Context: People with type 1 diabetes (T1D) have markedly reduced insulin sensitivity (IS) compared to their nondiabetic counterparts, and reduced IS is linked to higher cardiovascular risk. Objective: This study aimed to develop and validate an improved method for estimating IS in people with T1D. Design: Prospective cohort. Setting: Adults (36 with T1D, 41 nondiabetic) were recruited from the Coronary Artery Calcification in Type 1 Diabetes (CACTI) study for measurement of IS by hyperinsulinemic-euglycemic clamp to develop a clinically useful IS prediction equation (eIS) for T1D and nondiabetic individuals. These equations were then compared with previously published equations from the SEARCH and Pittsburgh Epidemiology of Diabetes Complications studies for the ability to predict measured IS in test sets of adults and adolescents from independent clamp studies. Intervention: None. Main Outcome Measure: Comparison of clamp-measured IS to estimated IS. Results: The best-fit prediction model (eIS) differed by diabetes status and included waist circumference, triglycerides, adiponectin, and diastolic blood pressure in all CACTI adults and insulin dose in adults with T1D (adjusted R2 0.64) or fasting glucose and hemoglobin A1c (HbA1c) in nondiabetic adults (adjusted R2 0.63). The eIS highly correlated with clamp-measured IS in all of the non-CACTI comparison populations (r 0.83, P .0002 in T1D adults; r 0.71, P .01 in nondiabetic adults; r 0.44, P .008 in T1D adolescents; r 0.44, P .006 in nondiabetic adolescents). Conclusions: eIS performed better than previous equations for estimating IS in individuals with and without T1D. These equations could simplify point-of-care assessment of IS to identify patientswho could benefit from targeted intervention.
CITATION STYLE
Duca, L. M., Maahs, D. M., Schauer, I. E., Bergman, B. C., Nadeau, K. J., Bjornstad, P., … Snell-Bergeon, J. K. (2016). Development and validation of a method to estimate insulin sensitivity in patients with and without type 1 diabetes. Journal of Clinical Endocrinology and Metabolism, 101(2), 686–695. https://doi.org/10.1210/jc.2015-3272
Mendeley helps you to discover research relevant for your work.