Body Mass Index, Outcomes, and Mortality Following Cardiac Surgery in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: The "obesity paradox" reflects an observed relationship between obesity and decreased morbidity and mortality, suggesting improved health outcomes for obese individuals. Studies examining the relationship between high body mass index (BMI) and adverse outcomes after cardiac surgery have reported conflicting results. METHODS AND RESULTS: The study population (N=78 762) was comprised of adult patients who had undergone first-time coronary artery bypass (CABG) or combined CABG/aortic valve replacement (AVR) surgery from April 1, 1998 to October 31, 2011 in Ontario (data from the Institute for Clinical Evaluative Sciences). Perioperative outcomes and 5-year mortality among pre-defined BMI (kg/m(2)) categories (underweight <20, normal weight 20 to 24.9, overweight 25 to 29.9, obese 30 to 34.9, morbidly obese >34.9) were compared using Bivariate analyses and Cox multivariate regression analysis to investigate multiple confounders on the relationship between BMI and adverse outcomes. A reverse J-shaped curve was found between BMI and mortality with their respective hazard ratios. Independent of confounding variables, 30-day, 1-year, and 5-year survival rates were highest for the obese group of patients (99.1% [95% Confidence Interval {CI}, 98.9 to 99.2], 97.6% [95% CI, 97.3 to 97.8], and 90.0% [95% CI, 89.5 to 90.5], respectively), and perioperative complications lowest. Underweight and morbidly obese patients had higher mortality and incidence of adverse outcomes. CONCLUSIONS: Overweight and obese patients had lower mortality and adverse perioperative outcomes after cardiac surgery compared with normal weight, underweight, and morbidly obese patients. The "obesity paradox" was confirmed for overweight and moderately obese patients. This may impact health resource planning, shifting the focus to morbidly obese and underweight patients prior to, during, and after cardiac surgery.
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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 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".