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采用模型预测控制的夜间闭环胰岛素输注:利用模拟研究评估低血糖和高血糖风险

Overnight closed-loop insulin delivery with model predictive control: assessment of hypoglycemia and hyperglycemia risk using simulation studies.

作者信息

Wilinska Malgorzata E, Budiman Erwin S, Taub Marc B, Elleri Daniela, Allen Janet M, Acerini Carlo L, Dunger David B, Hovorka Roman

机构信息

Cambridge University Metabolic Research Laboratories, Institute of Metabolic Science, University of Cambridge, Cambridge, UK.

出版信息

J Diabetes Sci Technol. 2009 Sep 1;3(5):1109-20. doi: 10.1177/193229680900300514.

DOI:10.1177/193229680900300514
PMID:20144424
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2769888/
Abstract

BACKGROUND

Hypoglycemia and hyperglycemia during closed-loop insulin delivery based on subcutaneous (SC) glucose sensing may arise due to (1) overdosing and underdosing of insulin by control algorithm and (2) difference between plasma glucose (PG) and sensor glucose, which may be transient (kinetics origin and sensor artifacts) or persistent (calibration error [CE]). Using in silico testing, we assessed hypoglycemia and hyperglycemia incidence during over-night closed loop. Additionally, a comparison was made against incidence observed experimentally during open-loop single-night in-clinic studies in young people with type 1 diabetes mellitus (T1DM) treated by continuous SC insulin infusion.

METHODS

Simulation environment comprising 18 virtual subjects with T1DM was used to simulate overnight closed-loop study with a model predictive control (MPC) algorithm. A 15 h experiment started at 17:00 and ended at 08:00 the next day. Closed loop commenced at 21:00 and continued for 11 h. At 18:00, protocol included meal (50 g carbohydrates) accompanied by prandial insulin. The MPC algorithm advised on insulin infusion every 15 min. Sensor glucose was obtained by combining model-calculated noise-free interstitial glucose with experimentally derived transient and persistent sensor artifacts associated with FreeStyle Navigator (FSN). Transient artifacts were obtained from FSN sensor pairs worn by 58 subjects with T1DM over 194 nighttime periods. Persistent difference due to FSN CE was quantified from 585 FSN sensor insertions, yielding 1421 calibration sessions from 248 subjects with diabetes.

RESULTS

Episodes of severe (PG < or = 36 mg/dl) and significant (PG < or = 45 mg/dl) hypoglycemia and significant hyperglycemia (PG > or = 300 mg/dl) were extracted from 18,000 simulated closed-loop nights. Severe hypoglycemia was not observed when FSN CE was less than 45%. Hypoglycemia and hyperglycemia incidence during open loop was assessed from 21 overnight studies in 17 young subjects with T1DM (8 males; 13.5 +/- 3.6 years of age; body mass index 21.0 +/- 4.0 kg/m2; duration diabetes 6.4 +/- 4.1 years; hemoglobin A1c 8.5% +/- 1.8%; mean +/- standard deviation) participating in the Artificial Pancreas Project at Cambridge. Severe and significant hypoglycemia during simulated closed loop occurred 0.75 and 17.11 times per 100 person years compared to 1739 and 3479 times per 100 person years during experimental open loop, respectively. Significant hyperglycemia during closed loop and open loop occurred 75 and 15,654 times per 100 person years, respectively.

CONCLUSIONS

The incidence of severe and significant hypoglycemia reduced 2300- and 200-fold, respectively, during stimulated overnight closed loop with MPC compared to that observed during open-loop overnight clinical studies in young subjects with T1DM. Hyperglycemia was 200 times less likely. Overnight closed loop with the FSN and the MPC algorithm is expected to reduce substantially the risk of hypoglycemia and hyperglycemia.

摘要

背景

基于皮下(SC)葡萄糖传感的闭环胰岛素给药过程中,低血糖和高血糖可能由于以下原因出现:(1)控制算法导致胰岛素过量给药和给药不足;(2)血浆葡萄糖(PG)与传感器葡萄糖之间的差异,这种差异可能是短暂的(动力学原因和传感器伪迹)或持续的(校准误差[CE])。通过计算机模拟测试,我们评估了过夜闭环期间低血糖和高血糖的发生率。此外,还与在1型糖尿病(T1DM)青年患者的门诊单夜开环研究中通过持续皮下胰岛素输注治疗时实验观察到的发生率进行了比较。

方法

使用包含18名T1DM虚拟受试者的模拟环境,通过模型预测控制(MPC)算法模拟过夜闭环研究。1个15小时的实验于17:00开始,次日08:00结束。闭环于21:00开始并持续11小时。18:00时,方案包括进餐(50克碳水化合物)并伴有餐时胰岛素。MPC算法每15分钟建议一次胰岛素输注量。通过将模型计算的无噪声组织间液葡萄糖与实验得出的与FreeStyle Navigator(FSN)相关的短暂和持续传感器伪迹相结合来获得传感器葡萄糖。短暂伪迹来自58名T1DM受试者在194个夜间佩戴的FSN传感器对。FSN CE导致的持续差异从585次FSN传感器插入中进行量化,从248名糖尿病受试者中获得1421次校准过程。

结果

从18000个模拟闭环夜间中提取严重(PG≤36mg/dl)和显著(PG≤45mg/dl)低血糖以及显著高血糖(PG≥300mg/dl)事件。当FSN CE小于45%时未观察到严重低血糖。通过对17名T1DM青年受试者(8名男性;年龄13.5±3.6岁;体重指数21.0±4.0kg/m2;糖尿病病程6.4±4.1年;糖化血红蛋白8.5%±1.8%;均值±标准差)参与剑桥人工胰腺项目的21次过夜研究评估开环期间的低血糖和高血糖发生率。模拟闭环期间严重和显著低血糖分别为每100人年0.75次和17.11次,而实验开环期间分别为每100人年为1739次和3479次。闭环和开环期间显著高血糖分别为每100人年75次和15654次。

结论

与T1DM青年受试者的开环过夜临床研究相比,使用MPC进行的模拟过夜闭环期间,严重和显著低血糖的发生率分别降低了2300倍和200倍。高血糖发生的可能性降低了200倍。使用FSN和MPC算法的过夜闭环有望大幅降低低血糖和高血糖的风险。

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