Best multiple logistic regression model for predicting silent myocardial ischemia.

<p>Best multiple logistic regression model for predicting silent myocardial ischemia.</p

ROC curves to detect Silent Myocardial Ischemia (SMI).

<p>The area under the curve (AUC) of the three risk scores tended to underestimate SMI risk when compared with our proposed model. <b>1A)</b> Comparison with the Framingham Risk Score [0.833 (95% CI: 0.692–0.974) vs. 0.688 (95% CI: 0.545–0.830, p = 0.122)]. <b>1B)</b> Comparison with the UKPDS Risk Score [0.833 (95% CI: 0.692–0.974) vs. 0.559 (95% CI: 0.424–0.693), p = 0.001]. <b>1C)</b> Comparison with the EDC Risk Score [0.833 (95% CI: 0.692–0.974) vs. 0.558 (95% CI: 0.352–0.763), p = 0.027].</p

Unadjusted odds ratio for the presence of SMI (univariate analysis).

<p>Unadjusted odds ratio for the presence of SMI (univariate analysis).</p

Clinical and metabolic characteristics of patients with type 1 diabetes.

<p>Clinical and metabolic characteristics of patients with type 1 diabetes.</p