Key result
A novel risk-estimation model incorporating insulin resistance and active smoking predicted silent myocardial ischemia in patients with type 1 diabetes with an AUC of 0.833, outperforming the UKPDS and EDC risk equations.
Cross-Sectional (n=84)
No
A novel risk estimation model using only insulin resistance and active smoking accurately predicts silent myocardial ischemia in patients with type 1 diabetes, outperforming several established CAD risk scores.
Should not yet change screening in type 1 diabetes; leaves open prospective validation of the model.
OBJECTIVES: The aim of the study was to develop a novel risk estimation model for predicting silent myocardial ischemia (SMI) in patients with type 1 diabetes (T1DM) and no clinical cardiovascular disease, evaluating the potential role of insulin resistance in such a model. Additionally, the accuracy of this model was compared with currently available models for predicting clinical coronary artery disease (CAD) in general and diabetic populations. RESEARCH, DESIGN AND METHODS: Patients with T1DM (35-65years, >10-year duration) and no clinical cardiovascular disease were consecutively evaluated for: 1) clinical and anthropometric data (including classical cardiovascular risk factors), 2) insulin sensitivity (estimate of glucose disposal rate (eGDR)), and 3) SMI diagnosed by stress myocardial perfusion gated SPECTs. RESULTS: Eighty-four T1DM patients were evaluated [50.1±9.3 years, 50% men, 36.9% active smokers, T1DM duration: 19.0(15.9-27.5) years and eGDR 7.8(5.5-9.4)mg·kg-1·min-1]. Of these, ten were diagnosed with SMI (11.9%). Multivariate logistic regression models showed that only eGDR (OR = -0.593, p = 0.005) and active smoking (OR = 7.964, p = 0.018) were independently associated with SMI. The AUC of the ROC curve of this risk estimation model for predicting SMI was 0.833 (95%CI:0.692-0.974), higher than those obtained with the use of currently available models for predicting clinical CAD (Framingham Risk Equation: 0.833 vs. 0.688, p = 0.122; UKPDS Risk Engine (0.833 vs. 0.559; p = 0.001) and EDC equation: 0.833 vs. 0.558, p = 0.027). CONCLUSION: This study provides the first ever reported risk-estimation model for predicting SMI in T1DM. The model only includes insulin resistance and active smoking as main predictors of SMI.
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Llauradó et al. (2017) conducted a cross-sectional in Type 1 diabetes without clinical cardiovascular disease (n=84). Risk estimation model (insulin resistance and active smoking) vs. Currently available models (Framingham, UKPDS, EDC) was evaluated on Prediction of silent myocardial ischemia (SMI) (AUC 0.833, 95% CI 0.692-0.974). A novel risk-estimation model incorporating insulin resistance and active smoking predicted silent myocardial ischemia in patients with type 1 diabetes with an AUC of 0.833, outperforming the UKPDS and EDC risk equations.
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