Utility of Insulin Resistance in Estimating Cardiovascular Risk in Subjects with Type 1 Diabetes According to the Scores of the Steno Type 1 Risk Engine

Abstract

Background: We sought to assess the potential of insulin resistance (IR) for estimating cardiovascular disease (CVD) risk in adults with type 1 diabetes (T1DM) according to the scores of the Steno Type 1 Risk Engine (ST1RE). Methods: A total of 179 adults with T1DM (50.8% men, age 41.2 ± 13.1 years, duration of T1DM 16 (12–23) years) without established CVD were evaluated. IR was assessed by the estimation of insulin sensitivity (eIS) using two validated prediction equations: the estimated insulin sensitivity developed from the Pittsburgh Epidemiology of Diabetes Complications Study (eIS-EDC) and the estimated insulin sensitivity developed from Coronary Artery Calcification in T1DM Study (eIS-CACTI) ST1RE was used to estimate 10-year CVD risk and to classify subjects into three groups according to their risk: low (<10%; n = 105), moderate (10–20%; n = 53), and high (≥20%; n = 21). Results: Both eIS-EDC and eIS-CACTI correlated negatively with ST1RE scores (eIS-EDC: r = −0.636, p < 0.001; eIS-CACTI: r = −0.291, p < 0.001). The C-statistic for predicting moderate/high risk and high risk was 0.816 (95% confidence interval (CI): 0.754–0.878) and 0.843 (95% CI: 0.772–0.913), respectively, for the eIS-EDC equation, and was 0.686 (95% CI: 0.609–0.763) and 0.646 (95% CI: 0.513–0.778), respectively, for the eIS-CACTI equation. The eIS-EDC equation had a significantly higher C-statistic both for moderate-/high-risk (p = 0.001) and high-risk (p = 0.007) subjects. Two cut-off points of eIS-EDC were identified for detecting moderate/high risk (8.52 mg·kg−1·min−1; sensitivity 74% and specificity 76%) and high risk (8.08 mg·kg−1·min−1; sensitivity 65% and specificity 95%) with potential applicability in clinical practice. Conclusions: eIS negatively correlates with the score of CVD risk in the ST1RE. Two cut-off points of eIS are reported with potential utility in clinical practice for detecting adults with T1DM with the highest CVD risk.