Procedure-related risk factors for bleeding after percutaneous transhepatic biliary drainage: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND/PURPOSE: Bleeding is the most dreaded complication after percutaneous transhepatic biliary drainage (PTBD). Clarifying the risk factors of bleeding can reduce the morbidity and mortality rates of PTBD. However, the procedure-related risk factors for bleeding after PTBD are still controversial. Therefore, this systematic review and meta-analysis were performed to identify procedure-related risk factors of bleeding after PTBD. METHODS: PubMed, Cochrane database, and Google Scholar were searched for published studies until 1st May 2021. Inclusion criteria were: studies associated with bleeding complications after PTBD and with sufficient data to compare different procedure-related factors for bleeding. Sources of bias were assessed using the Newcastle-Ottawa Scale and Cochrane risk-of-bias tool for randomised trials. Probable procedure-related risk factors were evaluated and outcomes were expressed in the case of dichotomous variables, as an odds ratio (OR) (with a 95% confidence interval, (CI)). RESULTS: Eleven studies were included in the meta-analysis. There was no significant difference in bleeding rates with respect to the side of PTBD (left/right, OR = 1.10, 95% CI: 0.68-1.76), the insertion level of bile duct (central/peripheral, OR = 1.39, 95% CI: 0.82-2.35), and the usage of ultrasound guidance (OR: 1.25, 95% CI: 0.60-2.60). A subgroup analysis revealed a left-sided approach that resulted in more hepatic arterial injuries than the right-sided approach (left/right, OR = 1.93, 95% CI: 1.32-2.83). CONCLUSION: Left-sided approach is a risk factor for hepatic arterial injuries after PTBD.
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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 | 0.011 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.041 |
| 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 | 0.003 | 0.002 |
| 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".