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1
The identifiable virtual patient model: comparison of simulation and clinical closed-loop study results.可识别的虚拟患者模型:模拟与临床闭环研究结果的比较
J Diabetes Sci Technol. 2012 Mar 1;6(2):371-9. doi: 10.1177/193229681200600223.
2
Closed-loop insulin delivery utilizing pole placement to compensate for delays in subcutaneous insulin delivery.利用极点配置来补偿皮下胰岛素输注延迟的闭环胰岛素输注。
J Diabetes Sci Technol. 2011 Nov 1;5(6):1342-51. doi: 10.1177/193229681100500605.
3
A controlled study of the effectiveness of an adaptive closed-loop algorithm to minimize corticosteroid-induced stress hyperglycemia in type 1 diabetes.一项关于自适应闭环算法在1型糖尿病中最小化皮质类固醇诱导的应激性高血糖有效性的对照研究。
J Diabetes Sci Technol. 2011 Nov 1;5(6):1312-26. doi: 10.1177/193229681100500602.
4
Artificial pancreas: past, present, future.人工胰腺:过去、现在与未来。
Diabetes. 2011 Nov;60(11):2672-82. doi: 10.2337/db11-0654.
5
Overnight closed loop insulin delivery (artificial pancreas) in adults with type 1 diabetes: crossover randomised controlled studies.成人 1 型糖尿病患者的夜间闭环胰岛素输注(人工胰腺):交叉随机对照研究。
BMJ. 2011 Apr 13;342:d1855. doi: 10.1136/bmj.d1855.
6
The effect of insulin feedback on closed loop glucose control.胰岛素反馈对闭环血糖控制的影响。
J Clin Endocrinol Metab. 2011 May;96(5):1402-8. doi: 10.1210/jc.2010-2578. Epub 2011 Mar 2.
7
Use of subcutaneous interstitial fluid glucose to estimate blood glucose: revisiting delay and sensor offset.使用皮下组织间液葡萄糖来估计血糖:重新审视延迟和传感器偏移。
J Diabetes Sci Technol. 2010 Sep 1;4(5):1087-98. doi: 10.1177/193229681000400507.
8
Update on mathematical modeling research to support the development of automated insulin delivery systems.支持自动胰岛素输送系统开发的数学建模研究进展
J Diabetes Sci Technol. 2010 May 1;4(3):759-69. doi: 10.1177/193229681000400334.
9
A bihormonal closed-loop artificial pancreas for type 1 diabetes.用于 1 型糖尿病的双激素闭环人工胰腺。
Sci Transl Med. 2010 Apr 14;2(27):27ra27. doi: 10.1126/scitranslmed.3000619.
10
Early pharmacokinetic and pharmacodynamic effects of mixing lispro with glargine insulin: results of glucose clamp studies in youth with type 1 diabetes.混合赖脯胰岛素和甘精胰岛素对青少年 1 型糖尿病患者早期药代动力学和药效学的影响:葡萄糖钳夹研究的结果。
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使用美国食品药品监督管理局批准的1型糖尿病模拟器来评估和优化比例积分微分控制器。

Use of a food and drug administration-approved type 1 diabetes mellitus simulator to evaluate and optimize a proportional-integral-derivative controller.

作者信息

Laxminarayan Srinivas, Reifman Jaques, Steil Garry M

机构信息

DoD Biotechnology High-Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, MD 21702, USA.

出版信息

J Diabetes Sci Technol. 2012 Nov 1;6(6):1401-12. doi: 10.1177/193229681200600621.

DOI:10.1177/193229681200600621
PMID:23294787
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3570882/
Abstract

BACKGROUND

Clinical studies have shown that the Medtronic proportional-integral-derivative (PID) control with insulin feedback (IFB) provides stable 24 h glucose control, but with high postprandial glucose. We coupled this algorithm to a Food and Drug Administration-approved type 1 diabetes mellitus simulator to determine whether a proportional-derivative controller with preprogrammed basal rates (PDBASAL) would have better performance.

METHODS

We performed simulation studies on 10 adult subjects to (1) obtain the basal profiles for the PDBASAL controller; (2) define the pharmacokinetic/pharmacodynamic profile used to effect IFB, (3) optimize the PID and PDBASAL control parameters, (4) evaluate improvements obtained with IFB, and (5) develop a method to simulate changes in insulin sensitivity and assess the ability of each algorithm to respond to such changes.

RESULTS

PDBASAL control significantly reduced peak postprandial glucose [252 (standard error = 11) versus 279 (14) mg/dl; p < .001] and increased nadir glucose [102 (3) versus 92 (3) mg/dl; p < .001] compared with PID control (both implemented with IFB). However, with PDBASAL control, fasting glucose remained elevated following a 30% decrease in insulin sensitivity [156 (6) mg/dl; different from the target of 110 mg/dl; p < .001] and remained below target following a 30% increase in insulin sensitivity [84 (2) mg/dl; p < .001]. In both cases, PID control returned glucose levels to target.

CONCLUSIONS

PDBASAL provides better postprandial glucose control than PID but is not appropriate for subjects whose basal requirements change with insulin sensitivity. Simulations used to compare different control strategies should assess this variability.

摘要

背景

临床研究表明,美敦力胰岛素反馈比例积分微分(PID)控制可实现24小时稳定的血糖控制,但餐后血糖较高。我们将该算法与美国食品药品监督管理局批准的1型糖尿病模拟器相结合,以确定具有预编程基础率的比例微分控制器(PDBASAL)是否具有更好的性能。

方法

我们对10名成年受试者进行了模拟研究,以(1)获取PDBASAL控制器的基础曲线;(2)定义用于实现胰岛素反馈(IFB)的药代动力学/药效学曲线,(3)优化PID和PDBASAL控制参数,(4)评估IFB带来的改善,以及(5)开发一种模拟胰岛素敏感性变化的方法,并评估每种算法对此类变化的反应能力。

结果

与PID控制(均采用IFB)相比,PDBASAL控制显著降低了餐后血糖峰值[252(标准误=11)对279(14)mg/dl;p<.001],并提高了血糖最低点[102(3)对92(3)mg/dl;p<.001]。然而,在PDBASAL控制下,胰岛素敏感性降低30%后空腹血糖仍升高[156(6)mg/dl;不同于目标值110mg/dl;p<.001],而胰岛素敏感性增加30%后空腹血糖仍低于目标值[84(2)mg/dl;p<.001]。在这两种情况下,PID控制均使血糖水平恢复至目标值。

结论

PDBASAL比PID能更好地控制餐后血糖,但不适用于基础需求随胰岛素敏感性变化的受试者。用于比较不同控制策略的模拟应评估这种变异性。