Laparoscopy in Acute Care Surgery: Repair of Perforated Duodenal Ulcer
Bibliographic record
Abstract
INTRODUCTION: The use of laparoscopic management as a first choice for the treatment of duodenal perforation is gaining ground but is not routine in many centers. In this report, we aim to report our experience with laparoscopy as the first approach for the repair of duodenal perforation. MATERIALS AND METHODS: This is a retrospective review of patients during our initial experience with the use of laparoscopy for the treatment of duodenal perforation between 2009 and 2013. RESULTS: A total of 100 patients underwent management of duodenal perforation. Laparoscopy was attempted initially in 76 patients (76%) and completed in 64 patients (64%). The length of hospital stay was shorter in the laparoscopic group (mean 2.6) than in the open group (mean 3.1) (p = 0.008). Complications developed in 14 patients (20%). There was a tendency towards fewer admissions to intensive care, less acute kidney injuries, and less acute respiratory distress syndrome in the laparoscopic group. In patients who underwent laparoscopic surgery, the chances of uneventful recovery were 4.3 times higher than in those patients who underwent open surgery (95% CI 1.3-13.5, p = 0.014). CONCLUSIONS: Laparoscopy in the treatment of perforated duodenal ulcer is safe and can be utilized as a routine approach for the treatment of this pathology.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".