Single-incision Appendectomy is Comparable to Conventional Laparoscopic Appendectomy
Bibliographic record
Abstract
PURPOSE: Acute appendicitis remains the common gastrointestinal emergency in adults. Single-incision laparoscopic appendectomy (SILA) has been proposed as the next evolution in minimally invasive surgery. SILA is postulated to reduce postoperative pain and enhance cosmesis, while effectively removing an inflamed appendix. However, the efficacy and benefits of SILA compared with conventional laparoscopic appendectomy (CLA) remain to be determined. Our objectives were to systematically review the literature comparing SILA with CLA for acute appendicitis and perform a pooled analysis on the efficacy of SILA. METHODS: Published English-language manuscripts were considered for review inclusion. A comprehensive search of electronic databases (eg, MEDLINE, EMBASE, SCOPUS, BIOSIS Previews, and the Cochrane Library) using broad search terms was completed. All comparative studies were included if they incorporated adult patients undergoing appendectomy for acute appendicitis by SILA. The primary outcomes of interest were operative time and length of hospital stay. RESULTS: From a total of 366 articles, 34 articles were identified. A total of 9 comparative studies were included for pooled analysis. There was no significant difference in operative time, length of stay, pain scores, and conversion or complication rates between SILA and CLA for acute appendicitis. CONCLUSIONS: This systematic review and pooled analysis demonstrates that SILA is comparable to CLA for acute appendicitis in adults. However, this review identifies the need for randomized controlled trials to clarify the efficacy of SILA compared with CLA.
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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 | 0.011 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.010 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".