Early results after laparoscopic Roux-en-Y gastric bypass: effect of the learning curve.
Bibliographic record
Abstract
INTRODUCTION: This study was performed to evaluate the safety and short-term efficacy of laparoscopic Roux-en-Y gastric bypass (LRYGB) for morbid obesity and to describe the relation between learning curve and short-term outcomes. METHODS: We collected a prospective database on the first 201 consecutive patients who underwent LRYGB by a single university-based, experienced bariatric surgeon over 24 months. We divided patients into 3 consecutive groups of 67 patients for analysis (Group 1, Group 2 and Group 3). RESULTS: The mean patient age was 37 (standard deviation [SD] 9) years; mean body mass index (BMI) was 49.2 (SD 8.3) kg/m2. BMI was similar in Groups 1 and 2 (mean 47.1, SD 5.9 and mean 48.7, SD 8.9 kg/m2) but increased in Group 3 (mean 52, SD 9.7 kg/m2, p < 0.01). Operative time decreased from 145 (SD 30) minutes in Group 1 to 114 (SD 24) minutes in Group 2 (p < 0.01) and was maintained at 119 (SD 23) minutes in Group 3. Early and late complication rates were 14.9% and 12.4%, respectively. Leak rates decreased from 6.0% in the first group to 1.5% in Groups 2 and 3, but they did not reach statistical significance. Anastomotic stricture rates decreased from 11.9% in Group 1 to 3.0% in Group 2 (p < 0.01). Overall excess weight loss for the entire series was 31.5% (SD 11.9%), 54.5% (SD 14.1%), 77.1% (SD 18.5%) and 82.1% (SD 17.5%) at 3, 6, 12 and 18 months, respectively. CONCLUSION: LRYGB can be performed with acceptable morbidity and short-term results during the learning curve. In our series, operative time and anastomotic stricture rates decreased with experience, despite an increase in mean BMI.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".