Clinical evaluation of a personalized artificial pancreas.
Clinical evaluation of a personalized artificial pancreas.
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DOI：
10.2337/dc12-0948
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发表时间：
2013-04
期刊：
影响因子：
16.2
通讯作者：
Doyle FJ 3rd
中科院分区：
文献类型：
--
作者：
Dassau E;Zisser H;Harvey RA;Percival MW;Grosman B;Bevier W;Atlas E;Miller S;Nimri R;Jovanovic L;Doyle FJ 3rd
自动调节血糖的人工胰腺（AP）将极大地改善糖尿病患者的生活。这种装置可以预防低血糖和高血糖以及相关的长期和短期并发症，并减轻频繁血糖测量和胰岛素注射的一些日常负担。我们进行了一项试点临床试验，评估使用商业设备的个性化、全自动 AP。使用模型预测控制的多参数公式和机载胰岛素算法进行了两项试验（n = 22，n受试者 = 17），以便控制算法或“大脑”可以嵌入芯片上作为未来移动设备的一部分。该协议评估了控制算法的三个主要挑战：1）从各种初始血糖水平使血糖正常化，2）维持血糖正常，3）克服未经通知的30±5克碳水化合物的膳食。初始葡萄糖值范围为 84–251 mg/dL。平均 70% 的试验时间中，血糖保持在接近正常范围 (80–180 mg/dL)。低血糖指数为0.34，高血糖指数为5.1。这些令人鼓舞的短期结果揭示了针对个体血糖特征量身定制的控制算法能够成功调节血糖，即使在面临未经通知的进餐或初始高血糖时也是如此。据我们所知，这代表了第一个真正的全自动多参数模型预测控制算法，具有机载胰岛素，不依赖用户干预来调节 1 型糖尿病患者的血糖。
An artificial pancreas (AP) that automatically regulates blood glucose would greatly improve the lives of individuals with diabetes. Such a device would prevent hypo- and hyperglycemia along with associated long- and short-term complications as well as ease some of the day-to-day burden of frequent blood glucose measurements and insulin administration. We conducted a pilot clinical trial evaluating an individualized, fully automated AP using commercial devices. Two trials (n = 22, nsubjects = 17) were conducted using a multiparametric formulation of model predictive control and an insulin-on-board algorithm such that the control algorithm, or “brain,” can be embedded on a chip as part of a future mobile device. The protocol evaluated the control algorithm for three main challenges: 1) normalizing glycemia from various initial glucose levels, 2) maintaining euglycemia, and 3) overcoming an unannounced meal of 30 ± 5 g carbohydrates. Initial glucose values ranged from 84–251 mg/dL. Blood glucose was kept in the near-normal range (80–180 mg/dL) for an average of 70% of the trial time. The low and high blood glucose indices were 0.34 and 5.1, respectively. These encouraging short-term results reveal the ability of a control algorithm tailored to an individual’s glucose characteristics to successfully regulate glycemia, even when faced with unannounced meals or initial hyperglycemia. To our knowledge, this represents the first truly fully automated multiparametric model predictive control algorithm with insulin-on-board that does not rely on user intervention to regulate blood glucose in individuals with type 1 diabetes.
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影响因子：
16.2
作者：
Castle JR;Engle JM;El Youssef J;Massoud RG;Yuen KC;Kagan R;Ward WK
通讯作者：
Ward WK
影响因子：
16.2
作者：
Atlas E;Nimri R;Miller S;Grunberg EA;Phillip M
通讯作者：
Phillip M
影响因子：
4.3
作者：
Dua, P.;Kouramas, K.;Pistikopoulos, E. N.
通讯作者：
Pistikopoulos, E. N.
影响因子：
4.6
作者：
Dua, Pinky;Doyle, Francis J., III;Pistikopoulos, Efstratios N.
通讯作者：
Pistikopoulos, Efstratios N.
影响因子：
3.2
作者：
Dua, Pinky;Doyle, Francis J., III;Pistikopoulos, Efstratios N.
通讯作者：
Pistikopoulos, Efstratios N.