Bariatric Surgery Outcomes in US Accredited vs Non-Accredited Centers: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Accreditation for bariatric surgery has been scrutinized recently for its impact on surgical outcomes. This study aimed to systematically examine the medical literature to examine the impact of bariatric accreditation on surgical outcomes. STUDY DESIGN: The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and checklist were used. The MEDLINE database was searched for the following terms (2000 through September 2014): gastric bypass or bariatric surgery or sleeve gastrectomy or vertical banded gastroplasty or biliopancreatic diversion or duodenal switch or adjustable gastric band or weight loss surgery and accreditation or center of excellence or credentialing or national coverage decision or CMS or Medicare. Only studies in English and articles comparing accredited with non-accredited centers were included. Quality was assessed using the Newcastle-Ottawa scale for evaluation of all studies. RESULTS: Thirteen studies were published in a very short time frame and covered >1.5 million patients. Ten of the 13 studies identified a substantial benefit of Center of Excellence accreditation for risk-adjusted outcomes. Six of the 8 studies reported a considerable reduction in mortality in patients operated on in Centers of Excellence, with odds ratios ranging from 2.26 to 3.57 for non-accredited centers; 2 studies showed no significant difference. Similarly, morbidity was reduced in 8 of 11 studies, although more discreetly, with odds ratios ranging from 1.09 to 1.39. CONCLUSIONS: This study found that the preponderance of medical evidence supports accreditation for bariatric 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 | 0.018 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.012 |
| Bibliometrics | 0.016 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".