Insulin resistance syndrome, body mass index and the risk of ischemic heart disease
Bibliographic record
Abstract
BACKGROUND: Many people who are not obese according to standard height and weight criteria may still display features of insulin resistance syndrome and thus be at high risk of ischemic heart disease. We sought to investigate the effect of cumulative features of insulin resistance syndrome on the risk of ischemic heart disease associated with variations in body mass index (BMI) among men who participated in the Quebec Cardiovascular Study. METHODS: A cohort of 1824 nondiabetic men free of ischemic heart disease was evaluated at the 1985 baseline evaluation and followed for a period of 13 years, during which 284 first ischemic heart disease events were recorded. Relative hazards (RHs) of ischemic heart disease in 3 BMI groups (normal weight, overweight and obese) were estimated using Cox proportional hazards regression. RESULTS: Although obese men (BMI > or = 30 kg/m2) were the most likely to accumulate features of insulin resistance syndrome, the univariate risk of ischemic heart disease in this group was not significantly increased compared with normal-weight men (BMI < 25 kg/m2) (RH 1.26, 95% confidence interval [CI] 0.88-1.80). However, obese men who accumulated more than 4 features of insulin resistance syndrome were at increased risk of ischemic heart disease (RH 1.81, 95% CI 1.02-3.19) compared with normal-weight men who had fewer than 3 features of the syndrome. Conversely, having more than 4 features of insulin resistance syndrome was associated with a 3-fold increase in the risk of ischemic heart disease among normal-weight men (RH 3.01, 95% CI 1.70-5.32). INTERPRETATION: Although obesity is an important risk factor for ischemic heart disease, variations in BMI alone poorly reflect the risk of ischemic heart disease associated with features of insulin resistance syndrome.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".