Keenan D Barry, Grosman Benyamin, Clark Harry W, Roy Anirban, Weinzimer Stuart A, Shah Rajiv V, Mastrototaro John J
Medtronic MiniMed, Northridge, California 91325, USA. barry.keenan@ medtronic.com
J Diabetes Sci Technol. 2011 Nov 1;5(6):1327-36. doi: 10.1177/193229681100500603.
Commercialization of a closed-loop artificial pancreas system that employs continuous subcutaneous insulin infusion and interstitial fluid glucose sensing has been encumbered by state-of-the-art technology. Continuous glucose monitoring (CGM) devices with improved accuracy could significantly advance development efforts. However, the current accuracy of CGM devices might be adequate for closed-loop control.
The influence that known CGM limitations have on closed-loop control was investigated by integrating sources of sensor inaccuracy with the University of Virginia Padova Diabetes simulator. Non-glucose interference, physiological time lag and sensor error measurements, selected from 83 Enlite™ glucose sensor recordings with the Guardian® REAL-Time system, were used to modulate simulated plasma glucose signals. The effect of sensor accuracy on closed-loop controller performance was evaluated in silico, and contrasted with closed-loop clinical studies during the nocturnal control period.
Based on n = 2472 reference points, a mean sensor error of 14% with physiological time lags of 3.28 ± 4.62 min (max 13.2 min) was calculated for simulation. Sensor bias reduced time in target for both simulation and clinical experiments. In simulation, additive error increased time <70 mg/dl and >180 mg/dl by 0.2% and 5.6%, respectively. In-clinic, the greatest low blood glucose index values (max = 5.9) corresponded to sensor performance.
Sensors have sufficient accuracy for closed-loop control, however, algorithms are necessary to effectively calibrate and detect erroneous calibrations and failing sensors. Clinical closed-loop data suggest that control with a higher target of 140 mg/dl during the nocturnal period could significantly reduce the risk for hypoglycemia.
采用持续皮下胰岛素输注和组织间液葡萄糖传感的闭环人工胰腺系统的商业化一直受到现有技术的阻碍。具有更高准确性的连续血糖监测(CGM)设备可能会显著推动研发工作。然而,当前CGM设备的准确性可能足以用于闭环控制。
通过将传感器不准确的来源与弗吉尼亚大学帕多瓦糖尿病模拟器相结合,研究了已知CGM局限性对闭环控制的影响。从83个使用Guardian®实时系统的Enlite™葡萄糖传感器记录中选取的非葡萄糖干扰、生理时间滞后和传感器误差测量值,用于调制模拟血浆葡萄糖信号。在计算机模拟中评估了传感器准确性对闭环控制器性能的影响,并与夜间控制期的闭环临床研究进行了对比。
基于n = 2472个参考点,计算出模拟的平均传感器误差为14%,生理时间滞后为3.28±4.62分钟(最大13.2分钟)。传感器偏差减少了模拟和临床实验中处于目标范围内的时间。在模拟中,附加误差使血糖<70 mg/dl和>180 mg/dl的时间分别增加了0.2%和5.6%。在临床中,最大的低血糖指数值(最大值 = 5.9)与传感器性能相对应。
传感器对于闭环控制具有足够的准确性,然而,需要算法来有效校准和检测错误的校准以及故障传感器。临床闭环数据表明,夜间将目标值提高到140 mg/dl进行控制可显著降低低血糖风险。