Radiofrequency ablation of malignant hepatic neoplasms.
Bibliographic record
Abstract
OBJECTIVE: To assess the safety and efficacy of radiofrequency ablation (RFA) in the treatment of malignant neoplasms of the liver. METHODS: Sixty-seven patients received RFA for primary or secondary hepatic malignancies. Patients were followed prospectively with computed tomography (CT) scanning to assess for therapeutic response, disease progression and complications. RESULTS: Eighty-eight lesions were treated, including 57 hepatocellular carcinomas, 28 metastases, 2 cholangiocarcinomas and 1 hepatic plasmacytoma. Mean tumour size was 2.7 cm (range 0.5-6.9 cm). A total of 101 ablations were performed (66 percutaneously, 35 intraoperatively). Over a mean follow-up period of 142 days, results were available for 85 lesions. Local tumour control was achieved for 61 (72%) lesions, but new distant lesions developed in 6 of these cases. Residual disease was present in 20 (23%) lesions, and 4 (5%) lesions developed local recurrence. There were 10 complications, including 1 death in a patient who developed a liver abscess and subsequently died from hepatic failure. CONCLUSIONS: RFA is safe and effective in the treatment of hepatic malignancies. Local tumour control can be achieved in most cases; however, careful surveillance is important for detecting recurrent disease, as well as new lesions distant from the treated site.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".