Perioperative Complications and Outcome of Laparoscopic Cholecystectomy in 20 Dogs
Bibliographic record
Abstract
OBJECTIVE: To report the complications and outcome of dogs undergoing laparoscopic cholecystectomy for uncomplicated gall bladder disease. STUDY DESIGN: Multi-institutional case series. ANIMALS: Client-owned dogs (n=20). METHODS: Medical records of dogs that underwent laparoscopic cholecystectomy were reviewed and signalment, history, clinical and ultrasound examination findings, surgical variables, and complications were collated. Laparoscopic cholecystectomy was performed using a multiport approach. Data were compared between dogs with successful laparoscopic cholecystectomy and dogs requiring conversion to open cholecystectomy. RESULTS: Six dogs (30%) required conversion from laparoscopic to open cholecystectomy due to inability to ligate the cystic duct (3), evidence of gall bladder rupture (1), leakage from the cystic duct during dissection (1), and cardiac arrest (1). Cystic duct dissection was performed in 19 dogs using an articulating dissector (10), right angle forceps (7), and unrecorded (2). The cystic duct was ligated in 15 dogs using surgical clips (5), suture (6), or a combination (4). All dogs were discharged from the hospital and had resolution of clinical signs, although 1 dog developed pancreatitis and 1 dog required revision surgery for bile peritonitis. There was no significant difference in preoperative blood analysis results, surgical technique, or duration of hospitalization between dogs undergoing laparoscopic cholecystectomy and cases converted to open cholecystectomy. CONCLUSION: Laparoscopic cholecystectomy can be performed successfully for uncomplicated gall bladder disease in dogs after careful case selection. The surgeon considering laparoscopic cholecystectomy should be familiar with a variety of methods for cystic duct dissection and ligation to avoid difficulties during the procedure.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".