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采用皮下葡萄糖传感与胰岛素输注以及模型预测控制算法的闭环人工胰腺:弗吉尼亚州的经验。

Closed-loop artificial pancreas using subcutaneous glucose sensing and insulin delivery and a model predictive control algorithm: the Virginia experience.

作者信息

Clarke William L, Anderson Stacey, Breton Marc, Patek Stephen, Kashmer Laurissa, Kovatchev Boris

机构信息

Division of Pediatric Endocrinology, Department of Pediatrics, University of Virginia Health Sciences Center, Charlottesville, Virginia 22908, USA.

出版信息

J Diabetes Sci Technol. 2009 Sep 1;3(5):1031-8. doi: 10.1177/193229680900300506.

Abstract

BACKGROUND

Recent progress in the development of clinically accurate continuous glucose monitors (CGMs), automated continuous insulin infusion pumps, and control algorithms for calculating insulin doses from CGM data have enabled the development of prototypes of subcutaneous closed-loop systems for controlling blood glucose (BG) levels in type 1 diabetes. The use of a new personalized model predictive control (MPC) algorithm to determine insulin doses to achieve and maintain BG levels between 70 and 140 mg/dl overnight and to control postprandial BG levels is presented.

METHODS

Eight adults with type 1 diabetes were studied twice, once using their personal open-loop systems to control BG overnight and for 4 h following a standardized meal and once using a closed-loop system that utilizes the MPC algorithm to control BG overnight and for 4 h following a standardized meal. Average BG levels, percentage of time within BG target of 70-140 mg/dl, number of hypoglycemia episodes, and postprandial BG excursions during both study periods were compared.

RESULTS

With closed-loop control, once BG levels achieved the target range (70-140 mg/dl), they remained within that range throughout the night in seven of the eight subjects. One subject developed a BG level of 65 mg/dl, which was signaled by the CGM trend analysis, and the MPC algorithm directed the discontinuance of the insulin infusion. The number of overnight hypoglycemic events was significantly reduced (p = .011) with closed-loop control. Postprandial BG excursions were similar during closed-loop and open-loop control.

CONCLUSION

Model predictive closed-loop control of BG levels can be achieved overnight and following a standardized breakfast meal. This "artificial pancreas" controls BG levels as effectively as patient-directed open-loop control following a morning meal but is significantly superior to open-loop control in preventing overnight hypoglycemia.

摘要

背景

临床上精确的连续血糖监测仪(CGM)、自动连续胰岛素输注泵以及根据CGM数据计算胰岛素剂量的控制算法的最新进展,使得开发用于控制1型糖尿病患者血糖(BG)水平的皮下闭环系统原型成为可能。本文介绍了一种新的个性化模型预测控制(MPC)算法,该算法用于确定胰岛素剂量,以在夜间将BG水平维持在70至140mg/dl之间,并控制餐后BG水平。

方法

对8名1型糖尿病成年患者进行了两次研究,一次使用他们的个人开环系统在夜间和标准化餐后4小时控制BG,另一次使用利用MPC算法的闭环系统在夜间和标准化餐后4小时控制BG。比较了两个研究期间的平均BG水平、BG在70 - 140mg/dl目标范围内的时间百分比、低血糖发作次数以及餐后BG波动情况。

结果

采用闭环控制时,8名受试者中有7名在BG水平达到目标范围(70 - 140mg/dl)后,整夜都保持在该范围内。一名受试者的BG水平降至65mg/dl,CGM趋势分析发出信号,MPC算法指示停止胰岛素输注。闭环控制使夜间低血糖事件的数量显著减少(p = 0.011)。闭环控制和开环控制期间的餐后BG波动相似。

结论

通过模型预测实现的BG水平闭环控制可以在夜间和标准化早餐后实现。这种“人工胰腺”控制BG水平的效果与患者自主的开环早餐后控制效果相当,但在预防夜间低血糖方面明显优于开环控制。

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