Recurrence of idiopathic acute pancreatitis after cholecystectomy: systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Occult biliary disease has been suggested as a frequent underlying cause of idiopathic acute pancreatitis (IAP). Cholecystectomy has been proposed as a strategy to prevent recurrent IAP. The aim of this systematic review was to determine the efficacy of cholecystectomy in reducing the risk of recurrent IAP. METHODS: PubMed, Embase and Cochrane Library databases were searched systematically for studies including patients with IAP treated by cholecystectomy, with data on recurrence of pancreatitis. Studies published before 1980 or including chronic pancreatitis and case reports were excluded. The primary outcome was recurrence rate. Quality was assessed using the Newcastle-Ottawa Scale. Meta-analyses were undertaken to calculate risk ratios using a random-effects model with the inverse-variance method. RESULTS: Overall, ten studies were included, of which nine were used in pooled analyses. The study population consisted of 524 patients with 126 cholecystectomies. Of these 524 patients, 154 (29·4 (95 per cent c.i. 25·5 to 33·3) per cent) had recurrent disease. The recurrence rate was significantly lower after cholecystectomy than after conservative management (14 of 126 (11·1 per cent) versus 140 of 398 (35·2 per cent); risk ratio 0·44, 95 per cent c.i. 0·27 to 0·71). Even in patients in whom IAP was diagnosed after more extensive diagnostic testing, including endoscopic ultrasonography or magnetic resonance cholangiopancreatography, the recurrence rate appeared to be lower after cholecystectomy (4 of 36 (11 per cent) versus 42 of 108 (38·9 per cent); risk ratio 0·41, 0·16 to 1·07). CONCLUSION: Cholecystectomy after an episode of IAP reduces the risk of recurrent pancreatitis. This implies that current diagnostics are insufficient to exclude a biliary cause.
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 | 0.012 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.035 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".