Irrigation Versus Suction Alone in Laparoscopic Appendectomy: Is Dilution the Solution to Pollution? A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
OBJECTIVES: To investigate outcomes of peritoneal irrigation versus suction without irrigation in patients undergoing emergency laparoscopic appendectomy. METHODS: We performed a systematic review and conducted a search of electronic information sources to identify all randomized controlled trials (RCTs) and observational studies investigating outcomes of irrigation versus suction alone in patients undergoing emergency laparoscopic appendectomy. We used the Cochrane risk of bias tool and the Newcastle-Ottawa scale to assess the risk of bias of RCTs and observational studies, respectively. Random-effects models were applied to calculate pooled outcome data. RESULTS: We identified 3 RCTs and 2 retrospective observational studies, enrolling 2511 patients. Our results suggested that there was no difference between peritoneal irrigation and suction alone in terms of intraabdominal abscess rate (odds ratio = 2.39, 95% confidence interval [CI] = 0.49-11.74, P = .28), wound infection (risk difference = 0.00, 95% CI = -0.04 to 0.05, P = .85), and length of stay (mean difference = -1.02, 95% CI = -3.10 to 1.07, P = .34); however, peritoneal irrigation was associated with longer operative time (mean difference = 7.12, 95% CI = 4.33 to 9.92, P < .00001). Our results remained consistent when randomized trials, adult patients, and pediatric patients were analyzed separately. CONCLUSIONS: The best available evidence suggests that the peritoneal irrigation with normal saline during laparoscopic appendectomy does not provide additional benefits compared with suction alone in terms of intraabdominal abscess, wound infection, and length of stay but it may prolong the operative time. The quality of the best available evidence is moderate; therefore, high-quality RCTs, which are adequately powered, are required to provide more robust basis for definite conclusions.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".