Abdominal Panniculectomy After Bariatric Surgery: An Unmet Need in the Bariatric Population
Bibliographic record
Abstract
Introduction: Panniculectomies are performed relatively infrequently despite demand for this procedure among bariatric surgery patients. Materials and Methods: In this multicomponent study, a survey of postbariatric surgery patients more than 6 months postop was distributed at the Edmonton Adult Bariatric Specialty Clinic from July 2017 to April 2018 and a survey of 245 plastic, bariatric, and general surgeons in the province of Alberta was administered online. Results: Of 87 postbariatric surgery patients surveyed, 90.6% were satisfied with the result of their bariatric surgery, yet 69.1% reported at least one issue relating to excess skin and 90.7% were interested in undergoing panniculectomy for excess abdominal skin. Among 22 general and 11 plastic surgeons surveyed, 41% of whom reported performing panniculectomy, 74% agreed that postbariatric panniculectomy is a medical necessity, but the majority of surgeons not already performing panniculectomy would not include it in their practice due to lack of interest, lack of operating room time, and inadequate financial compensation. Conclusion: There is significant demand for panniculectomy, but few surgeons are interested in performing panniculectomy, leaving a considerable care gap.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".