Dataset Information

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

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.

SUBMITTER: Llaurado G

PROVIDER: S-EPMC5378337 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Publications

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

Llauradó Gemma G Cano Albert A Hernández Cristina C González-Sastre Montserrat M Rodríguez Ato-Antonio AA Puntí Jordi J Berlanga Eugenio E Albert Lara L Simó Rafael R Vendrell Joan J González Clemente José-Miguel JM

PloS one 20170403 4

<h4>Objectives</h4>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.<h4>Research, design and methods</h4>Patie ...[more]

PMID: 28369151

Similar Datasets

Project description:Most guidelines recommend a systematic screening of asymptomatic high risk patients with diabetes for silent ischemia, but the clinical benefit of this strategy has not been demonstrated compared with the simple control of cardiovascular risk factors. We sought to determine whether referring asymptomatic diabetic patients for screening of silent ischemia decreases the risk of cardiovascular events compared with usual care.DYNAMIT was a prospective, randomized, open, blinded end-point multicenter trial run between 2000 and 2005, with a 3.5 year mean follow-up in ambulatory care in 45 French hospitals. The study included 631 male and female with diabetes aged 63.9 ± 5.1 years, with no evidence of coronary artery disease and at least 2 additional cardiovascular risk factors, receiving appropriate medical treatment. The patients were randomized centrally to either screening for silent ischemia using a bicycle exercise test or Dipyridamole Single Photon Emission Computed Tomography (N = 316), or follow-up without screening (N = 315). The main study end point was time to death from all causes, non-fatal myocardial infarction, non-fatal stroke, or heart failure requiring hospitalization or emergency service intervention. The results of a meta-analysis of DYNAMIT and DIAD, a similar study, are also presented.The study was discontinued prematurely because of difficulties in recruitment and a lower-than expected event rate. Follow-up was complete for 98.9% patients regarding mortality and for 97.5% regarding the main study end point. Silent ischemia detection procedure was positive or uncertain in 68 (21.5%) patients of the screening group. There was no significant difference between the screening and the usual care group for the main outcome (hazard ratio = 1.00 95%CI 0.59 to 1.71). The meta-analysis of these and DIAD results gave similar results, with narrower confidence intervals for each endpoint.These results suggest that the systematic detection of silent ischemia in high-risk asymptomatic patients with diabetes is unlikely to provide any major benefit on hard outcomes in patients whose cardiovascular risk is controlled by an optimal medical treatment.ClinicalTrials.gov: NCT00627783.

Dataset Information

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

Objectives

Research, design and methods

Results

Conclusion

Publications

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

Similar Datasets

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