The relationship between body mass index, treatment, and mortality in patients with established coronary artery disease: a report from APPROACH
Bibliographic record
Abstract
Aims Our objective was to examine the association between body mass index (BMI) and survival according to the type of treatment in individuals with established coronary artery disease (CAD). Methods and results Patients with CAD were identified in the Alberta Provincial Project for Outcome Assessment in Coronary Heart Disease (APPROACH) registry between January 2001 and March 2006. Analyses were conducted separately by treatment strategy [medical management only, percutaneous coronary intervention (PCI), or coronary artery bypass grafting (CABG)]. Patients were grouped according to six BMI categories. Multivariable-adjusted hazard ratios (HRs) for mortality were calculated using the Cox regression with the referent group for all analyses being normal BMI (18.5-24.9 kg/m(2)). The cohort included 31 021 patients with a median follow-up time of 46 months. In the medically managed only group, BMIs of 25.0-29.9 and 30.0-34.9 kg/m(2) were associated with significantly lower mortality compared with normal BMI patients (adjusted HR 0.72; 95% CI 0.63-0.83 and adjusted HR 0.82; 95% CI 0.69.0-0.98, respectively). In the CABG group, BMI of 30.0-34.9 kg/m(2) had the lowest risk of mortality (adjusted HR 0.75; 95% CI 0.61-0.94), whereas in the PCI group, BMI of 35.0-39.9 kg/m(2) had the lowest risk of mortality (adjusted HR 0.65; 95% CI 0.47-0.90). Patients who were overweight or have mild or moderate obesity were also more likely to undergo revascularization procedures compared with those with normal BMI, despite having lower risk coronary anatomy. Conclusion A paradoxical association between BMI and survival exists in patients with established CAD irrespective of treatment strategy. Patients with obesity may be presenting earlier and receiving more aggressive treatment compared with those with normal BMI.
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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) | 0.001 | 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".