Meta-analysis: rectal indomethacin for the prevention of post-ERCP pancreatitis
Bibliographic record
Abstract
BACKGROUND: Despite initial evidence in the literature, nonsteroidal anti-inflammatory drugs (NSAIDs) have not been widely used to prevent post-endoscopic retrograde cholangiopancreatography (ERCP) pancreatitis (PEP). AIM: To complete a meta-analysis of high-quality RCTs that included the latest available literature published after past meta-analytical efforts METHODS: A comprehensive electronic literature search was carried out for RCTs comparing peri-procedural rectal indomethacin and placebo in preventing PEP. Methodological quality was assessed by the Cochrane risk of bias tool. Fixed model Mantel-Haenszel meta-analysis, Q test and I(2) index were used. Several subgroup and sensitivity analyses were planned. RESULTS: A total of four of 61 retrieved trials between 2007 and 2012 (n = 1470) were included. No significant publication bias existed. All studies used similar criteria to detect pancreatitis. The pooled proportion estimate of the rate of pancreatitis was 5.1% with indomethacin and 10.3% with placebo. After excluding the high-risk patients, the rates were 3.9% and 7.9% respectively. Fixed model meta-analysis showed that the rate of pancreatitis was significantly lower using indomethacin as compared with placebo [OR = 0.49(0.34-0.71); P = 0.0002]. Number needed to treat was 20. There was no significant statistical or clinical heterogeneity. In subgroup analysis, the difference remained unchanged for average-risk population [OR = 0.49(0.28-0.85); P = 0.01] or in preventing severe PEP [OR = 0.41(0.21-0.78); P = 0.007]. The result of the main outcome remained robust in multiple sensitivity analyses. CONCLUSIONS: Rectal indomethacin used immediately before or after ERCP significantly reduces the risk of PEP to half in both low- and high-risk patients, and with both statistically and clinically significant conclusions. These results suggest that a possible change in routine practice for patients at both low and high risk of developing PEP should be advocated.
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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 | 0.013 | 0.027 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.052 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".