Author, as appears in the article.: Llauradó G; Cano A; Hernández C; González-Sastre M; Rodríguez A; Puntí J; Berlanga E; Albert L; Simó R; Vendrell J; Clemente J
Department: Medicina i Cirurgia
URV's Author/s: Vendrell Ortega, Juan José
Abstract: © 2017 Llauradó et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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.
Thematic Areas: Zootecnia / recursos pesqueiros Sociology Sociología Serviço social Saúde coletiva Química Psychology Psicología Planejamento urbano e regional / demografia Odontología Nutrição Multidisciplinary sciences Multidisciplinary Medicine (miscellaneous) Medicina veterinaria Medicina iii Medicina ii Medicina i Materiais Matemática / probabilidade e estatística Linguística e literatura Letras / linguística Interdisciplinary research in the social sciences Interdisciplinar Human geography and urban studies History & philosophy of science Historia Geografía Geociências General medicine General biochemistry,genetics and molecular biology General agricultural and biological sciences Farmacia Environmental studies Ensino Engenharias iv Engenharias iii Engenharias ii Engenharias i Enfermagem Educação física Educação Economia Direito Demography Comunicação e informação Ciências sociais aplicadas i Ciências biológicas iii Ciências biológicas ii Ciências biológicas i Ciências ambientais Ciências agrárias i Ciência política e relações internacionais Ciência de alimentos Ciência da computação Biotecnología Biology Biodiversidade Biochemistry, genetics and molecular biology (miscellaneous) Astronomia / física Arquitetura, urbanismo e design Archaeology Antropologia / arqueologia Anthropology Agricultural and biological sciences (miscellaneous) Administração, ciências contábeis e turismo Administração pública e de empresas, ciências contábeis e turismo
licence for use: https://creativecommons.org/licenses/by/3.0/es/
ISSN: 19326203
Author's mail: juanjose.vendrell@urv.cat
Author identifier: 0000-0002-6994-6115
Record's date: 2024-09-07
Papper version: info:eu-repo/semantics/publishedVersion
Link to the original source: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0174640
Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
Papper original source: Plos One. 12 (4): e0174640-
APA: Llauradó G; Cano A; Hernández C; González-Sastre M; Rodríguez A; Puntí J; Berlanga E; Albert L; Simó R; Vendrell J; Clemente J (2017). Type 1 diabetes: Developing the first riskestimation model for predicting silent myocardial ischemia. The potential role of insulin resistance. Plos One, 12(4), e0174640-. DOI: 10.1371/journal.pone.0174640
Article's DOI: 10.1371/journal.pone.0174640
Entity: Universitat Rovira i Virgili
Journal publication year: 2017
Publication Type: Journal Publications
Repositori URV