Is endoscopic retrograde appendicitis therapy a better modality for acute uncomplicated appendicitis? A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Previous studies had shown endoscopic retrograde appendicitis therapy (ERAT) is an effective treatment for acute appendicitis. However, different studies reported conflicting outcomes regarding the effectiveness of ERAT in comparison with laparoscopic appendectomy (LA). AIM: To compare the effectiveness of ERAT with LA. METHODS: Randomized controlled trials (RCTs) and retrospective studies of ERAT for acute uncomplicated appendicitis were searched in PubMed, Cochrane Library, Web of Science, Embase database, China National Knowledge Infrastructure (CNKI), the WanFang Database, and Chinese Scientific Journals Database (VIP) from the establishment date to March 1 2021. Heterogeneity was assessed using the I-squared statistic. Pooled odds ratios (OR), weighted mean difference (WMD), and standard mean difference (SMD), with 95% confidence intervals (CI) were calculated through either fixed-effects or random-effects model. Sensitivity analysis was also performed. Publication bias was tested by Egger's test, and Begg's test. The quality of included RCT were evaluated by the Jadad scale, while Newcastle-Ottawa scale is adopted for assessing the methodological quality of case-control studies. All statistical analysis was performed using Stata 15.1 statistical software. All statistical analysis was performed using Stata 15.1 statistical software. This study is registered with PROSPERO, CRD42021243955. RESULTS: = 0.020]. Moreover, the quality of 10 RCTs were low with 0-3 Jadad scores, while the methodological quality of two case-control studies were fair with a score of 2 (each). CONCLUSION: Compared with LA, ERAT reduces operation time, the level of postoperative inflammation, and results in fewer complications and shorter recovery time, with preserving the appendix and its immune and biological functions.
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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 | 0.018 | 0.045 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.039 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".