Estimating insulin sensitivity and b-cell function from the oral glucose tolerance test: validation of a new insulin sensitivity and secretion (ISS) model.

Autor: Joon Ha, Chung, Stephanie T., Springer, Max, Joon Young Kim, Phil Chen, Chhabra, Aaryan, Cree, Melanie G., Behn, Cecilia Diniz, Sumner, Anne E., Arslanian, Silva A., Sherman, Arthur S.
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Zdroj: American Journal of Physiology: Endocrinology & Metabolism; Apr2024, Vol. 326 Issue 4, p454-471, 18p
Abstrakt: Efficient and accurate methods to estimate insulin sensitivity (SI) and b-cell function (BCF) are of great importance for studying the pathogenesis and treatment effectiveness of type 2 diabetes (T2D). Existing methods range in sensitivity, input data, and technical requirements. Oral glucose tolerance tests (OGTTs) are preferred because they are simpler and more physiological than intravenous methods. However, current analytical methods for OGTT-derived SI and BCF also range in complexity; the oral minimal models require mathematical expertise for deconvolution and fitting differential equations, and simple algebraic surrogate indices (e.g., Matsuda index, insulinogenic index) may produce unphysiological values. We developed a new insulin secretion and sensitivity (ISS) model for clinical research that provides precise and accurate estimates of SI and BCF from a standard OGTT, focusing on effectiveness, ease of implementation, and pragmatism. This model was developed by fitting a pair of differential equations to glucose and insulin without need of deconvolution or C-peptide data. This model is derived from a published model for longitudinal simulation of T2D progression that represents glucose-insulin homeostasis, including postchallenge suppression of hepatic glucose production and first- and second-phase insulin secretion. The ISS model was evaluated in three diverse cohorts across the lifespan. The new model had a strong correlation with gold-standard estimates from intravenous glucose tolerance tests and insulin clamps. The ISS model has broad applicability among diverse populations because it balances performance, fidelity, and complexity to provide a reliable phenotype of T2D risk. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index