Laparoscopic Compared to Open Repeat Hepatectomy for Colorectal Liver Metastases: a Multi‐institutional Propensity‐Matched Analysis of Short‐ and Long‐Term Outcomes
Bibliographic record
Abstract
INTRODUCTION: While uptake of laparoscopic hepatectomy has improved, evidence on laparoscopic re-hepatectomy (LRH) for colorectal liver metastases (CRLMs) is limited and has never been compared to the open approach. We sought to define outcomes of LRH compared to open re-hepatectomy (ORH). METHODS: Patients undergoing re-hepatectomy for CRLM at 39 institutions (2006-2013) were identified. Primary outcomes were 30-day post-operative overall morbidity, mortality, and length of stay. Secondary outcomes were recurrence and survival at latest follow-up. LRHs were matched to ORHs (1:3) using a propensity score created by comparing pre-operative clinicopathologic factors (number and size of liver metastases and major hepatectomy). RESULTS: Of 376 re-hepatectomies included, 27 were LRH, including 1 (3.7%) conversion. The propensity-matched cohort included 108 patients. Neither median operative time (252 vs. 230 min; p = 0.82) nor overall 30-day morbidity (48.1 vs. 38.3%; p = 0.37) differed. Non-specific morbidity (including cardiac, respiratory, infectious, and renal events) decreased with LRH (11.1 vs. 30.9%, p = 0.04), while surgical-specific morbidity, including liver insufficiency, was higher (44.4 vs. 22.2%, p = 0.03). One ORH and 0 LRH suffered 30-day mortality. Median length of stay (9 vs. 12 days; p = 0.60) was comparable. At latest follow-up, 26 (96.3%) LRH and 67 (82.7%) ORH patients were alive. Eight (29.6%) LRH and 36 (44.4%) ORH patients were alive without disease. CONCLUSION: LRH for recurrent CRLM was associated with overall short-term outcomes comparable to ORH, but different morbidity profiles. While it may offer a safe and feasible approach, further insight is necessary to better define patient selection.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".