Management of Bile Duct Injury: Experience of 37 Cases
Bibliographic record
Abstract
Background: Bile duct injury (BDI) is one of the most serious complications during Gall bladder surgery, particularly in cholecystectomy, and is associated with significant morbidity, prolonged hospitalization, and the need for complex reconstructive procedures. Early diagnosis and appropriate management are essential for achieving favorable outcomes. This study aims to evaluate the clinical presentation, pattern of injury, management strategies, and postoperative outcomes of patients with bile duct injury treated at our tertiary care center. Methods: This retrospective observational descriptive study included all patients with iatrogenic bile duct injury managed at our center during the study period. Demographic characteristics, cause and timing of injury, clinical presentation, Strasberg classification, management modalities, and postoperative outcomes were reviewed from hospital records. Data were analyzed using descriptive statistics and expressed as mean ± standard deviation or frequency and percentage. Results: The most common presenting features were abdominal pain/peritonitis (62.2%), fever (59.5%), and bile leakage (56.8%). Strasberg type E3 was the most frequent injury (18.9%). Roux-en-Y hepaticojejunostomy was the commonest definitive treatment (64.9%), followed by ERCP with biliary stenting (51.4%), primary repair (40.5%), and percutaneous drainage (32.4%), with some patients requiring staged interventions. Wound infection was the most common postoperative complication (45.9%), while anastomotic stricture occurred in 8.1% and reintervention was required in 5.4% of patients. The overall mortality rate was 2.7%. Conclusion: Bile duct injury remains a challenging surgical complication, occurring predominantly after laparoscopic cholecystectomy. Early recognition, accurate classification, and management in specialized hepatobiliary centers using a multidisciplinary approach can achieve satisfactory outcomes.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".