Laparoscopic Sleeve Gastrectomy Versus Laparoscopic Roux-en-Y Gastric Bypass
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to compare weight loss, obesity-related comorbidities, and biochemical outcomes of LSG versus LRYGB through a meta-analysis of randomized controlled trials (RCTs). SUMMARY OF BACKGROUND DATA: LSG and LRYGB are the 2 most commonly performed bariatric surgeries for the treatment of obesity. The comparative outcomes of the 2 surgeries is a topic of ongoing debate and medium-term outcomes remain uncertain. METHODS: A search for RCTs comparing LRYGB versus LSG was conducted. Pooled outcomes between 2 procedures were compared using pairwise random-effects meta-analysis at 1, 3, and 5-year follow-up time points. Grading of recommendations, assessment, development, and evaluation was used to assess certainty of evidence. RESULTS: Thirty-three studies involving 2475 patients were included. LRYGB resulted in greater loss of body mass index compared to LSG at 1 year [mean difference -1.25 kg/m2, 95% confidence interval (CI) -2.01 to -0.49, P = 0.001; moderate certainty of evidence] which persisted at 3 years, but there was insufficient evidence at 5 years. Resolution of dyslipidemia was higher for LRYGB than LSG at 1 year (risk ratio 0.58, 95% CI 0.46-0.73, P < 0.001; moderate certainty of evidence) and 5 years (risk ratio 0.68, 95%CI 0.46-0.99, P = 0.04; low certainty of evidence). There was no difference between LRYGB and LSG for remission of type 2 diabetes, hypertension, and hemoglobin A1c, fasting insulin, homeostatic model assessment of insulin resistance, high-density lipoprotein, and the rate of 30-day major and minor complications. CONCLUSIONS: There are insufficient data from RCTs to draw any conclusions regarding the long-term comparative effectiveness beyond 3 years between LRYGB and LSG.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.016 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".