Coronary artery disease risk among obese metabolically healthy young men
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to assess coronary artery disease (CAD) risk among obese young men without metabolic risk factors. DESIGN: A longitudinal study in a historical cohort. METHODS: Incident CAD during a median follow-up of 6.1 years was assessed among 31,684 young men (mean age 31.2 ± 5.7 years) of the Metabolic, Lifestyle and Nutrition Assessment in Young Adults (MELANY) cohort. Participants were categorized by BMI and the number of metabolic abnormalities (based on the Adult Treatment Panel-III). Metabolically healthy (MH) obesity was defined as BMI ≥ 30 kg/m(2) in the presence of normal blood pressure (BP) and normal levels of fasting glucose, triglyceride, and HDL-cholesterol (HDL-c) levels (n = 599; 1.9%). Cox proportional hazard models were applied. RESULTS: There were 198 new cases of CAD that were diagnosed during 209,971 person-years of follow-up, of which six cases occurred among MH obese. The incidence of CAD among MH lean, overweight, and obese participants was 0.23, 0.45, and 1.0/1000 person-years respectively. In a multivariable model adjusted for clinical and biochemical CAD risk factors, a higher CAD risk was observed among MH-obese (hazard ratio = 3.08; 95% CI = 1.10-8.68, P = 0.033), compared to MH-normal weight subjects. This risk persisted when BMI was treated as a time-dependent variable, or when fasting glucose, HDL-c, triglycerides, or BP were added to the model. Similar results were also obtained when a more permissive definition of MH was used. CONCLUSIONS: Obesity may continue to contribute to increased risk for incident CAD in young men even in the presence of a healthy metabolic profile.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".