Endoloops in Laparoscopic Appendicectomy: a Cost Effectiveness Analysis
Bibliographic record
Abstract
Introduction Over 50,000 appendicectomies are performed in the UK annually with significant associated costs to the healthcare system.The aim of this study was to investigate whether a significant difference in complication rate exists where different numbers of endoloop ligatures have been applied to the appendiceal base during laparoscopic appendicectomy, and to analyse for potential cost saving. Methods We performed a retrospective analysis of appendicectomies at our centre in one year, providing a sample of 254 patients. Cases were analysed against exclusion criteria, operative method, and histological findings. Each was followed up for complications in the 30 days post discharge and graded using the Clavien-Dindo system. Our null hypothesis of no difference in complication rate was tested using Fisher’s exact test. Results Of 254 patients, 59 were excluded due to open approach, non-endoloop method, or lack of available record, leaving a population of 195. The result of the two-tailed P value equalled 1.000, indicating no statistically significant difference in complication rate whether one or two endoloops were used. Regarding cost effectiveness, an endoloop costs £13.59. If the 62 cases in which 2 endoloops were used to secure the base had utilised a single endoloop, this would amount to a saving of £842.58. Conclusion Our study set out to assess whether the complication rate differs in cases where one or two endoloops have been applied. Retrospective statistical analysis found no significant difference between groups. Based on these findings, we recommend use of one endoloop to secure the base in laparoscopic appendicectomy.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".