Association of Waist-Hip Ratio to Sudden Cardiac Death and Severe Coronary Atherosclerosis in Medicolegal Autopsies
Bibliographic record
Abstract
Various modifiable and nonmodifiable risk factors, such as abdominal obesity, are known to affect the development of atherosclerotic cardiovascular disease and subsequent sudden cardiac death (SCD). The waist-hip ratio is a surrogate marker of visceral obesity that has been shown in various studies to be a better predictor of cardiovascular risk than the body mass index (BMI), a measurement of generalized obesity. Waist-hip ratio was measured prospectively on medicolegal autopsies performed for 1 year, in addition to standard measurements of BMI and heart weight, and histologic determination of severe coronary atherosclerosis (SCA, coronary artery diameter stenosis >75%). Logistic modeling was performed to determine any association between WHR, BMI, cardiovascular disease risk factors, heart weight, and SCD or SCA. Waist-hip ratio was not shown to be statistically significantly associated with either SCD (P = 0.68) or SCA (P = 0.14). Body mass index was shown to be significantly associated with SCA (P < 0.001), and heart weight was shown to be significantly associated with both SCD and SCA (P < 0.001, both). Waist-hip ratio, as a surrogate marker of central obesity and increased risk of atherosclerotic cardiovascular disease, is shown not to be statistically significantly associated with either SCD or SCA in postmortem cases.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".