title: Prediction models for insulin resistance.
abstract: A prediction model for estimating insulin resistance in hypertensive patients is presented. Body-mass index, serum triglyceride concentrations and liver enzyme activity in plasma correlate to insulin resistance determined with the euglycaemic, hyperinsulinaemic clamp technique. Prediction models using body-mass index and either triglycerides or serum alanine-amino transferase were equally good in predicting insulin resistance and gave results that were as reliable as those obtained in a model using fasting-insulin concentrations. The hyperinsulinaemic clamp had a reproducibility error of 14%, and body-mass index and serum triglycerides had a multiple correlation of 0.57 to the insulin-sensitivity results. The model predicts insulin resistance with acceptable statistical power, whereas the power to predict high values of insulin sensitivity is less good.
authors.affiliation: Department of Geriatrics, Uppsala University, Sweden.
authors.forename: L
authors.initials: L
authors.lastname: Berglund
authors.forename: H
authors.initials: H
authors.lastname: Lithell
mesh_terms: D000368:Aged; D000410:Alanine Transaminase / Q000097:blood; D001824:Body Constitution / Q000502:physiology; D005260:Female; D006801:Humans; D006973:Hypertension / Q000097:blood / Q000503:physiopathology*; D007333:Insulin Resistance / Q000502:physiology*; D008297:Male; D011237:Predictive Value of Tests; D012044:Regression Analysis; D015203:Reproducibility of Results
chemical_list: D000410:Alanine Transaminase