This report aims to compare the prediction of the metabolic syndrome (MetS) and its components for morbidity and mortality of coronary heart disease (CHD) in a cohort of Australian Aboriginal and Torres Strait Islander adults (TSIs). A total of 2,100 adults (1,283 Aborigines and 817 TSIs) was followed up for 6 years from 2000. Outcome measures were all CHD events (deaths and hospitalizations). Baseline anthropometric measurements, blood pressure (BP), fasting blood lipids and glucose were collected. Smoking and alcohol intake was self-reported. We found MetS was more prevalent in TSI (50.3%) compared to Aborigines (33.0%). Baseline MetS doubled the risk of a CHD event in Aborigines. Increased fasting triglycerides was stronger in predicting CHD (hazard ratio (HR): 2.8) compared with MetS after adjusted for age, sex, tobacco and alcohol consumption, and baseline diabetes and albuminuria for Aborigines but not among TSIs. MetS was not more powerful than its components in predicting CHD event. In Australian Aborigines, the "triglyceridemic waist" phenotype strongly predicts CHD event, whereas among TSI, baseline diabetes mediated the prediction of increased fasting glucose for CHD event.
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http://dx.doi.org/10.1038/oby.2011.156 | DOI Listing |
Front Med (Lausanne)
January 2025
Department of Emergency, Wuhan Fourth Hospital, Wuhan, Hubei, China.
Background: At present, the relationship among inflammatory markers [monocytes/HDL-c (MHR), neutrophils/HDL-c (NHR) and lymphocytes/HDL-c (LHR)] and long-term prognosis of coronary heart disease (CHD) is still unclear. Therefore, this study explores the relationship between inflammatory indicators and the risk of long-term major adverse cardiovascular events (MACE) in elderly patients with CHD.
Methods: A retrospective analysis was conducted on 208 elderly patients who underwent coronary angiography at Wuhan Fourth Hospital from August 2022 to August 2023.
Rev Cardiovasc Med
January 2025
Department of Cardiology, The Third Affiliated Hospital of Sun Yat-sen University, 510630 Guangzhou, Guangdong, China.
Background: Extensive research has established obstructive sleep apnea (OSA) as a contributing factor to numerous cardiovascular and cerebrovascular diseases. However, whether OSA affects in-stent restenosis (ISR) after elective drug-eluting stenting is unclear. Therefore, the objective of this study was to examine the impact of OSA on ISR in patients with coronary heart disease (CHD) who underwent successful elective drug-eluting stent (DES) implantation.
View Article and Find Full Text PDFJ Diabetes Investig
January 2025
Department of Diabetes, Endocrinology and Metabolism, Center Hospital, National Center for Global Health and Medicine, Tokyo, Japan.
Aim: To determine the epidemiological characteristics and risk factors for heart failure (HF) among Japanese patients with type 2 diabetes.
Methods: A retrospective cohort analysis, using J-DREAMS database, was conducted from December 2015 to January 2020 with type 2 diabetes. The primary objectives were to describe patient characteristics stratified by HF history at baseline and new HF events during follow-up.
J Cardiovasc Electrophysiol
January 2025
Department of Electrophysiology, German Heart Center Munich, TUM University Hospital, Munich, Bavaria, Germany.
Introduction: Data regarding safety and long-term outcome of very high-power-short duration (vHPSD) ablation in adult congenital heart disease (ACHD) patients with paroxysmal or persistent atrial fibrillation (AF) are lacking.
Methods: Retrospective observational single-center study. The data of 66 consecutive ACHD patients (mean age 60 ± 12.
Bioengineering (Basel)
December 2024
Department of Pathology, University of Yamanashi, Yamanashi 409-3898, Japan.
The latest World Health Organization (WHO) classification of central nervous system tumors (WHO2021/5th) has incorporated molecular information into the diagnosis of each brain tumor type including diffuse glioma. Therefore, an artificial intelligence (AI) framework for learning histological patterns and predicting important genetic events would be useful for future studies and applications. Using the concept of multiple-instance learning, we developed an AI framework named GLioma Image-level and Slide-level gene Predictor (GLISP) to predict nine genetic abnormalities in hematoxylin and eosin sections: , , mutations, promoter mutations, homozygous deletion (CHD), amplification (amp), 7 gain/10 loss (7+/10-), 1p/19q co-deletion, and promoter methylation.
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