Laparoscopic versus open liver resection for intrahepatic cholangiocarcinoma: a systematic review of propensity score-matched studies
Bibliographic record
Abstract
Outcomes of laparoscopic liver resection (LLR) versus open LR (OLR) for intrahepatic cholangiocarcinoma (ICCA) are heterogeneous. We aimed to compare LLR and OLR for ICCA based on propensity-score-matched (PSM) studies. Two reviewers independently searched the online databases (PubMed, Embase, and Cochrane Library) for PSM studies that compared LLR and OLR for ICCA. The Ottawa-Newcastle Quality Assessment Scale with a cutoff of ≥ 7 was used to define higher-quality literature. Only 'high-quality' PSM analyses of the English language that met all our inclusion criteria were considered. A total of ten PSM trials were included in the analyses. Compared with OLR, although the lymph node dissection (LND) (RR = 0.67) and major hepatectomy rates were lower in the LLR group (RR = 0.87), higher R0 resections (RR = 1.05) and lower major complications (Clavien-Dindo grade ≥ III) (RR = 0.72) were also observed in the LLR group. In addition, patients in the LLR group showed less estimated blood loss (MD = - 185.52 ml) and shorter hospital stays as well (MD = - 2.75 days). Further analysis found the overall survival (OS) (HR = 0.91), disease-free survival (DFS) (HR = 0.95), and recurrence-free survival (HR = 0.80) for patients with ICCA after LLR were all comparable to those of OLR. LLR for selected ICCA patients may be technically safe and feasible, providing short-term benefits and achieving oncological efficacy without compromising the long-term survival of the patients.
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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 | 0.013 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.010 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".