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Record W3048915567 · doi:10.1016/j.jimed.2020.06.002

Optimized nerve block techniques while performing percutaneous hepatic ablation: Literature review and practical use

2020· review· en· W3048915567 on OpenAlexaffabout
David Liu, Anastasia Hadjivassiliou, David Valenti, SG Ho, Darren Klass, JB Chung, PT Kim, L.J. Boucher

Bibliographic record

VenueJournal of interventional medicine · 2020
Typereview
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsMcGill University Health CentreVancouver General HospitalUniversity of British Columbia
Fundersnot available
KeywordsMedicineSedationAblationPercutaneousCryoablationAblation zoneRadiofrequency ablationMicrowave ablationAnesthesiaAirwaySurgeryGeneral anaesthesiaInternal medicine

Abstract

fetched live from OpenAlex

Percutaneous image guided thermal ablation has become a cornerstone of therapy for patients with oligometastatic disease and primary liver malignancies. Evolving from percutaneous ethanol injection (PEI), thermal ablation utilizing radiofrequency ablation (RFA) and microwave ablation (MWA) have become the standard approach in the treatment of isolated lesions that fit within the size criteria for curative intent therapy (typically 3-4cm). With the evolution of more intense thermal ablation, such as MWA, the dramatic increase in both the size of ablation zone and intensity of heat generation have extended the limits of this technique. As a result of these innovations, intra-procedural and post-procedural pain have also significantly increased, requiring either higher levels of intravenous sedation or, in some institutions, general anesthesia. In addition to the increase in therapeutic intensity, the use of intravenous sedation during aggressive ablation procedures carries the risk of over-sedation when the noxious insult (i.e. the ablation) is removed, adding further difficulty to post-procedural recovery and management. Furthermore, high subdiaphragmatic lesions become challenging in this setting due to issues relating to sedation and compliance with breath hold/breathing instructions. Although general anesthesia may mitigate these complications, the added resources associated with providing general anesthesia during ablation is not cost effective and may result in substantial delays in treatment. The reduction of Aerosol Generating Medical Procedures (AGMP), such as intubation due to the COVID-19 Pandemic, must also be taken into consideration. Due to the potential increased risk of infection transmission, alternatives to general anesthesia should be considered when safe and possible. Upper abdominal regional nerve block techniques have been used to manage pain related to trauma, surgery, and cancer; however, blocks of this nature are not well described in the interventional radiology literature. The McGill University group has developed experience in using such blocks as splanchnic, celiac and hepatic hilar nerve blocks to provide peri-procedural pain control [1]. Since incorporating these techniques (along with hydrodissection with tumescent anesthesia), we have also observed in our high volume ablation center a dramatic decrease in the amount of sedatives administered during the procedure, a decrease in patient discomfort during localization and ablation, as well as decreased pain post-procedure. Faster time to discharge and overall reduction in room procedural time serve as added benefits. The purpose of this publication is to outline and illustrate the practical application and use of nerve block/regional anesthesia techniques with respect to percutaneous hepatic thermal ablation.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.005
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.060
GPT teacher head0.377
Teacher spread0.317 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations8
Published2020
Admission routes2
Has abstractyes

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