» Articles » PMID: 20144424

Overnight Closed-loop Insulin Delivery with Model Predictive Control: Assessment of Hypoglycemia and Hyperglycemia Risk Using Simulation Studies

Overview
Specialty Endocrinology
Date 2010 Feb 11
PMID 20144424
Citations 30
Authors
Affiliations
Soon will be listed here.
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.

Citing Articles

Effectiveness and safety of a model predictive control (MPC) algorithm for an artificial pancreas system in outpatients with type 1 diabetes (T1D): systematic review and meta-analysis.

Kang S, Hwang Y, Kwon J, Kim S Diabetol Metab Syndr. 2022; 14(1):187.

PMID: 36494830 PMC: 9733359. DOI: 10.1186/s13098-022-00962-2.


Novel Methods to Understand the Temporal Nature and Accuracy of Delivery for Insulin Infusion Pumps.

Kumar S, Karia D, Gopkumar A, Koty P, Arora M J Diabetes Sci Technol. 2022; 18(3):618-624.

PMID: 35929433 PMC: 11089866. DOI: 10.1177/19322968221115749.


A revised Sorensen model: Simulating glycemic and insulinemic response to oral and intra-venous glucose load.

Panunzi S, Pompa M, Borri A, Piemonte V, De Gaetano A PLoS One. 2020; 15(8):e0237215.

PMID: 32797106 PMC: 7428140. DOI: 10.1371/journal.pone.0237215.


Day-and-night glycaemic control with closed-loop insulin delivery versus conventional insulin pump therapy in free-living adults with well controlled type 1 diabetes: an open-label, randomised, crossover study.

Bally L, Thabit H, Kojzar H, Mader J, Qerimi-Hyseni J, Hartnell S Lancet Diabetes Endocrinol. 2017; 5(4):261-270.

PMID: 28094136 PMC: 5379244. DOI: 10.1016/S2213-8587(17)30001-3.


Home Use of Day-and-Night Hybrid Closed-Loop Insulin Delivery in Suboptimally Controlled Adolescents With Type 1 Diabetes: A 3-Week, Free-Living, Randomized Crossover Trial.

Tauschmann M, Allen J, Wilinska M, Thabit H, Acerini C, Dunger D Diabetes Care. 2016; 39(11):2019-2025.

PMID: 27612500 PMC: 5079605. DOI: 10.2337/dc16-1094.


References
1.
Patek S, Bequette B, Breton M, Buckingham B, Dassau E, Doyle 3rd F . In silico preclinical trials: methodology and engineering guide to closed-loop control in type 1 diabetes mellitus. J Diabetes Sci Technol. 2010; 3(2):269-82. PMC: 2771529. DOI: 10.1177/193229680900300207. View

2.
Hovorka R, Chassin L, Wilinska M, Canonico V, Akwi J, Federici M . Closing the loop: the adicol experience. Diabetes Technol Ther. 2004; 6(3):307-18. DOI: 10.1089/152091504774197990. View

3.
Hovorka R . The future of continuous glucose monitoring: closed loop. Curr Diabetes Rev. 2008; 4(3):269-79. DOI: 10.2174/157339908785294479. View

4.
Basu R, Dalla Man C, Campioni M, Basu A, Klee G, Toffolo G . Effects of age and sex on postprandial glucose metabolism: differences in glucose turnover, insulin secretion, insulin action, and hepatic insulin extraction. Diabetes. 2006; 55(7):2001-14. DOI: 10.2337/db05-1692. View

5.
McGarraugh G, Bergenstal R . Detection of hypoglycemia with continuous interstitial and traditional blood glucose monitoring using the FreeStyle Navigator Continuous Glucose Monitoring System. Diabetes Technol Ther. 2009; 11(3):145-50. DOI: 10.1089/dia.2008.0047. View