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Record W3211351045 · doi:10.1093/pm/pnab281

Consensus practice guidelines on interventions for cervical spine (facet) joint pain from a multispecialty international working group

2021· article· en· W3211351045 on OpenAlexaff
Robert W. Hurley, Meredith C B Adams, Meredith Barad, Arun Bhaskar, Anuj Bhatia, Andrea L. Chadwick, Timothy R. Deer, Jennifer M. Hah, W. Michael Hooten, Narayan Kissoon, David Wonhee Lee, Zachary L. McCormick, Jee Youn Moon, Samer Narouze, David Provenzano, Byron J. Schneider, Maarten van Eerd, Jan Van Zundert, Mark S. Wallace, Sara M Wilson, Zirong Zhao, Steven P. Cohen

Bibliographic record

VenuePain Medicine · 2021
Typearticle
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsToronto Western HospitalUniversity of TorontoUniversity Health Network
FundersNational Institute of Biomedical Imaging and BioengineeringNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institute of General Medical SciencesU.S. Department of Defense
KeywordsMedicineNeck painPsychological interventionFamily medicineStakeholderAlternative medicinePhysical therapyPublic relationsNursingPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: The past two decades have witnessed a surge in the use of cervical spine joint procedures including joint injections, nerve blocks and radiofrequency ablation to treat chronic neck pain, yet many aspects of the procedures remain controversial. METHODS: In August 2020, the American Society of Regional Anesthesia and Pain Medicine and the American Academy of Pain Medicine approved and charged the Cervical Joint Working Group to develop neck pain guidelines. Eighteen stakeholder societies were identified, and formal request-for-participation and member nomination letters were sent to those organizations. Participating entities selected panel members and an ad hoc steering committee selected preliminary questions, which were then revised by the full committee. Each question was assigned to a module composed of 4-5 members, who worked with the Subcommittee Lead and the Committee Chairs on preliminary versions, which were sent to the full committee after revisions. We used a modified Delphi method whereby the questions were sent to the committee en bloc and comments were returned in a non-blinded fashion to the Chairs, who incorporated the comments and sent out revised versions until consensus was reached. Before commencing, it was agreed that a recommendation would be noted with >50% agreement among committee members, but a consensus recommendation would require ≥75% agreement. RESULTS: Twenty questions were selected, with 100% consensus achieved in committee on 17 topics. Among participating organizations, 14 of 15 that voted approved or supported the guidelines en bloc, with 14 questions being approved with no dissensions or abstentions. Specific questions addressed included the value of clinical presentation and imaging in selecting patients for procedures, whether conservative treatment should be used before injections, whether imaging is necessary for blocks, diagnostic and prognostic value of medial branch blocks and intra-articular joint injections, the effects of sedation and injectate volume on validity, whether facet blocks have therapeutic value, what the ideal cut-off value is for designating a block as positive, how many blocks should be performed before radiofrequency ablation, the orientation of electrodes, whether larger lesions translate into higher success rates, whether stimulation should be used before radiofrequency ablation, how best to mitigate complication risks, if different standards should be applied to clinical practice and trials, and the indications for repeating radiofrequency ablation. CONCLUSIONS: Cervical medial branch radiofrequency ablation may provide benefit to well-selected individuals, with medial branch blocks being more predictive than intra-articular injections. More stringent selection criteria are likely to improve denervation outcomes, but at the expense of false-negatives (ie, lower overall success rate). Clinical trials should be tailored based on objectives, and selection criteria for some may be more stringent than what is ideal in clinical practice.

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)0.129
metaresearch head score (Gemma)0.187
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: none
Teacher disagreement score0.129
Threshold uncertainty score0.681

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1290.187
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.005
Bibliometrics0.0140.009
Science and technology studies0.0030.003
Scholarly communication0.0060.005
Open science0.0090.008
Research integrity0.0100.009
Insufficient payload (model declined to judge)0.0100.008

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 head0.179
GPT teacher head0.430
Teacher spread0.251 · 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

Citations56
Published2021
Admission routes1
Has abstractyes

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