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Record W4411711249 · doi:10.20935/acadonco7777

Irreversible electroporation for unresectable liver malignancies

2025· article· en· W4411711249 on OpenAlexaff
Zili Zhou, Christopher J Wall, Jeff Bird, Shahid Ahmed, Gavin Beck, John M. Shaw, Mike Moser

Bibliographic record

VenueAcademia oncology. · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Inactivation Methods
Canadian institutionsSaskatchewan Health AuthoritySaskatchewan HealthUniversity of Saskatchewan
Fundersnot available
KeywordsElectroporationMedicineGeneral surgeryCancer researchInternal medicineChemistryBiochemistry

Abstract

fetched live from OpenAlex

Background: Irreversible electroporation (IRE) is a non-thermal ablation technique used for liver tumors that are unresectable due to their proximity to critical structures. This study evaluates outcomes for patients treated with IRE. Methods: We reviewed 19 patients who underwent 22 IRE procedures between July 2015 and February 2024. Tumors were deemed unresectable by a multidisciplinary tumor board because of abutment to hepatic veins or Inferior vena cava (IVC) (n = 10), recurrence near the hilum post-lobectomy (n = 4), portal vein bifurcation involvement (n = 3), or cirrhosis (n = 3). A percutaneous approach was used in 19 of 22 procedures. Results: The median overall survival was 36.8 months (95% CI 28.9, NR). For patients with colorectal liver metastases, median survival was 49 months (46.7, NR). Local recurrence occurred in 7 of 22 cases (32%), with a median recurrence-free survival of 27 months. Complications were rare, with 16/19 (84%) having no 90-day post-procedure complications. Discussion: Our results support IRE as a safe and effective option for managing unresectable liver tumors near critical structures. These outcomes, achieved at a medium-sized center, highlight its feasibility and patient benefits in anatomically challenging cases.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.290
Threshold uncertainty score0.565

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.022
GPT teacher head0.363
Teacher spread0.341 · 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 designBench or experimental
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

Citations0
Published2025
Admission routes1
Has abstractyes

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