Cardiorenal outcomes in eligible patients referred for bariatric surgery
Bibliographic record
Abstract
OBJECTIVE: Bariatric surgery is associated with reduced atherosclerotic cardiovascular disease (CVD) and heart failure hospitalization in people with type 2 diabetes (T2D) and those with prior CVD. Most patients undergoing bariatric surgery do not have T2D or CVD. Many otherwise eligible patients do not have surgery because of self-exclusion. Clinical outcomes in these groups are less established. METHODS: This study retrospectively assessed cardiorenal outcomes in 8,568 patients after acceptance of referral for surgery. RESULTS: A total of 63.8% patients did not undergo surgery. After multivariate adjustment for sex, age, BMI, income quintile, distance from hospital, hypertension, T2D, and CVD, hazard ratios (HR) for the primary (incident myocardial infarction, stroke, heart failure hospitalization, and death; HR = 0.52, 95% CI: 0.4-0.66) and secondary CVD outcomes (primary outcomes and coronary/carotid revascularization; HR = 0.53, 95% CI: 0.42-0.67) were lower in the surgery cohort. This reduction was seen in those with (primary: HR = 0.45, 95% CI: 0.32-0.63, secondary: HR = 0.47, 95% CI: 0.34-0.65) and without T2D (primary: HR = 0.61, 95% CI: 0.42-0.88, secondary: HR = 0.53, 95% CI: 0.42-0.67). Reduced kidney disease (HR = 0.46, 95% CI: 0.22-0.92) but increased liver disease hospitalization (HR = 2.5, 95% CI: 1.45-4.27) was observed with surgery. CONCLUSIONS: Non-progression to surgery associates with increased CVD despite low baseline prevalence of CVD. The cardiorenal benefits of bariatric surgery warrant confirmation in a well-powered randomized clinical trial.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".