Author, as appears in the article.: Vendrell, J.; Llauradó, G.; Cano, A.; Hernández, C.; González-Sastre, M.; Rodríguez, A.-A.; Puntí, J.; Berlanga, E.; Albert, L.; Simó, R.; Clemente, J.-M.G.

Department: Medicina i Cirurgia

URV's Author/s: VENDRELL ORTEGA, JUAN JOSÉ; Llauradó, G.; Cano, A.; Hernández, C.; González-Sastre, M.; Rodríguez, A.-A.; Puntí, J.; Berlanga, E.; Albert, L.; Simó, R.; Clemente, J.-M.G.

Keywords: Està en blanc

Abstract: 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.

Research group: Grup de Recerca Biomèdica HJ23

Thematic Areas: Health sciences Ciencias de la salud Ciències de la salut

licence for use: https://creativecommons.org/licenses/by/3.0/es/

ISSN: 1932-6203

Author identifier: N/D; N/D; N/D; N/D; N/D; N/D; N/D; N/D; N/D; N/D; N/D

Record's date: 2017-04-21

Journal volume: 12

Papper version: info:eu-repo/semantics/publishedVersion

Link to the original source: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0174640

Article's DOI: 10.1371/journal.pone.0174640

Entity: Universitat Rovira i Virgili

Journal publication year: 2017

Publication Type: Article Artículo Article