Endoloop versus endostapler closure of the appendiceal stump in pediatric laparoscopic appendectomy
Bibliographic record
Abstract
BACKGROUND: There is little information available to inform choice of technique for appendiceal stump control in pediatric laparoscopic appendectomy (LA). We compared complications (stump leak, intra-abdominal abscess formation [IAA], surgical site infection [SSI]) in children undergoing LA for perforated (PA) and nonperforated appendicitis (NPA) by technique of appendiceal stump control. METHODS: All children who underwent LA for confirmed acute appendicitis between 2006 and 2009 were reviewed. Choice of stump control (endoloop [EL] or endostapler [ES]) was determined by surgeon preference. Interactions between stump closure techniques and other potential confounders (intra-abdominal drain, irrigation, different antibiotic regimens) were explored using a logistic regression model. RESULTS: Of 242 patients undergoing LA, 57 (23.6%) had PA. In the PA group the appendiceal stump was closed with EL in 47 (82.5%) patients, while in the NPA group EL was used in 161 (87%) patients. Among PA patients, IAA was more common in the ES than the EL group (5 of 10 [50%] v. 6 of 47 [12.7%]). There was no significant difference in rates of SSI. Among NPA patients, there were no differences in rates of IAA or SSI. There were no stump leaks in either group. Logistic regression analysis confirmed the predictive effect of ES use on IAA formation in PA (adjusted odds ratio 7.09; 95% confidence interval 1.08-46.13; p = 0.042). CONCLUSION: Our data suggest that in most cases of PA, the appendiceal stump can be safely controlled with EL. Within the PA group, the higher rates of IAA seen in ES patients may be attributable to the quality of the appendiceal stump rather than the technique of closure.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".