Optimizing insulin sensitivity assessment using the minimal model in chronic heart failure

W. Doehner, S. D. Anker, I. F. Godsland

Research output: Contribution to journalArticle

Abstract

Background: Minimal model analysis of the intravenous glucose tolerance test (IVGTT) has been used successfully to demonstrate that patients with chronic heart failure (CHF) are insulin-resistant. Continuing experience in minimal model methodology has raised questions about how best to assign basal glucose concentrations during such analyses. Methods and Results: IVGTT data from randomly selected patients with CHF (n = 15) and controls (n = 15) were analysed using the minimal model, with the basal glucose concentration (G b) assigned the value of fasting plasma glucose concentration (G fast), or the value of plasma glucose concentration 180 minutes after the start of the IVGTT (G180). Insulin sensitivity (S1) was significantly higher with Gb = Gfast, than with G b = G180 (controls: 5.60 ± 0.78 vs. 3.36 ± 0.25/μU/ml × 104, p = 0.0017; patients 4.19 ± 0.54 vs. 2.36 ± 0.15/min/μU/ml × 104, p = 0.0004). At Gb = Gfast, CHF patients showed a non-significant 25% reduction in SI in comparison to controls (p = 0.15). In contrast, at Gb = G180, CHF patients showed a significant 30% reduction of SI in comparison to controls (p = 0.0018). SI estimates derived at Gb = Gfast exhibited twice the variability of those estimated using Gb = G180 (coefficients of variation of SI in patients with CHF were 50.0% and 24.8%, respectively). Conclusion: In studies of patients with CHF, greater precision and discriminatory power of insulin sensitivity estimates is obtained when the basal glucose concentration is taken as the plasma glucose concentration 180 minutes after the start of the IVGTT.

Original languageEnglish
Pages (from-to)106-110
Number of pages5
JournalHormone and Metabolic Research
Volume37
Issue number2
DOIs
Publication statusPublished - Feb 2005

Keywords

  • Chronic heart failure
  • Insulin sensitivity
  • Minimal model

ASJC Scopus subject areas

  • Biochemistry
  • Endocrinology

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