The Incidence of Endoscopic Retrograde Cholangiopancreatography-Related Complications in Patients With Liver Transplant: A Meta-Analysis and Systematic Review
Bibliographic record
Abstract
Background: Existing literature on post-endoscopic retrograde cholangiopancreatography (ERCP) complications in patients with liver transplant remains scarce and largely inconsistent. We therefore aimed to systematically review and analyze the literature on complication rates associated with ERCP in patients with liver transplant. Methods: We performed a comprehensive literature search in PubMed, PubMed Central, Embase, and ScienceDirect databases from inception through March 2020 to identify all the studies that evaluated post-ERCP complications in patients with liver transplant. Effect estimates from the individual studies were extracted and combined using the random effect, generic inverse variance method of DerSimonian and Laird, and a pooled odds ratio (OR) and event rates were calculated. Forest plots were generated, and publication bias was assessed for using conventional techniques. Results: Fourteen studies with a total of 1,787 patients were analyzed. In total, 3,192 ERCPs were performed on these patients. The pooled all-complication rate was 5.2% (95% confidence interval (CI): 0.035 - 0.075). Procedural complications analyzed included post-ERCP pancreatitis 3.4% (95% CI: 0.025 - 0.047), bleeding 1.1% (95% CI: 0.006 - 0.020), infections 0.2% (95% CI: 0.025 - 0.047), and cholangitis 0.8% (95% CI: 0.004 - 0.020). No cases of periprocedural death were reported. The pooled OR for post-ERCP pancreatitis in patients with liver transplant compared to patients without liver transplant was 1.289 (95% CI: 0.455 - 3.653, P = 0.633, I 2 = 72.88%). Conclusion: Post-ERCP complication rates in liver transplant patients are comparable to the general population and hence, peri-procedural evaluation and management may follow the current standards of care in this patient population. Gastroenterol Res. 2021;14(5):259-267 doi: https://doi.org/10.14740/gr1391
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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 | 0.014 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.038 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".