Volume-Outcome Association in Bariatric Surgery
Bibliographic record
Abstract
OBJECTIVE: To systematically examine the association between annual hospital and surgeon case volume and patient outcomes in bariatric surgery. BACKGROUND: Bariatric surgery remains a technically demanding field with significant risk for morbidity and mortality. To mitigate this risk, minimum annual hospital and surgeon case volume requirements are being set and certain hospitals are being designated as "Bariatric Surgery Centers of Excellence." The effects of these interventions on patient outcomes remain unclear. METHODS: A comprehensive systematic review on volume-outcome association in bariatric surgery was conducted by searching MEDLINE, Cochrane Database of Systematic Reviews, and Evidence Based Medicine Reviews databases. Abstracts of identified articles were reviewed and pertinent full-text versions were retrieved. Manual search of bibliographies was performed and relevant studies were retrieved. Methodological quality assessment and data extraction were completed in a systematic fashion. Pooling of results was not feasible due to the heterogeneity of the studies. A qualitative summary of results is presented. RESULTS: From a total of 2928 unique citations, 24 studies involving a total of 458,032 patients were selected for review. Two studies were prospective cohorts (level of evidence [LOE] 1), 3 were retrospective cohorts (LOE 3), 2 were retrospective case controls (LOE 3), and 17 were retrospective case series (LOE 4). The overall methodological quality of the reviewed studies was fair. A positive association between annual surgeon volume and patient outcomes was reported in 11 of 13 studies. A positive association between annual hospital volume and patient outcomes was reported in 14 of 17 studies. CONCLUSIONS: There is strong evidence of improved patient outcomes in the hands of high-volume surgeons and high-volume centers. This study supports the concept of "Bariatric Surgery Center of Excellence" accreditation; however, future research into the quality of care characteristics of successful bariatric programs is recommended. Understanding the characteristics of high-volume surgeons, which lead to improved patient outcomes, also requires further investigation.
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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 | 0.022 | 0.106 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 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".