Unravelling the Complexity Myth for Minimally Invasive Right Hepatectomy: Liver Parenchymal Features and their Correlation to Objective Outcomes in Major Anatomical Resections
Bibliographic record
Abstract
BACKGROUND: Minimally invasive approaches to major liver resection have been limited by presumed difficulty of the operation. While some concerns arise from mastering the techniques, factors such as tumor size and liver parenchymal features have anecdotally been described as surrogates for operative difficulty. These factors have not been systematically studied for minimally invasive right hepatectomy (MIRH). METHODS: Seventy-five patients who underwent MIRH during 2007-2016 by the senior author were evaluated; these were compared to control group of open right hepatectomy. Demographics, operative, and post-operative variables were collected. Operative times and estimated blood loss, two objective parameters of operative difficulty were correlated to volume of hepatic resection, parenchymal transection diameter and liver parenchymal features using regression analysis. RESULTS: Thirty-eight (50.6%) resections were performed for malignant indications. Average tumor size was 5.7 cm (±3.6), mean operative time was 196 min (±74), and mean EBL was 220 mL (±170). Average transection diameter was 10.1 cm (±1.7). There was no correlation between operative difficulty with parenchymal transection diameter or presence of steatosis. Blood loss was higher with increased right hepatic lobe volume and body mass index. CONCLUSIONS: This analysis of a very defined anatomical resection suggests that the often quoted radiographic and pathologic features indicative of a challenging procedure were not significant in determining operative difficulty.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".