The Identifiable Virtual Patient Model: Comparison of Simulation and Clinical Closed-Loop Study Results
Optimizing a closed-loop insulin delivery algorithm for individuals with type 1 diabetes can be potentially facilitated by a mathematical model of the patient. However, model simulation studies that evaluate changes to the control algorithm need to produce conclusions similar to those that would be...
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Published in | Journal of diabetes science and technology Vol. 6; no. 2; pp. 371 - 379 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
United States
Diabetes Technology Society
01.03.2012
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Subjects | |
Online Access | Get full text |
ISSN | 1932-2968 1932-3107 |
DOI | 10.1177/193229681200600223 |
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Abstract | Optimizing a closed-loop insulin delivery algorithm for individuals with type 1 diabetes can be potentially facilitated by a mathematical model of the patient. However, model simulation studies that evaluate changes to the control algorithm need to produce conclusions similar to those that would be obtained from a clinical study evaluating the same modification. We evaluated the ability of a low-order identifiable virtual patient (IVP) model to achieve this goal.
Ten adult subjects (42.5 ± 11.5 years of age; 18.0 ± 13.5 years diabetes; 6.9 ± 0.8% hemoglobin A1c) previously characterized with the IVP model were studied following the procedures independently reported in a pediatric study assessing proportional-integral-derivative control with and without a 50% meal insulin bolus. Peak postprandial glucose levels with and without the meal bolus and use of supplemental carbohydrate to treat hypoglycemia were compared using two-way analysis of variance and chi-square tests, respectively.
The meal bolus decreased the peak postprandial glucose levels in both the adult-simulation and pediatricclinical study (231 ± 38 standard deviation to 205 ± 33 mg/dl and 226 ± 51 to 194 ± 47 mg/dl, respectively; p = .0472). No differences were observed between the peak postprandial levels obtained in the two studies (clinical and simulation study not different, p = .57; interaction p = .83) or in the use of supplemental carbohydrate (3 occurrences in 17 patient days of closed-loop control in the clinical-pediatric study; 7 occurrences over 20 patient days in the adult-simulation study, p = .29).
Closed-loop simulations using an IVP model can predict clinical study outcomes in patients studied independently from those used to develop the model. |
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AbstractList | Optimizing a closed-loop insulin delivery algorithm for individuals with type 1 diabetes can be potentially facilitated by a mathematical model of the patient. However, model simulation studies that evaluate changes to the control algorithm need to produce conclusions similar to those that would be obtained from a clinical study evaluating the same modification. We evaluated the ability of a low-order identifiable virtual patient (IVP) model to achieve this goal.BACKGROUNDOptimizing a closed-loop insulin delivery algorithm for individuals with type 1 diabetes can be potentially facilitated by a mathematical model of the patient. However, model simulation studies that evaluate changes to the control algorithm need to produce conclusions similar to those that would be obtained from a clinical study evaluating the same modification. We evaluated the ability of a low-order identifiable virtual patient (IVP) model to achieve this goal.Ten adult subjects (42.5 ± 11.5 years of age; 18.0 ± 13.5 years diabetes; 6.9 ± 0.8% hemoglobin A1c) previously characterized with the IVP model were studied following the procedures independently reported in a pediatric study assessing proportional-integral-derivative control with and without a 50% meal insulin bolus. Peak postprandial glucose levels with and without the meal bolus and use of supplemental carbohydrate to treat hypoglycemia were compared using two-way analysis of variance and chi-square tests, respectively.METHODSTen adult subjects (42.5 ± 11.5 years of age; 18.0 ± 13.5 years diabetes; 6.9 ± 0.8% hemoglobin A1c) previously characterized with the IVP model were studied following the procedures independently reported in a pediatric study assessing proportional-integral-derivative control with and without a 50% meal insulin bolus. Peak postprandial glucose levels with and without the meal bolus and use of supplemental carbohydrate to treat hypoglycemia were compared using two-way analysis of variance and chi-square tests, respectively.The meal bolus decreased the peak postprandial glucose levels in both the adult-simulation and pediatricclinical study (231 ± 38 standard deviation to 205 ± 33 mg/dl and 226 ± 51 to 194 ± 47 mg/dl, respectively; p = .0472). No differences were observed between the peak postprandial levels obtained in the two studies (clinical and simulation study not different, p = .57; interaction p = .83) or in the use of supplemental carbohydrate (3 occurrences in 17 patient days of closed-loop control in the clinical-pediatric study; 7 occurrences over 20 patient days in the adult-simulation study, p = .29).RESULTSThe meal bolus decreased the peak postprandial glucose levels in both the adult-simulation and pediatricclinical study (231 ± 38 standard deviation to 205 ± 33 mg/dl and 226 ± 51 to 194 ± 47 mg/dl, respectively; p = .0472). No differences were observed between the peak postprandial levels obtained in the two studies (clinical and simulation study not different, p = .57; interaction p = .83) or in the use of supplemental carbohydrate (3 occurrences in 17 patient days of closed-loop control in the clinical-pediatric study; 7 occurrences over 20 patient days in the adult-simulation study, p = .29).Closed-loop simulations using an IVP model can predict clinical study outcomes in patients studied independently from those used to develop the model.CONCLUSIONSClosed-loop simulations using an IVP model can predict clinical study outcomes in patients studied independently from those used to develop the model. Optimizing a closed-loop insulin delivery algorithm for individuals with type 1 diabetes can be potentially facilitated by a mathematical model of the patient. However, model simulation studies that evaluate changes to the control algorithm need to produce conclusions similar to those that would be obtained from a clinical study evaluating the same modification. We evaluated the ability of a low-order identifiable virtual patient (IVP) model to achieve this goal. Ten adult subjects (42.5 ± 11.5 years of age; 18.0 ± 13.5 years diabetes; 6.9 ± 0.8% hemoglobin A1c) previously characterized with the IVP model were studied following the procedures independently reported in a pediatric study assessing proportional-integral-derivative control with and without a 50% meal insulin bolus. Peak postprandial glucose levels with and without the meal bolus and use of supplemental carbohydrate to treat hypoglycemia were compared using two-way analysis of variance and chi-square tests, respectively. The meal bolus decreased the peak postprandial glucose levels in both the adult-simulation and pediatricclinical study (231 ± 38 standard deviation to 205 ± 33 mg/dl and 226 ± 51 to 194 ± 47 mg/dl, respectively; p = .0472). No differences were observed between the peak postprandial levels obtained in the two studies (clinical and simulation study not different, p = .57; interaction p = .83) or in the use of supplemental carbohydrate (3 occurrences in 17 patient days of closed-loop control in the clinical-pediatric study; 7 occurrences over 20 patient days in the adult-simulation study, p = .29). Closed-loop simulations using an IVP model can predict clinical study outcomes in patients studied independently from those used to develop the model. |
Author | Steil, Garry M. Kanderian, Sami S. Weinzimer, Stuart A. |
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SubjectTerms | Adolescent Adult Algorithms Analysis of Variance Biomarkers - blood Blood Glucose - drug effects Blood Glucose - metabolism Chi-Square Distribution Computer Simulation Diabetes Mellitus, Type 1 - blood Diabetes Mellitus, Type 1 - drug therapy Dietary Carbohydrates - administration & dosage Eating Fasting - blood Glycated Hemoglobin A - metabolism Humans Hypoglycemia - chemically induced Hypoglycemic Agents - administration & dosage Hypoglycemic Agents - adverse effects Hypoglycemic Agents - blood Insulin - administration & dosage Insulin - adverse effects Insulin - blood Insulin Infusion Systems Middle Aged Models, Biological Original Patient Simulation Postprandial Period Reproducibility of Results Time Factors |
Title | The Identifiable Virtual Patient Model: Comparison of Simulation and Clinical Closed-Loop Study Results |
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