Cameron Fraser, Niemeyer Günter, Wilson Darrell M, Bequette B Wayne, Benassi Kari S, Clinton Paula, Buckingham Bruce A
1 Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute , Troy, New York.
Diabetes Technol Ther. 2014 Nov;16(11):728-34. doi: 10.1089/dia.2014.0093. Epub 2014 Sep 26.
Closed-loop control of blood glucose levels in people with type 1 diabetes offers the potential to reduce the incidence of diabetes complications and reduce the patients' burden, particularly if meals do not need to be announced. We therefore tested a closed-loop algorithm that does not require meal announcement.
A multiple model probabilistic predictive controller (MMPPC) was assessed on four patients, revised to improve performance, and then assessed on six additional patients. Each inpatient admission lasted for 32 h with five unannounced meals containing approximately 1 g/kg of carbohydrate per admission. The system used an Abbott Diabetes Care (Alameda, CA) Navigator(®) continuous glucose monitor (CGM) and Insulet (Bedford, MA) Omnipod(®) insulin pump, with the MMPPC implemented through the artificial pancreas system platform. The controller was initialized only with the patient's total daily dose and daily basal pattern.
On a 24-h basis, the first cohort had mean reference and CGM readings of 179 and 167 mg/dL, respectively, with 53% and 62%, respectively, of readings between 70 and 180 mg/dL and four treatments for glucose values <70 mg/dL. The second cohort had mean reference and CGM readings of 161 and 142 mg/dL, respectively, with 63% and 78%, respectively, of the time spent euglycemic. There was one controller-induced hypoglycemic episode. For the 30 unannounced meals in the second cohort, the mean reference and CGM premeal, postmeal maximum, and 3-h postmeal values were 139 and 132, 223 and 208, and 168 and 156 mg/dL, respectively.
The MMPPC, tested in-clinic against repeated, large, unannounced meals, maintained reasonable glycemic control with a mean blood glucose level that would equate to a mean glycated hemoglobin value of 7.2%, with only one controller-induced hypoglycemic event occurring in the second cohort.
对1型糖尿病患者进行血糖水平的闭环控制有可能降低糖尿病并发症的发生率并减轻患者负担，尤其是在无需提前告知用餐情况时。因此，我们测试了一种无需提前告知用餐情况的闭环算法。
对4名患者评估了一种多模型概率预测控制器（MMPPC），对其进行修订以改善性能，然后又对另外6名患者进行了评估。每次住院持续32小时，期间有5次未提前告知的用餐，每次用餐含碳水化合物约1克/千克。该系统使用雅培糖尿病护理公司（加利福尼亚州阿拉米达）的Navigator（®）连续血糖监测仪（CGM）和英苏莱特公司（马萨诸塞州贝德福德）的Omnipod（®）胰岛素泵，通过人工胰腺系统平台实施MMPPC。控制器仅根据患者的每日总剂量和每日基础模式进行初始化。
在24小时内，第一组患者的参考读数和CGM读数平均分别为179和167毫克/分升，分别有53%和62%的读数在70至180毫克/分升之间，针对血糖值<70毫克/分升进行了4次治疗。第二组患者的参考读数和CGM读数平均分别为161和142毫克/分升，分别有63%和78%的时间处于血糖正常状态。发生了1次由控制器引起的低血糖事件。对于第二组的30次未提前告知的用餐，餐前参考读数和CGM读数、餐后最高读数以及餐后3小时读数平均分别为139和132、223和208、168和156毫克/分升。
在临床中针对重复的、大量的未提前告知用餐情况对MMPPC进行测试，其维持了合理的血糖控制，平均血糖水平相当于糖化血红蛋白平均水平为7.2%，在第二组中仅发生了1次由控制器引起的低血糖事件。
