Gabexate in the prophylaxis of post-ERCP pancreatitis: a meta-analysis of randomized controlled trials
Bibliographic record
Abstract
BACKGROUND: Acute pancreatitis is a common complication of endoscopic retrograde cholangiopancreatography and the benefit of its pharmacological treatment is unclear. Although prophylactic use of gabexate for the reduction of pancreatic injury after ERCP has been evaluated, the discrepancy about gabexate's beneficial effect on pancreatic injury still exists. This study aimed to evaluate the effectiveness and safety of gabexate in the prophylaxis of post-endoscopic retrograde cholangiopancreatography pancreatitis (PEP). METHODS: We employed the method recommended by the Cochrane Collaboration to perform a meta-analysis of randomized controlled trials (RCTs) of gabexate in the prevention of post-ERCP pancreatitis (PEP) including three RCTs conducted in Italy and one in China. RESULTS: All of the four RCTs were of high quality. When the RCTs were analyzed, odds ratios (OR) for gabexate mesilate were 0.67 [95% CI (0.31 to approximately 1.47), p = 0.32] for PEP, 3.78 [95% CI (0.62 to approximately 22.98), p = 0.15] for severe PEP, 0.68 [95% CI (0.19 to approximately 2.43), p = 0.56] for the case-fatality of PEP, 0.88 [95% CI (0.72 to approximately 1.07), p = 0.20] for post-ERCP hyperamylasemia, 0.69 [95% CI (0.39 to approximately 1.21), p = 0.19] for post-ERCP abdominal pain, thus indicating no beneficial effects of gabexate on acute pancreatitis, the death rate of PEP, hyperamylasemia and abdominal pain. No evidence of publication bias was found. CONCLUSION: Gabexate mesilate can not prevent the pancreatic injury after ERCP. It is not recommended for the use of gabexate mesilate in the prophylaxis of PEP.
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.
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 | 0.020 | 0.042 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.042 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| 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".