The Prevalence of Metabolic Syndrome in Coronary Artery Disease Patients
Bibliographic record
Abstract
BACKGROUND: Metabolic syndrome (MetS) is a worldwide health problem, which is growing in Iranian adults. MetS is associated with risk of type 2 diabetes and coronary artery disease (CAD). In this study, we aimed to investigate the prevalence of MetS and its individual components in CAD patients. METHODS: This cross-sectional study was performed on 200 CAD patients who had undergone elective coronary angiography at the cardiology department. Anthropometric indices including waist circumference (WC) and body mass index were measured. Blood samples were obtained to determine glucose and lipid profile. MetS components were defined according to the modified Adult Treatment Panel III (ATP III) criteria. RESULTS: The prevalence of MetS among patients was 49.5% (women: 55.9%; men: 40.2%; P < 0.05). The prevalence increased with age. The low high-density lipoprotein-cholesterol (low HDL-C) (84.8%), high fasting blood glucose (high FBG) (77.8%) and high WC (75.8%) were the most prevalent risk factors in CAD patients with MetS. CONCLUSIONS: Recent data indicate that the dyslipidemia, hyperglycemia and abdominal obesity are crucial predictors of MetS in CAD patients. Further prospective studies are recommended for more clarification.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".