Journal Article

Type 1 diabetes: Developing the first risk-estimation model for predicting silent myocardial ischemia. The potential role of insulin resistance

Albert, Lara, González-Sastre, Montserrat, Vendrell, Joan, González Clemente, José-Miguel, Cano, Albert, Hernández, Cristina, Rodríguez, Ato-Antonio, Berlanga, Eugenio, Llauradó, Gemma, Puntí, Jordi, Simó, Rafael

2017

Overview

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. 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. 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). 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.

• Publisher: Public Library of Science,Public Library of Science (PLoS)
• Subject: Adult / Aged / Algorithms / Autoimmune diseases / Biology and Life Sciences / Cardiology / Cardiovascular disease / Cardiovascular diseases / Chronic illnesses / Coronary artery / Coronary artery disease / Coronary Artery Disease - diagnosis / Coronary vessels / Diabetes / Diabetes mellitus / Diabetes mellitus (insulin dependent) / Diabetes Mellitus, Type 1 - pathology / Endocrinology / Female / Glucose / Health risk assessment / Health risks / Heart / Heart diseases / Hemoglobin / Humans / Immunology / Insulin / Insulin resistance / Insulin Resistance - physiology / Ischemia / Logistic Models / Male / Medicine and Health Sciences / Metabolic Syndrome - diagnosis / Metabolism / Middle Aged / Models, Theoretical / Myocardial ischemia / Myocardial Ischemia - diagnosis / Nutrition / Population / Prognosis / Regression analysis / Regression models / Risk Assessment / Risk Factors / Silent myocardial ischemia / Smoking / Type 1 diabetes / Vascular Stiffness - physiology