Third bariatric procedure for insufficient weight loss or weight regain: how far should we go?
Bibliographic record
Abstract
Background Revisional procedures in bariatric surgery are increasing with several debated failure risk factors, such as super obesity and old age. No study has yet evaluated the outcomes and risks of a third bariatric procedure indicated for weight loss failure or weight regain. Objectives To assess failure risks of a third bariatric procedure according to Reinhold's criteria (percentage excess weight loss [%EWL] ≤50% and/or body mass index [BMI] ≥35 kg/m 2 ). Setting A university-affiliated tertiary care center, France. Methods From 2009 to 2019, clinical data and weight loss results of patients who benefited from 3 bariatric procedures for weight loss failure or weight regain were collected prospectively and analyzed using a binary logistic regression. Weight loss failure was defined according to Reinhold's criteria. Results Among 1401 bariatric procedures performed, 336 patients benefited from 2 or more procedures, and 45 had a third surgery. Eleven patients that were reoperated on because of malnutrition or gastroesophageal reflux disease were excluded from the final analysis. Among 34 patients with 3 procedures because of weight loss failure or regain, mean BMI was 48.3 ± 8.3 kg/m 2 , and mean age was 30 ± 10.7 years. Three out of 34 patients (9%) presented a severe complication (Dindo-Clavien IIIb) and 2 (6%) had a minor one. Achieving Reinhold's weight loss criteria after the second bariatric procedure was a significant predictor of success of the third procedure (β = 2.9 ± 1.3 S.E.). Conclusion Not reaching Reinhold's criteria after a second bariatric procedure was identified as a significant risk factor of failure of a third procedure. A third surgery should be carefully discussed especially in case of primary failure of previous procedures.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.012 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".