Morbid Obesity is Not a Risk Factor for the Development of Clinically Significant Coronary Artery Atherosclerosis
Bibliographic record
Abstract
Morbid obesity represents a significant health problem to a large and growing segment of the industrialized world. The cardiovascular complications are numerous and include systemic and pulmonary hypertension, obesity cardiomyopathy, heart failure, left ventricular dilatation and hypertrophy, arrhythmias, and sudden cardiac death. Morbidly obese (MO) individuals who die suddenly and unexpectedly may not have significant coronary artery atherosclerosis or acutely lethal natural diseases at autopsy. In this way, forensic pathologists may be challenged to understand the mechanism of sudden death when the major anatomic finding is often limited to cardiomegaly with or without chamber dilatation and wall thickening. The death investigation files for a large metropolitan medical examiner department were the source of data in this case-control retrospective study. A total of 3863 cases met inclusion criteria. The following data were obtained: sex, age, cause of death, manner of death, weight in pounds, height in inches, body mass index, heart weight in grams, and coronary artery atherosclerosis (CAA) severity. A population of MO decedents (N = 1290) was identified, and sex- and age-matched case controls of non-obese decedents (N = 2573) were selected. The degree of CAA was recorded for all major vascular territories in both MO decedents and control cases, and there was no statistically significant difference in CAA between decedents in the MO group and the control group. These data illustrate that obesity is not a significant independent risk factor for CAA.
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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 | 0.004 |
| 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".