Magnetic duodenoileal anastomosis with sleeve gastrectomy: a prospective multicenter study
Bibliographic record
Abstract
BACKGROUND: Magnetic digestive anastomosis has the potential to reduce anastomotic complications and complexity. We report the 1-year results of a new surgical technique using Self-forming Neodymium magnet Anastomosis Procedure with Sleeve gastrectomy (SNAP-S; GI Windows). METHODS: This was a prospective, nonrandomized multicenter trial. Participants with type 2 diabetes (T2D) who met criteria for metabolic surgery were recruited. A dual-path duodenoileal anastomosis was created at 300 cm from the ileocecal valve using circular magnetic anastomosis. The proximal magnet was deployed by endoscopy and the distal one by laparoscopy. Sleeve gastrectomy was performed at the same time. Data are reported as mean ± standard deviation or percentage. RESULTS: , hemoglobin A1C 7.3 ± 1.3%). There was no conversion, mortality, or adverse event related to the magnetic anastomosis. Mean time for anastomosis creation was 32 ± 10 minutes. One patient was not implanted because of an inability to bring the ileum to the duodenum. Follow-up rate at 12 months was 95%. A total of 41 procedure-related adverse events were recorded during follow-up. Seven events in 4 subjects were considered serious. Total weight loss at 3, 6, and 12 months was 22 ± 19%, 28 ± 19%, and 31 ± 11%, respectively. Excess weight loss was 45 ± 14%, 59 ± 21%, and 78 ± 33%, respectively. All patients had an hemoglobin A1C ≤6.0% at 12 months with complete T2D remission in 78%. CONCLUSION: The SNAP-S procedure is feasible with a low complication rate related to the anastomotic technique itself. The SNAP-S procedure provides significant weight loss and improvement of comorbidities. Additional prospective data are needed to better define the place of SNAP-S procedure.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".