Single-incision Appendectomy is Comparable to Conventional Laparoscopic Appendectomy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.010 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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 it