Harvey Rebecca A, Dassau Eyal, Zisser Howard, Seborg Dale E, Doyle Francis J
Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, CA, USA Sansum Diabetes Research Institute, Santa Barbara, CA, USA.
Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, CA, USA Biomolecular Science & Engineering Program, University of California, Santa Barbara, Santa Barbara, CA, USA Sansum Diabetes Research Institute, Santa Barbara, CA, USA.
J Diabetes Sci Technol. 2014 Mar;8(2):307-320. doi: 10.1177/1932296814523881. Epub 2014 Mar 13.
The Glucose Rate Increase Detector (GRID), a module of the Health Monitoring System (HMS), has been designed to operate in parallel to the glucose controller to detect meal events and safely trigger a meal bolus. The GRID algorithm was tuned on clinical data with 40-70 g CHO meals and tested on simulation data with 50-100 g CHO meals. Active closed- and open-loop protocols were executed in silico with various treatments, including automatic boluses based on a 75 g CHO meal and boluses based on simulated user input of meal size. An optional function was used to reduce the recommended bolus using recent insulin and glucose history. For closed-loop control of a 3-meal scenario (50, 75, and 100 g CHO), the GRID improved median time in the 80-180 mg/dL range by 17% and in the >180 range by 14% over unannounced meals, using an automatic bolus for a 75 g CHO meal at detection. Under open-loop control of a 75 g CHO meal, the GRID shifted the median glucose peak down by 73 mg/dL and earlier by 120 min and reduced the time >180 mg/dL by 57% over a missed-meal bolus scenario, using a full meal bolus at detection. The GRID improved closed-loop control in the presence of large meals, without increasing late postprandial hypoglycemia. Users of basal-bolus therapy could also benefit from GRID as a safety alert for missed meal corrections.
葡萄糖速率增加检测器（GRID）是健康监测系统（HMS）的一个模块，其设计目的是与葡萄糖控制器并行运行，以检测进餐事件并安全触发进餐大剂量注射。GRID算法在含40 - 70克碳水化合物（CHO）的进餐临床数据上进行了调整，并在含50 - 100克CHO的进餐模拟数据上进行了测试。在计算机模拟中执行了主动闭环和开环协议，采用了各种治疗方法，包括基于75克CHO进餐的自动大剂量注射以及基于模拟用户输入进餐量的大剂量注射。使用了一个可选功能，根据近期胰岛素和葡萄糖历史记录减少推荐的大剂量注射。对于三餐情况（50、75和100克CHO）的闭环控制，与未通知的进餐相比，GRID在检测到75克CHO进餐后使用自动大剂量注射，使血糖在80 - 180毫克/分升范围内的中位时间提高了17%，在大于180毫克/分升范围内提高了14%。在75克CHO进餐的开环控制下，与错过进餐大剂量注射的情况相比，GRID在检测到进餐后使用全餐大剂量注射，使血糖峰值中位数降低了73毫克/分升，提前了120分钟，并使血糖大于180毫克/分升的时间减少了57%。GRID在存在大量进餐的情况下改善了闭环控制，而不会增加餐后晚期低血糖。基础 - 大剂量疗法的使用者也可以将GRID作为错过进餐校正的安全警报而从中受益。
