Harmonizing Definitions and Perspectives in Extreme Liver Surgery
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to propose to our community a common language about extreme liver surgery. BACKGROUND: The lack of a clear definition of extreme liver surgery prevents convincing comparisons of results among centers. METHODS: We used a 2-round Delphi methodology to quantify consensus among liver surgery experts. For inclusion in the final recommendations, we established a consensus when the positive responses (agree and totally agree) exceeded 70%. The study steering group summarized and reported the recommendations. In general, a 5-point Likert scale with a neutral central value was used, and in a few cases multiple choices. Results are displayed as numbers and percentages. RESULTS: A 2-round Delphi study was completed by 38 expert surgeons in complex hepatobiliary surgery. The surgeon´s median age was 58 years old (52-63) and the median years of experience was 25 years (20-31). For the proposed definitions of total vascular occlusion, hepatic flow occlusion and inferior vein occlusion, the degree of agreement was 97%, 81%, and 84%, respectively. In situ approach (64%) was the preferred, followed by ante situ (22%) and ex situ (14%). Autologous or cadaveric graft for hepatic artery or hepatic vein repair were the most recommended (89%). The use of veno-venous bypass or portocaval shunt revealed the divergence depending on the case. Overall, 75% of the experts agreed with the proposed definition for extreme liver surgery. CONCLUSIONS: Obtaining a consensus on the definition of extreme liver surgery is essential to guarantee the correct management of patients with highly complex hepatobiliary oncological disease. The management of candidates for extreme liver surgery involves comprehensive care ranging from adequate patient selection to the appropriate surgical strategy.
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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 | 0.202 | 0.144 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.005 | 0.025 |
| Scholarly communication | 0.012 | 0.016 |
| Open science | 0.005 | 0.022 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".