Prophylactic therapies for the prevention of cholangitis in pediatric patients undergoing kasai procedure: a systematic review
Bibliographic record
Abstract
Introduction: Cholangitis is a frequent and severe complication following Kasai portoenterostomy in children with biliary atresia, significantly impacting native liver survival. Although prophylactic strategies such as antibiotics have been widely employed, their effectiveness remains inconclusive. Methods: A systematic review was conducted in accordance with PRISMA 2020 guidelines. Comprehensive literature searches were performed in PubMed, Cochrane Library, Scopus, and Web of Science up to June 2025. Eligible studies included randomized controlled trials and observational cohorts evaluating prophylactic interventions to prevent cholangitis post-Kasai in pediatric patients. Data extraction focused on study characteristics, interventions, outcomes, and methodological quality assessed using RoB 2 and the Newcastle-Ottawa Scale. Results: Six primary studies involving 454 patients were included. One randomized controlled trial demonstrated that oral TMP-SMX or neomycin for six months postoperatively significantly reduced cholangitis recurrence compared to historical controls. Another study showed early intravenous antibiotics followed by oral TMP-SMX reduced cholangitis incidence. However, three retrospective cohorts found no significant benefit of antibiotic prophylaxis in reducing infection rates or improving transplant-free survival. One study evaluating Roux-en-Y limb length suggested that surgical configuration may influence cholangitis risk. Methodological quality ranged from low to high, with heterogeneity in interventions and follow-up duration. Conclusion: Oral prophylactic antibiotics, particularly TMP-SMX, may offer benefit in reducing postoperative cholangitis following the Kasai procedure. Nonetheless, current evidence remains inconsistent. Standardized multicenter trials are warranted to establish optimal preventive strategies.
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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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".