrates (CHOs). However, CHO counting is not only burdensome but also prone to errors. Recently, an artificial pancreas algorithm that does not require premeal insulin boluses-the so-called automatic regulation of glucose (ARG)-was introduced. In its first pilot clinical study, although the exact CHO counting was not required, subjects still needed to announce the meal time and classify the meal size.
An automatic switching signal generator (SSG) is proposed in this work to remove the manual mealtime announcement from the control strategy. The SSG is based on a Kalman filter and works with continuous glucose monitoring readings only.
The ARG algorithm with unannounced meals (ARG) was tested under the effect of different types of mixed meals and intrapatient variability, and contrasted with the ARG algorithm with announced meals (ARG). Simulations reveal that, for slow-absorbing meals, the time in the euglycemic range, [70-180] mg/dL, increases using the unannounced strategy (ARG: 78.1 [68.6-80.2]% (median [IQR]) and ARG: 87.8 [84.5-90.6]%), while similar results were found with fast-absorbing meals (ARG: 87.4 [86.0-88.9]% and ARG: 87.6 [86.1-88.8]%). On the other hand, when intrapatient variability is considered, time in euglycemia is also comparable (ARG: 81.4 [75.4-83.5]% and ARG: 80.9 [77.0-85.1]%).
results indicate that it is feasible to perform an in vivo evaluation of the ARG algorithm with unannounced meals.
无论是在标准基础-餐时胰岛素治疗还是混合闭环控制下，1型糖尿病患者都需要计算碳水化合物（CHO）含量。然而，计算CHO含量不仅繁琐，而且容易出错。最近，一种无需餐前大剂量胰岛素的人工胰腺算法——即所谓的葡萄糖自动调节（ARG）算法被引入。在其首次试点临床研究中，尽管不需要精确计算CHO含量，但患者仍需告知用餐时间并对餐量进行分类。
本研究提出了一种自动切换信号发生器（SSG），以从控制策略中去除手动用餐时间告知环节。该SSG基于卡尔曼滤波器，仅与连续血糖监测读数配合使用。
在不同类型混合餐和患者个体差异的影响下，对不告知用餐情况的ARG算法（ARG）进行了测试，并与告知用餐情况的ARG算法（ARG）进行了对比。模拟结果显示，对于吸收缓慢的餐食，采用不告知策略时，血糖正常范围[70-180]mg/dL内的时间增加（ARG：78.1[68.6-80.2]%（中位数[四分位间距]），ARG：87.8[84.5-90.6]%），而对于吸收快速的餐食，也得到了类似结果（ARG：87.4[86.0-88.9]%，ARG：87.6[86.1-88.8]%）。另一方面，考虑患者个体差异时，血糖正常时间也具有可比性（ARG：81.4[75.4-83.5]%，ARG：80.9[77.0-85.1]%）。
结果表明，对不告知用餐情况的ARG算法进行体内评估是可行的。
