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Record W2773677636 · doi:10.4103/eus.eus_97_17

Practice guidelines for endoscopic ultrasound-guided celiac plexus neurolysis

2017· article· en· W2773677636 on OpenAlexaff
Siyu Sun, AnandV Sahai, JonathanM Wyse, Robert Battat, Adrian Săftoiu, AliA Siddiqui, AngTiing Leong, BrendaLucia Arturo Arias, Carlo Fabbri, DouglasG Adler, Erwin Santo, Evangelos Kalaitzakis, Everson L. Artifon, Girish Mishra, HusseinHassan Okasha, Jan‐Werner Poley, Jintao Guo, Juan J. Vila, L Lee, Malay Sharma, ManoopS Bhutani, Marc Giovannini, Masayuki Kitano, MohamadAli Eloubeidi, M Khashab, NamQ Nguyen, Payal Saxena, Peter Vilmann, Pietro Fusaroli, Pramod Kumar Garg, Sammy Ho, Shuntaro Mukai, Silvia Carrara, Subbaramiah Sridhar, Sundeep Lakhtakia, SurinderS Rana, Vinay Dhir

Bibliographic record

VenueEndoscopic Ultrasound · 2017
Typearticle
Languageen
FieldMedicine
TopicPain Management and Opioid Use
Canadian institutionsCentre Hospitalier de l’Université de MontréalMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsMedicineEndoscopic ultrasoundGeneral surgeryMedical physicsRadiology

Abstract

fetched live from OpenAlex

OBJECTIVES: The objective of guideline was to provide clear and relevant consensus statements to form a practical guideline for clinicians on the indications, optimal technique, safety and efficacy of endoscopic ultrasound guided celiac plexus neurolysis (EUS-CPN). METHODS: Six important clinical questions were determined regarding EUS-CPN. Following a detailed literature review, 6 statements were proposed attempting to answer those questions. A group of expert endosonographers convened in Chicago, United States (May 2016), where the statements were presented and feedback provided. Subsequently a consensus group of 35 expert endosonographers voted based on their individual level of agreement. A strong recommendation required 80% voter agreement. The modified GRADE (Grading of Recommendations Assessment, Development, and Evaluation) criteria were used to rate the strength of recommendations and the quality of evidence. RESULTS: Eighty percent agreement was reached on 5 of 6 consensus statements, 79.4% agreement was reached on the remaining one. CONCLUSIONS: EUS-CPN is efficacious, should be integrated into the management of pancreas cancer pain, and can be considered early at the time of diagnosis of inoperable disease. Techniques may still vary based on operator experience. Serious complications exist, but are rare.

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)0.035
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.256
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.035
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.077
GPT teacher head0.388
Teacher spread0.311 · 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.

Study designNot applicable
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

Citations46
Published2017
Admission routes1
Has abstractyes

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