Treatment Methods for Leakage Occurring at Staple Line After Laparoscopic Sleeve Gastrectomy
Bibliographic record
Abstract
In this presentation, medical literature regarding this topic was reviewed along with the evaluation of treatment methods used in two specific cases during which leakages occurred along the staple line after laparoscopic sleeve gastrectomy (LSG). One of the two patients who developed a leakage after LSG was a 26-year-old female (case 1) and the other was a 20-year-old female (case 2). Case 1 was explored, when a leakage was diagnosed through clinical and screening procedures on day 3 after the surgery. After determining the leakage, the defect was primarily sutured and a feeding jejunostomy was placed. Case 1 developed leakage again on the fourth day after the second surgery, an esophagogastric stent was performed three times whose drainage was cut off from the leakage line, and the patient was discharged with full recovery. However, case 2 then developed leakage on the 14th day after surgery. Next an esophagogastric stent was placed in the patient, and a computer tomography (CT)-guided percutaneous drainage was placed to drain the collections inside the abdomen. Four weeks after this procedure, the stent was removed and after specifying that the leakage had closed, the patient was discharged with full recovery. The treatment methods of gastric leakages after LSG are also variable, and the treatment method is designated depending on the dimension of the leakage, the extent of the abdominal contamination, and the location of the leakage. J Curr Surg. 2015;5(2-3):175-178 doi: http://dx.doi.org/10.14740/jcs269wÂ
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".