1
|
McHugh AD, Chase JG, Knopp JL, Ormsbee JJ, Kulawiec DG, Merry TL, Murphy R, Shepherd PR, Burden HJ, Docherty PD. The Impact of Exogenous Insulin Input on Calculating Hepatic Clearance Parameters. J Diabetes Sci Technol 2022; 16:945-954. [PMID: 33478257 PMCID: PMC9264438 DOI: 10.1177/1932296820986878] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
OBJECTIVE Model-based metabolic tests require accurate identification of subject-specific parameters from measured assays. Insulin assays are used to identify insulin kinetics parameters, such as general and first-pass hepatic clearances. This study assesses the impact of intravenous insulin boluses on parameter identification precision. METHOD Insulin and C-peptide data from two intravenous glucose tolerance test (IVGTT) trials of healthy adults (N = 10 × 2; denoted A and B), with (A) and without (B) insulin modification, were used to identify insulin kinetics parameters using a grid search. Monte Carlo analysis (N = 1000) quantifies variation in simulation error for insulin assay errors of 5%. A region of parameter values around the optimum was identified whose errors are within variation due to assay error. A smaller optimal region indicates more precise practical identifiability. Trial results were compared to assess identifiability and precision. RESULTS Trial B, without insulin modification, has optimal parameter regions 4.7 times larger on average than Trial A, with 1-U insulin bolus modification. Ranges of optimal parameter values between trials A and B increase from 0.04 to 0.12 min-1 for hepatic clearance and from 0.07 to 0.14 for first-pass clearance on average. Trial B's optimal values frequently lie outside physiological ranges, further indicating lack of distinct identifiability. CONCLUSIONS A small 1-U insulin bolus improves identification of hepatic clearance parameters by providing a smaller region of optimal parameter values. Adding an insulin bolus in metabolic tests can significantly improve identifiability and outcome test precision. Assay errors necessitate insulin modification in clinical tests to ensure identifiability and precision.
Collapse
Affiliation(s)
- Alexander D. McHugh
- Centre for Bioengineering, Department of
Mechanical Engineering, University of Canterbury, Christchurch, New Zealand
- Alexander D. McHugh, BE(Hons),
Centre for Bioengineering, Department of Mechanical Engineering,
University of Canterbury, Level 5 Civil/Mechanical Building, Private Bag 4800,
Christchurch, 8140, New Zealand.
| | - J. Geoffrey Chase
- Centre for Bioengineering, Department of
Mechanical Engineering, University of Canterbury, Christchurch, New Zealand
| | - Jennifer L. Knopp
- Centre for Bioengineering, Department of
Mechanical Engineering, University of Canterbury, Christchurch, New Zealand
| | - Jennifer J. Ormsbee
- Centre for Bioengineering, Department of
Mechanical Engineering, University of Canterbury, Christchurch, New Zealand
| | - Diana G. Kulawiec
- Department of Biomedical Engineering,
Rochester Institute of Technology, Rochester, NY, USA
| | - Troy L. Merry
- Discipline of Nutrition, Faculty of
Medical and Health Sciences, University of Auckland, Auckland, New Zealand
- Maurice Wilkins Centre for Molecular
Biodiscovery, University of Auckland, Auckland, New Zealand
| | - Rinki Murphy
- Discipline of Nutrition, Faculty of
Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Peter R. Shepherd
- Discipline of Nutrition, Faculty of
Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Hannah J. Burden
- Discipline of Nutrition, Faculty of
Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Paul D. Docherty
- Centre for Bioengineering, Department of
Mechanical Engineering, University of Canterbury, Christchurch, New Zealand
- Institute for Technical Medicine,
Furtwangen University, Villingen-Schwenningen, Germany
| |
Collapse
|
2
|
Abstract
BACKGROUND The ability to measure insulin secretion from pancreatic beta cells and monitor glucose-insulin physiology is vital to current health needs. C-peptide has been used successfully as a surrogate for plasma insulin concentration. Quantifying the expected variability of modelled insulin secretion will improve confidence in model estimates. METHODS Forty-three healthy adult males of Māori or Pacific peoples ancestry living in New Zealand participated in an frequently sampled, intravenous glucose tolerance test (FS-IVGTT) with an average age of 29 years and a BMI of 33 kg/m2. A 2-compartment model framework and standardized kinetic parameters were used to estimate endogenous pancreatic insulin secretion from plasma C-peptide measurements. Monte Carlo analysis (N = 10 000) was then used to independently vary parameters within ±2 standard deviations of the mean of each variable and the 5th and 95th percentiles determined the bounds of the expected range of insulin secretion. Cumulative distribution functions (CDFs) were calculated for each subject for area under the curve (AUC) total, AUC Phase 1, and AUC Phase 2. Normalizing each AUC by the participant's median value over all N = 10 000 iterations quantifies the expected model-based variability in AUC. RESULTS Larger variation is found in subjects with a BMI > 30 kg/m2, where the interquartile range is 34.3% compared to subjects with a BMI ≤ 30 kg/m2 where the interquartile range is 24.7%. CONCLUSIONS Use of C-peptide measurements using a 2-compartment model and standardized kinetic parameters, one can expect ~±15% variation in modelled insulin secretion estimates. The variation should be considered when applying this insulin secretion estimation method to clinical diagnostic thresholds and interpretation of model-based analyses such as insulin sensitivity.
Collapse
Affiliation(s)
- Jennifer J. Ormsbee
- Department of Mechanical Engineering,
Centre for Bioengineering, University of Canterbury, Christchurch, New Zealand
- Jennifer J. Ormsbee, MSc, University of
Canterbury, Level 5 Civil/Mechanical Building, Private Bag 4800, Christchurch,
Canterbury 8140, New Zealand.
| | - Hannah J. Burden
- Discipline of Nutrition, Faculty of
Medical and Health Sciences, The University of Auckland, Auckland, New Zealand
| | - Jennifer L. Knopp
- Department of Mechanical Engineering,
Centre for Bioengineering, University of Canterbury, Christchurch, New Zealand
| | - J. Geoffrey Chase
- Department of Mechanical Engineering,
Centre for Bioengineering, University of Canterbury, Christchurch, New Zealand
| | - Rinki Murphy
- Discipline of Nutrition, Faculty of
Medical and Health Sciences, The University of Auckland, Auckland, New Zealand
| | - Peter R. Shepherd
- Discipline of Nutrition, Faculty of
Medical and Health Sciences, The University of Auckland, Auckland, New Zealand
- Maurice Wilkins Centre for Molecular
Biodiscovery, The University of Auckland, Auckland, New Zealand
| | - Troy Merry
- Discipline of Nutrition, Faculty of
Medical and Health Sciences, The University of Auckland, Auckland, New Zealand
- Maurice Wilkins Centre for Molecular
Biodiscovery, The University of Auckland, Auckland, New Zealand
| |
Collapse
|