Lipid accumulation product (LAP) as a potential index to predict risk of insulin resistance in young, non-obese Asian Indian males from Southern India: observations from hyperinsulinemic-euglycemic clamp studies

Autor: Geethanjali Finney, Shajith Anoop S, Grace Rebekah, Nihal Thomas, Arun Jose, Riddhi Dasgupta, Mercy Inbakumari
Rok vydání: 2021
Předmět:
Zdroj: BMJ Open Diabetes Research & Care
BMJ Open Diabetes Research & Care, Vol 9, Iss 1 (2021)
ISSN: 2052-4897
DOI: 10.1136/bmjdrc-2021-002414
Popis: IntroductionWe aimed to compare the predictive accuracy of surrogate indices namely the lipid accumulation product (LAP) index, homeostatic model of assessment of insulin resistance (HOMA-IR), fasting glucose-insulin ratio (FG-IR) and the quantitative-insulin sensitivity check index (QUICKI), against the M value of hyperinsulinemic-euglycemic clamp (HEC), and to determine a cut-off value for the LAP index to predict risk of insulin resistance in non-obese (body mass index 2), normoglycemic, Asian Indian males from Southern India.Research design and methodsData of HEC studies performed in 108 non-obese, normoglycemic, Asian Indian males was obtained retrospectively and the M value (a measure of whole-body insulin sensitivity) was calculated. The M value is the rate of whole-body glucose metabolism at the hyperinsulinemic plateau (a measure of insulin sensitivity) and is calculated between 60 and 120 min after the start of the insulin infusion in the HEC procedure. The LAP index, the HOMA-IR, FG-IR and QUICKI were calculated. Spearman’s correlation and logistic regression analysis were performed. Cut-off value for the LAP index was obtained using receiver operating characteristics with area under curve (AUC) analysis at 95% CI. P value ResultsSignificant negative correlation was observed for the M value with LAP index (r=−0.39, pConclusionThe LAP index showed higher predictive accuracy for the risk of insulin resistance as compared with HOMA-IR, QUICKI and FG-IR in non-obese, normoglycemic Asian Indian males from Southern India.
Databáze: OpenAIRE