Starting a new laparoscopic liver surgery program: initial experience and improved efficiency
Bibliographic record
Abstract
BACKGROUND: Owing to the anatomic complexity of the liver and the risk of hemorrhage, most liver resections are still performed using an open procedure. We evaluated the outcomes of introducing a laparoscopic liver program to a community teaching hospital. METHODS: We retrospectively reviewed laparoscopic liver resections performed between August 2010 and July 2013 at St. Joseph's Health Centre in Toronto. The primary outcomes were mortality, major morbidity and negative margins. Secondary outcomes included other perioperative outcomes. We used nonparametric tests to compare the outcomes during the first (group A) and second (group B) halves of the study period. RESULTS: Group A included 19 patients and group B had 25 patients; 9 and 4 patients, respectively, had major resections. Group A had the only death due to liver failure. There was no difference in major complications (10.6% v. 16%) or length of stay (4.5 v. 4.6 d) between the groups. One patient in group B had a positive margin. There was a significant decrease in duration of surgery (from 237 to 170 min, p = 0.007), with a trend toward shorter duration for major resections (from 318 to 238 min, p = 0.07). Furthermore, more procedures were performed for malignancy in group B than group A (36.8% v. 84.0%, p = 0.001). CONCLUSION: Laparoscopic liver resection can be safely introduced into a Canadian community teaching hospital. Average duration of surgery decreased by 67 minutes despite a 2-fold increase in the number of cases performed for malignancy.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".