Simple modeling allows prediction of steady-state glucose disposal rate from early data in hyperinsulinemic glucose clamps

Pooja Singal, Ranganath Muniyappa, Robin Chisholm, Gail Hall, Hui Chen, Michael J. Quon, Kieren J. Mather

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

After a constant insulin infusion is initiated, determination of steadystate conditions for glucose infusion rates (GIR) typically requires ≥3 h. The glucose infusion follows a simple time-dependent rise, reaching a plateau at steady state. We hypothesized that nonlinear fitting of abbreviated data sets consisting of only the early portion of the clamp study can provide accurate estimates of steady-state GIR. Data sets from two independent laboratories were used to develop and validate this approach. Accuracy of the predicted steady-state GDR was assessed using regression analysis and Altman-Bland plots, and precision was compared by applying a calibration model. In the development data set (n = 88 glucose clamp studies), fitting the full data set with a simple monoexponential model predicted reference GDR values with good accuracy (difference between the 2 methods -0.37 mg·kg-1 ·min-1) and precision [root mean square error (RMSE) = 1.11], validating the modeling procedure. Fitting data from the first 180 or 120 min predicted final GDRs with comparable accuracy but with progressively reduced precision [fitGDR-180 RMSE = 1.27 (P = NS vs. fitGDR-full); fitGDR-120 RMSE = 1.56 (P < 0.001)]. Similar results were obtained with the validation data set (n = 183 glucose clamp studies), confirming the generalizability of this approach. The modeling approach also derives kinetic parameters that are not available from standard approaches to clamp data analysis. We conclude that fitting a monoexponential curve to abbreviated clamp data produces steady-state GDR values that accurately predict the GDR values obtained from the full data sets, albeit with reduced precision. This approach may help reduce the resources required for undertaking clamp studies.

Original languageEnglish (US)
Pages (from-to)E229-E236
JournalAmerican Journal of Physiology - Endocrinology and Metabolism
Volume298
Issue number2
DOIs
StatePublished - Feb 1 2010

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Glucose Clamp Technique
Glucose
Calibration
Datasets
Reference Values
Regression Analysis
Insulin

Keywords

  • Fitting
  • Insulin

ASJC Scopus subject areas

  • Physiology
  • Physiology (medical)
  • Endocrinology, Diabetes and Metabolism

Cite this

Simple modeling allows prediction of steady-state glucose disposal rate from early data in hyperinsulinemic glucose clamps. / Singal, Pooja; Muniyappa, Ranganath; Chisholm, Robin; Hall, Gail; Chen, Hui; Quon, Michael J.; Mather, Kieren J.

In: American Journal of Physiology - Endocrinology and Metabolism, Vol. 298, No. 2, 01.02.2010, p. E229-E236.

Research output: Contribution to journalArticle

Singal, Pooja ; Muniyappa, Ranganath ; Chisholm, Robin ; Hall, Gail ; Chen, Hui ; Quon, Michael J. ; Mather, Kieren J. / Simple modeling allows prediction of steady-state glucose disposal rate from early data in hyperinsulinemic glucose clamps. In: American Journal of Physiology - Endocrinology and Metabolism. 2010 ; Vol. 298, No. 2. pp. E229-E236.
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