Meta-analysis of prophylactic corticosteroid use in post-ERCP pancreatitis
Bibliographic record
Abstract
BACKGROUND: Acute pancreatitis is a common complication of endoscopic retrograde cholangiopancreatography and benefit of pharmacological treatment is unclear. Although prophylactic use of corticosteroid for reduction of pancreatic injury after ERCP has been evaluated, discrepancy about beneficial effect of corticosteroid on pancreatic injury still exists. The aim of current study is to evaluate effectiveness and safety of corticosteroid in prophylaxis of post-endoscopic retrograde cholangiopancreatography pancreatitis (PEP). METHODS: We employed the method recommended by the Cochrane Collaboration to perform a meta-analysis of seven randomized controlled trials (RCTs) of corticosteroid in prevention of post-ERCP pancreatitis (PEP) around the world. RESULTS: Most of the seven RCTs were of high quality. When the RCTs were analyzed, odds ratios (OR) for corticosteroid were 1.13 [95% CI (0.89~1.44), p = 0.32] for PEP, 1.61 [95% CI (0.74~3.52), p = 0.23] for severe PEP, 0.92 [95% CI (0.57~1.48), p = 0.73] for post-ERCP hyperamylasemia respectively. The results indicated that there were no beneficial effects of corticosteroid on acute pancreatitis and hyperamylasemia. No evidence of publication bias was found. CONCLUSION: Corticosteroids cannot prevent pancreatic injury after ERCP. Therefore, their use in the prophylaxis of PEP is not recommended.
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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 | 0.021 | 0.047 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.045 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".