Extended Right Hepatectomy following Clearance of the Left Liver Lobe and Portal Vein Embolization for Curatively Intended Treatment of Extensive Bilobar Colorectal Liver Metastases: A Single-Center Case Series
Bibliographic record
Abstract
Background: Two-staged hepatectomy (TSH) including portal vein embolization (PVE) may offer surgical treatment for extensive bilobar colorectal liver metastases (CRLM). This study aimed to investigate the feasibility and outcomes of extended right hepatectomy (ERH) within TSH including PVE for patients with extended CRLM. Methods: We retrospectively collected data of patients who underwent TSH for extended CRLM between 2015 and 2021 at our institution. Clearance of the left liver lobe (clear-up, CU) associated with PVE was followed by ERH. Results: Minimally invasive (n = 12, 46%, MIH) or open hepatectomy (n = 14, 54%, OH) was performed. Postoperative major morbidity and 90-day mortality were 54% and 0%. Three-year overall survival was 95%. Baseline characteristics, postoperative and long-term outcomes were comparable between MIH and OH. However, hospital stay was significantly shorter after MIH (8 vs. 15 days, p = 0.008). Additionally, the need for intraoperative transfusions tended to be lower in the MIH group (17% vs. 50%, p = 0.110). Conclusions: ERH following CU and PVE for extended CRLM is feasible and safe in laparoscopic and open approaches. MIH for ERH may result in shorter postoperative hospital stays. Further high-volume, multicenter studies are required to evaluate the potential superiority of MIH.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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 | 0.000 |
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".