Indications and Outcomes of Laparoscopic Versus Robotic Conversional Bariatric Surgery: An MBSAQIP Study
Bibliographic record
Abstract
BACKGROUND: Conversional bariatric surgeries (CBS) are performed using laparoscopic and robotic techniques, but comprehensive data comparing these approaches remains scarce. OBJECTIVE: To compare the indications and outcomes of laparoscopic versus robotic CBS. METHODS: The MBSAQIP database was retrospectively analyzed from 2020 to 2022, comparing laparoscopic and robotic CBS. Primary outcomes were 30-day serious complications and mortality. RESULTS: Of 72,189 CBS procedures, 75.4% were laparoscopic and 24.6% robotic. Mean age and BMI were similar between groups. The most common indications for both approaches were reflux, weight regain, and inadequate weight loss, with reflux being more prevalent in robotic CBS (38.3% vs 33.2%). Sleeve-to-bypass was the most common procedure in both groups (35.8% laparoscopic, 44.2% robotic). Robotic CBS had longer mean operative times (165.4 vs 121.7 min, p < 0.001) and slightly longer hospital stays (1.7 vs 1.6 days, p < 0.001). The rate of serious complications was slightly higher for robotic CBS, though not statistically significant (6.5% vs 6.1%, p = 0.08). Robotic CBS had higher rates of leak (0.9% vs 0.7%, p = 0.071), reoperation (2.8% vs 2.6%, p = 0.138), and readmission (6.7% vs 5.4%, p < 0.001). Mortality rates were similar (0.1% for both, p = 0.942). CONCLUSIONS: Both laparoscopic and robotic CBS show similar safety profiles with comparable mortality rates. However, robotic CBS was associated with longer operative times, slightly longer hospital stays, and higher readmission rates. These findings suggest that the choice between approaches should consider individual patient factors and institutional expertise.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".