RESUMO
BACKGROUND AND AIMS: Carotid intima-media thickness (cIMT) is inconsistent in predicting cardiovascular risk. This may stem from the variability of the media thickness (cM) outweighing the intimal thickness (cIT) as the sign of atherosclerosis. Thus, we evaluated in type 2 diabetes (T2D) individuals, the association between carotid measures and coronary artery calcification (CAC). METHODS AND RESULTS: Association between the presence of CAC and cIT, cM, and cIMT were examined on 224 individuals. Logistic binary regression was used to assess CAC predictors. The Akaike information criterion (AIC) and log-likelihood test (LLT) were used to assess differences among univariate models. The cIT (0.335 mm vs 0.363 mm; p = 0.001) and cIMT (0.715 vs 0.730; p = 0.019), but not cM (0.386 mm vs 0,393 mm; p = 0.089) were higher among individuals with CAC. In unadjusted analysis, cIT (273;-134; p = 0.001) showed greater relationship with CAC, when compared to cIMT (279;-137; p = 0.022) and cM (281;-139; p = 0.112) based on the AIC and LLT, respectively. In multivariate logistic regression, CAC was related to carotid plaque (OR): 1.91, 95% confidence interval (CI):1.08, 3.38; p = 0.027), and high-cIT (OR: 2.70, 95%CI:1.51, 4.84; p = 0.001), but not to high-cIMT (OR:1.70, 95%CI:0.96, 3.00; p = 0.067) nor high-cM (OR:1.33, 95%CI:0.76, 2.34; p = 0.322). CONCLUSION: In T2D individuals, cIT is a better predictor of CAC than cIMT; cM is not associated with CAC.
Assuntos
Doenças das Artérias Carótidas , Doença da Artéria Coronariana , Diabetes Mellitus Tipo 2 , Humanos , Espessura Intima-Media Carotídea , Diabetes Mellitus Tipo 2/complicações , Diabetes Mellitus Tipo 2/diagnóstico , Diabetes Mellitus Tipo 2/epidemiologia , Brasil/epidemiologia , Doença da Artéria Coronariana/diagnóstico por imagem , Doença da Artéria Coronariana/epidemiologia , Doença da Artéria Coronariana/etiologia , Fatores de Risco , Doenças das Artérias Carótidas/diagnóstico por imagem , Doenças das Artérias Carótidas/epidemiologia , Doenças das Artérias Carótidas/etiologiaRESUMO
BACKGROUND: Optimal control of traditional risk factors only partially attenuates the exceeding cardiovascular mortality of individuals with diabetes. Employment of machine learning (ML) techniques aimed at the identification of novel features of risk prediction is a compelling target to tackle residual cardiovascular risk. The objective of this study is to identify clinical phenotypes of T2D which are more prone to developing cardiovascular disease. METHODS: The Brazilian Diabetes Study is a single-center, ongoing, prospective registry of T2D individuals. Eligible patients are 30 years old or older, with a confirmed T2D diagnosis. After an initial visit for the signature of the informed consent form and medical history registration, all volunteers undergo biochemical analysis, echocardiography, carotid ultrasound, ophthalmologist visit, dual x-ray absorptiometry, coronary artery calcium score, polyneuropathy assessment, advanced glycation end-products reader, and ambulatory blood pressure monitoring. A 5-year follow-up will be conducted by yearly phone interviews for endpoints disclosure. The primary endpoint is the difference between ML-based clinical phenotypes in the incidence of a composite of death, myocardial infarction, revascularization, and stroke. Since June/2016, 1030 patients (mean age: 57 years, diabetes duration of 9.7 years, 58% male) were enrolled in our study. The mean follow-up time was 3.7 years in October/2021. CONCLUSION: The BDS will be the first large population-based cohort dedicated to the identification of clinical phenotypes of T2D at higher risk of cardiovascular events. Data derived from this study will provide valuable information on risk estimation and prevention of cardiovascular and other diabetes-related events. CLINICALTRIALS.GOV IDENTIFIER: NCT04949152.