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Record W2096419987 · doi:10.4021/gr490w

Laparoscopic Radiofrequency Thermal Ablation of Hepatocellular Carcinoma in Liver Cirrhosis Patients

2012· article· en· W2096419987 on OpenAlexvenueno aff
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Bibliographic record

VenueGastroenterology Research · 2012
Typearticle
Languageen
FieldMedicine
TopicHepatocellular Carcinoma Treatment and Prognosis
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHepatocellular carcinomaCirrhosisPercutaneousRadiofrequency ablationHepatologyRadiologyUltrasoundAblationSpiral computed tomographyComplicationComputed tomographySurgeryInternal medicine

Abstract

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BACKGROUND: Laparoscopic radiofrequency ablation (LRFA) for hepatocellular carcinoma (HCC) under guidance of intra-operative laparoscopic ultrasound (IOLUS) aiming of obtaining additional information for liver situation, better tumor staging and effective treatment of hepatic focal lesion (HFL) in patients with a difficult percutaneous approach. METHODS: Between September 2010 and July 2012, 301 patients with HCC in liver cirrhosis were referred from HCC clinic at National Hepatology and Tropical Medicine Research Institute (NHTMRI). Twenty nine patients were submitted to LRFA with IOLUS guidance. Operation time, hospital stay, post procedure complication were recorded. Spiral CT scan one month postoperative was mandatory during follow up. RESULTS: LRFA was completed in all patients. The IOLUS examination identified new HFL in three patients. A total of 32 lesions were treated. The mean operative time was 120 minutes; eight procedures were associated in six patients: cholecystectomy (6) and adhesiolysis (2). A complete tumor ablation was observed in all patients which were documented via spiral computed tomography (CT scan) one month after treatment. CONCLUSION: LRFA of HCC proved to be a safe and effective technique. IOLUS is superior on spiral CT scan in detection a small HCC.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.602

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.096
GPT teacher head0.307
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2012
Admission routes1
Has abstractyes

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