ArticleArchives of medical sciences. Atherosclerotic diseases2018
All-cause mortality of metabolically healthy or unhealthy obese: risk stratification using myocardial perfusion imaging.
Article in Archives of medical sciences. Atherosclerotic diseases, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Treatment goal attainment for secondary prevention in coronary patients with or without diabetes mellitus - Polish multicenter study POLASPIRE.Archives of medical science : AMS · 2023Article
- Automated quantitative analysis of CZT SPECT stratifies cardiovascular risk in the obese population: Analysis of the REFINE SPECT registry.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2022Article
- Prevalence and clinical characteristics of metabolically unhealthy obesity in an Iranian adult population.Diabetes, metabolic syndrome and obesity : targets and therapy · 2019Article
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3 authors.
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Abstract
introductionThere is still controversy about the favorable prognosis of "metabolically healthy" (MH) obese. This study evaluated mortality and the use of myocardial perfusion scintigraphy (MPS) for risk stratification of MH or metabolically unhealthy (MU) obese or nonobese patients. MATERIAL AND
methodsPatients without dyslipidemia, hypertension, or diabetes were considered MH, and those with ≥ 1 of these risk factors were considered MU. The MPS was categorized as normal, abnormal or ischemic. Patients were followed for 4.0 ±1.0 years for all-cause death.
resultsOf 2450 patients, 613 were obese. The MH obese patients less often had ischemia than MU obese, but there was no significant difference in the prevalence of ischemia compared to all nonobese. The annualized death rate of MH obese was 1.3% and of nonobese 1.0% (
conclusionsThe annualized death rate of MH obese patients was not significantly different from that of nonobese individuals. Myocardial perfusion scintigraphy was able to stratify prognosis in the overall patient population. These data may be helpful to identify high-risk individuals, thereby improving patient management.
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