Continuous vs. interrupted suturing in hepaticojejunostomy: a comprehensive systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Hepaticojejunostomy (HJ) is a crucial reconstructive step in upper gastrointestinal (UGI), pancreaticoduodenectomy (PD), and Hepaticobiliarypancreatic (HBP) surgeries. The optimal suturing technique remains debated, with conflicting evidence regarding operative efficiency, costs, and complications. This meta-analysis compares continuous and interrupted suturing to provide evidence-based recommendations. METHODS: A systematic review and meta-analysis were conducted using PubMed, Embase, and Cochrane Library. Primary outcomes were anastomotic time and costs, while secondary outcomes included bile leakage, anastomotic stricture, morbidity, cholangitis, hospital stay, and re-exploration rates. A random or fixed-effects model was applied based on heterogeneity. We included randomized controlled trials and non-randomized cohort studies. The risk of bias was assessed using the Cochrane ROB 2 tool, Newcastle-Ottawa Scale (NOS), and MINORS instrument as appropriate. Additionally, the quality of evidence for each outcome was evaluated using the GRADE approach. Sensitivity analyses were performed using the leave-one-out method. RESULTS: Seven studies (1,159 patients) were included (continuous: 388, interrupted: 771). Continuous suturing significantly reduced anastomotic time (MD = -13.06 min, 95% CI: -17.37 to -8.75, P < 0.001) and costs (SMD = -4.89, 95% CI: -6.10 to -3.67, P < 0.001). However, no significant differences were observed in bile leakage, anastomotic stricture, morbidity, cholangitis, hospital stay, or re-exploration rates (P > 0.05). Sensitivity analyses confirmed these findings. CONCLUSION: Continuous suturing reduces anastomotic time by ~ 13 min and costs by ~ $90 without increasing complications. While these differences may be statistically significant, their clinical relevance can vary depending on the surgical context. Surgical choice should consider surgeon expertise, institutional protocols, and patient factors. Further randomized controlled trials are necessary to validate these findings.
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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 | 0.012 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.042 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 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".