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Novel laboratory index, based on fasting blood parameters, accurately reflects insulin sensitivity

Cite this dataset

Karczewska-Kupczewska, Monika et al. (2021). Novel laboratory index, based on fasting blood parameters, accurately reflects insulin sensitivity [Dataset]. Dryad.


Simple and reliable measurement of insulin sensitivity may be important for the prevention of insulin-resistance related diseases. Surrogate indices of insulin sensitivity are of limited utility in population without signs of metabolic syndrome. The aim of our study was to provide simple and accurate index of insulin sensitivity. The study group comprised 150 young healthy participants. Hyperinsulinemic-euglycemic clamp was performed. Regression models with different laboratory parameters were constructed. Validation cohort 1 comprised independent group of 110 subjects, including individuals with prediabetes and newly diagnosed type 2 diabetes. Validation cohort 2 comprised 38 obese subjects before and after diet-induced weight loss. Validation cohort 3 comprised 60 nondiabetic subjects from an independent center. The supervised principal component model established optimal set of variables correlated with insulin sensitivity. This model (Fasting Laboratory Assessment of Insulin Sensitivity, FLAIS) used red blood cell count, alanine aminotransferase activity, serum C-peptide, SHBG, IGF-binding protein 1 and adiponectin concentrations. FLAIS exhibited strong correlation with clamp-derived insulin sensitivity. The sensitivity of the model was 90% and the specificity was 68%. In the validation cohort 1, differences in FLAIS among the groups paralleled those observed with the clamp, with the lowest values in prediabetes and diabetes. In the validation cohort 2, FLAIS reflected the change in insulin sensitivity after weight loss. The main findings were confirmed in the validation cohort 3. We provide simple and accurate method of assessing insulin sensitivity, which allows to identify insulin resistance even in the population without overt metabolic disturbances.