Model-based closed-loop glucose control in type 1 diabetes: The DiaCon Experience

Signe  Schmidt; Dimitri Boiroux; Anne Katrine Duun-Henriksen; Laurits Frøssing; Ole Skyggebjerg; John Bagterp Jørgensen; Niels Kjølstad Poulsen; H. Madsen; Sten Madsbad; Kirsten Nørgaard

Model-based closed-loop glucose control in type 1 diabetes: The DiaCon Experience

Signe Schmidt, Dimitri Boiroux, Anne Katrine Duun-Henriksen, Laurits Frøssing, Ole Skyggebjerg, John Bagterp Jørgensen, Niels Kjølstad Poulsen, H. Madsen, Sten Madsbad, Kirsten Nørgaard

Department of Clinical Medicine

27 Citations (Scopus)

Abstract

Background: To improve type 1 diabetes mellitus (T1DM) management, we developed a model predictive control (MPC) algorithm for closed-loop (CL) glucose control based on a linear second-order deterministic-stochastic model. The deterministic part of the model is specified by three patient-specific parameters: insulin sensitivity factor, insulin action time, and basal insulin infusion rate. The stochastic part is identical for all patients but identified from data from a single patient. Results of the first clinical feasibility test of the algorithm are presented. Methods: We conducted two randomized crossover studies. Study 1 compared CL with open-loop (OL) control. Study 2 compared glucose control after CL initiation in the euglycemic (CL-Eu) and hyperglycemic (CL-Hyper) ranges, respectively. Patients were studied from 22:00-07:00 on two separate nights. Results: Each study included six T1DM patients (hemoglobin A1c 7.2% ± 0.4%). In study 1, hypoglycemic events (plasma glucose < 54 mg/dl) occurred on two OL and one CL nights. Average glucose from 22:00-07:00 was 90 mg/dl [74-146 mg/dl; median (interquartile range)] during OL and 108 mg/dl (101-128 mg/dl) during CL (determined by continuous glucose monitoring). However, median time spent in the range 70-144 mg/dl was 67.9% (3.0-73.3%) during OL and 80.8% (70.5-89.7%) during CL. In study 2, there was one episode of hypoglycemia with plasma glucose <54 mg/dl in a CL-Eu night. Mean glucose from 22:00-07:00 and time spent in the range 70-144 mg/dl were 121 mg/dl (117-133 mg/dl) and 69.0% (30.7-77.9%) in CL-Eu and 149 mg/dl (140-193 mg/dl) and 48.2% (34.9-72.5%) in CL-Hyper, respectively. Conclusions: This study suggests that our novel MPC algorithm can safely and efectively control glucose overnight, also when CL control is initiated during hyperglycemia.

Original language	English
Journal	Journal of Diabetes Science and Technology
Volume	7
Issue number	5
Pages (from-to)	1255-1264
Number of pages	10
ISSN	1932-2968
Publication status	Published - Sept 2013

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title = "Model-based closed-loop glucose control in type 1 diabetes: The DiaCon Experience",

abstract = "Background: To improve type 1 diabetes mellitus (T1DM) management, we developed a model predictive control (MPC) algorithm for closed-loop (CL) glucose control based on a linear second-order deterministic-stochastic model. The deterministic part of the model is specified by three patient-specific parameters: insulin sensitivity factor, insulin action time, and basal insulin infusion rate. The stochastic part is identical for all patients but identified from data from a single patient. Results of the first clinical feasibility test of the algorithm are presented. Methods: We conducted two randomized crossover studies. Study 1 compared CL with open-loop (OL) control. Study 2 compared glucose control after CL initiation in the euglycemic (CL-Eu) and hyperglycemic (CL-Hyper) ranges, respectively. Patients were studied from 22:00-07:00 on two separate nights. Results: Each study included six T1DM patients (hemoglobin A1c 7.2% ± 0.4%). In study 1, hypoglycemic events (plasma glucose < 54 mg/dl) occurred on two OL and one CL nights. Average glucose from 22:00-07:00 was 90 mg/dl [74-146 mg/dl; median (interquartile range)] during OL and 108 mg/dl (101-128 mg/dl) during CL (determined by continuous glucose monitoring). However, median time spent in the range 70-144 mg/dl was 67.9% (3.0-73.3%) during OL and 80.8% (70.5-89.7%) during CL. In study 2, there was one episode of hypoglycemia with plasma glucose <54 mg/dl in a CL-Eu night. Mean glucose from 22:00-07:00 and time spent in the range 70-144 mg/dl were 121 mg/dl (117-133 mg/dl) and 69.0% (30.7-77.9%) in CL-Eu and 149 mg/dl (140-193 mg/dl) and 48.2% (34.9-72.5%) in CL-Hyper, respectively. Conclusions: This study suggests that our novel MPC algorithm can safely and efectively control glucose overnight, also when CL control is initiated during hyperglycemia.",

author = "Signe Schmidt and Dimitri Boiroux and Duun-Henriksen, {Anne Katrine} and Laurits Fr{\o}ssing and Ole Skyggebjerg and J{\o}rgensen, {John Bagterp} and Poulsen, {Niels Kj{\o}lstad} and H. Madsen and Sten Madsbad and Kirsten N{\o}rgaard",

year = "2013",

month = sep,

language = "English",

volume = "7",

pages = "1255--1264",

journal = "Journal of Diabetes Science and Technology",

issn = "1932-2968",

publisher = "SAGE Publications",

number = "5",

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TY - JOUR

T1 - Model-based closed-loop glucose control in type 1 diabetes

T2 - The DiaCon Experience

AU - Schmidt, Signe

AU - Boiroux, Dimitri

AU - Duun-Henriksen, Anne Katrine

AU - Frøssing, Laurits

AU - Skyggebjerg, Ole

AU - Jørgensen, John Bagterp

AU - Poulsen, Niels Kjølstad

AU - Madsen, H.

AU - Madsbad, Sten

AU - Nørgaard, Kirsten

PY - 2013/9

Y1 - 2013/9

N2 - Background: To improve type 1 diabetes mellitus (T1DM) management, we developed a model predictive control (MPC) algorithm for closed-loop (CL) glucose control based on a linear second-order deterministic-stochastic model. The deterministic part of the model is specified by three patient-specific parameters: insulin sensitivity factor, insulin action time, and basal insulin infusion rate. The stochastic part is identical for all patients but identified from data from a single patient. Results of the first clinical feasibility test of the algorithm are presented. Methods: We conducted two randomized crossover studies. Study 1 compared CL with open-loop (OL) control. Study 2 compared glucose control after CL initiation in the euglycemic (CL-Eu) and hyperglycemic (CL-Hyper) ranges, respectively. Patients were studied from 22:00-07:00 on two separate nights. Results: Each study included six T1DM patients (hemoglobin A1c 7.2% ± 0.4%). In study 1, hypoglycemic events (plasma glucose < 54 mg/dl) occurred on two OL and one CL nights. Average glucose from 22:00-07:00 was 90 mg/dl [74-146 mg/dl; median (interquartile range)] during OL and 108 mg/dl (101-128 mg/dl) during CL (determined by continuous glucose monitoring). However, median time spent in the range 70-144 mg/dl was 67.9% (3.0-73.3%) during OL and 80.8% (70.5-89.7%) during CL. In study 2, there was one episode of hypoglycemia with plasma glucose <54 mg/dl in a CL-Eu night. Mean glucose from 22:00-07:00 and time spent in the range 70-144 mg/dl were 121 mg/dl (117-133 mg/dl) and 69.0% (30.7-77.9%) in CL-Eu and 149 mg/dl (140-193 mg/dl) and 48.2% (34.9-72.5%) in CL-Hyper, respectively. Conclusions: This study suggests that our novel MPC algorithm can safely and efectively control glucose overnight, also when CL control is initiated during hyperglycemia.

AB - Background: To improve type 1 diabetes mellitus (T1DM) management, we developed a model predictive control (MPC) algorithm for closed-loop (CL) glucose control based on a linear second-order deterministic-stochastic model. The deterministic part of the model is specified by three patient-specific parameters: insulin sensitivity factor, insulin action time, and basal insulin infusion rate. The stochastic part is identical for all patients but identified from data from a single patient. Results of the first clinical feasibility test of the algorithm are presented. Methods: We conducted two randomized crossover studies. Study 1 compared CL with open-loop (OL) control. Study 2 compared glucose control after CL initiation in the euglycemic (CL-Eu) and hyperglycemic (CL-Hyper) ranges, respectively. Patients were studied from 22:00-07:00 on two separate nights. Results: Each study included six T1DM patients (hemoglobin A1c 7.2% ± 0.4%). In study 1, hypoglycemic events (plasma glucose < 54 mg/dl) occurred on two OL and one CL nights. Average glucose from 22:00-07:00 was 90 mg/dl [74-146 mg/dl; median (interquartile range)] during OL and 108 mg/dl (101-128 mg/dl) during CL (determined by continuous glucose monitoring). However, median time spent in the range 70-144 mg/dl was 67.9% (3.0-73.3%) during OL and 80.8% (70.5-89.7%) during CL. In study 2, there was one episode of hypoglycemia with plasma glucose <54 mg/dl in a CL-Eu night. Mean glucose from 22:00-07:00 and time spent in the range 70-144 mg/dl were 121 mg/dl (117-133 mg/dl) and 69.0% (30.7-77.9%) in CL-Eu and 149 mg/dl (140-193 mg/dl) and 48.2% (34.9-72.5%) in CL-Hyper, respectively. Conclusions: This study suggests that our novel MPC algorithm can safely and efectively control glucose overnight, also when CL control is initiated during hyperglycemia.

M3 - Journal article

SN - 1932-2968

VL - 7

SP - 1255

EP - 1264

JO - Journal of Diabetes Science and Technology

JF - Journal of Diabetes Science and Technology

IS - 5

ER -

Model-based closed-loop glucose control in type 1 diabetes: The DiaCon Experience

Abstract

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