Laparoscopic Sleeve Gastrectomy for the Surgical Treatment of Obesity: Is It an Easy Procedure?
Bibliographic record
Abstract
Laparoscopic sleeve gastrectomy (LSG) is currently the most performed bariatric procedure in the world. The 4th International Federation for the Surgery of Obesity and Metabolic Disorders (IFSO) Global registry report (2014-18) estimates 87,015 procedures, equal to 45.9% of all bariatric procedures. Initially performed as the first step of the duodenals witch (biliopancreatic diversion with duodenal switch (BPD-DS)), a very complex malabsorptive procedure invented by a Canadian Surgeon P. Marceau as an evolution of the BPD, invented by N. Scopinaro, an Italian surgeon, LSG established itself in the early 2000s as a stand alone procedure, especially following the observations of Michael Gagner, pioneer of bariatric surgery. Over the years LSG has grown rapidly. The reasons for this popularity are the relative technical simplicity compared to other procedures, efficacy, good quality. For these reasons there has been a real explosion of bariatric surgery: many surgeons, driven by the relative simplicity of the procedure (longitudinal gastrectomy on the guide of a probe), begun to propose this procedure. So is LSG really an effective simple procedure that is good for all patients? Absolutely not. Performing a longitudinal gastrectomy can be simple; performing a good LSG is not.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".