Homeostasis model assessment: insulin resistance and β-cell function from fasting plasma glucose and insulin concentrations in man View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

1985-07

AUTHORS

D. R. Matthews, J. P. Hosker, A. S. Rudenski, B. A. Naylor, D. F. Treacher, R. C. Turner

ABSTRACT

The steady-state basal plasma glucose and insulin concentrations are determined by their interaction in a feedback loop. A computer-solved model has been used to predict the homeostatic concentrations which arise from varying degrees of β-cell deficiency and insulin resistance. Comparison of a patient's fasting values with the model's predictions allows a quantitative assessment of the contributions of insulin resistance and deficient β-cell function to the fasting hyperglycaemia (homeostasis model assessment, HOMA). The accuracy and precision of the estimate have been determined by comparison with independent measures of insulin resistance and β-cell function using hyperglycaemic and euglycaemic clamps and an intravenous glucose tolerance test. The estimate of insulin resistance obtained by homeostasis model assessment correlated with estimates obtained by use of the euglycaemic clamp (Rs = 0.88, p < 0.0001), the fasting insulin concentration (Rs = 0.81, p < 0.0001), and the hyperglycaemic clamp, (Rs = 0.69, p < 0.01). There was no correlation with any aspect of insulin-receptor binding. The estimate of deficient β-cell function obtained by homeostasis model assessment correlated with that derived using the hyperglycaemic clamp (Rs = 0.61, p < 0.01) and with the estimate from the intravenous glucose tolerance test (Rs = 0.64, p < 0.05). The low precision of the estimates from the model (coefficients of variation: 31% for insulin resistance and 32% for β-cell deficit) limits its use, but the correlation of the model's estimates with patient data accords with the hypothesis that basal glucose and insulin interactions are largely determined by a simple feed back loop. More... »

PAGES

412-419

Journal

TITLE

Diabetologia

ISSUE

7

VOLUME

28

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/bf00280883

    DOI

    http://dx.doi.org/10.1007/bf00280883

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1027902786

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/3899825


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    23 schema:description The steady-state basal plasma glucose and insulin concentrations are determined by their interaction in a feedback loop. A computer-solved model has been used to predict the homeostatic concentrations which arise from varying degrees of β-cell deficiency and insulin resistance. Comparison of a patient's fasting values with the model's predictions allows a quantitative assessment of the contributions of insulin resistance and deficient β-cell function to the fasting hyperglycaemia (homeostasis model assessment, HOMA). The accuracy and precision of the estimate have been determined by comparison with independent measures of insulin resistance and β-cell function using hyperglycaemic and euglycaemic clamps and an intravenous glucose tolerance test. The estimate of insulin resistance obtained by homeostasis model assessment correlated with estimates obtained by use of the euglycaemic clamp (Rs = 0.88, p < 0.0001), the fasting insulin concentration (Rs = 0.81, p < 0.0001), and the hyperglycaemic clamp, (Rs = 0.69, p < 0.01). There was no correlation with any aspect of insulin-receptor binding. The estimate of deficient β-cell function obtained by homeostasis model assessment correlated with that derived using the hyperglycaemic clamp (Rs = 0.61, p < 0.01) and with the estimate from the intravenous glucose tolerance test (Rs = 0.64, p < 0.05). The low precision of the estimates from the model (coefficients of variation: 31% for insulin resistance and 32% for β-cell deficit) limits its use, but the correlation of the model's estimates with patient data accords with the hypothesis that basal glucose and insulin interactions are largely determined by a simple feed back loop.
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