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Record W2407238194 · doi:10.1227/neu.0000000000000951

Degenerative Cervical Myelopathy

2015· review· en· W2407238194 on OpenAlexaff
Lindsay Tetreault, Christina L. Goldstein, Paul M. Arnold, James S. Harrop, Alan S. Hilibrand, Aria Nouri, Michael G. Fehlings

Bibliographic record

VenueNeurosurgery · 2015
Typereview
Languageen
FieldMedicine
TopicCervical and Thoracic Myelopathy
Canadian institutionsUniversity of TorontoToronto Western HospitalUniversity Health Network
Fundersnot available
KeywordsMedicineMyelopathyCervical spondylosisDegenerative diseaseSpinal cordDegenerative DisorderArthropathyAsymptomaticSurgeryRadiologyOsteoarthritisDiseasePathology

Abstract

fetched live from OpenAlex

Cervical spinal cord dysfunction can result from either traumatic or nontraumatic causes, including tumors, infections, and degenerative changes. In this article, we review the range of degenerative spinal disorders resulting in progressive cervical spinal cord compression and propose the adoption of a new term, degenerative cervical myelopathy (DCM). DCM comprises both osteoarthritic changes to the spine, including spondylosis, disk herniation, and facet arthropathy (collectively referred to as cervical spondylotic myelopathy), and ligamentous aberrations such as ossification of the posterior longitudinal ligament and hypertrophy of the ligamentum flavum. This review summarizes current knowledge of the pathophysiology of DCM and describes the cascade of events that occur after compression of the spinal cord, including ischemia, destruction of the blood-spinal cord barrier, demyelination, and neuronal apoptosis. Important features of the diagnosis of DCM are discussed in detail, and relevant clinical and imaging findings are highlighted. Furthermore, this review outlines valuable assessment tools for evaluating functional status and quality of life in these patients and summarizes the advantages and disadvantages of each. Other topics of this review include epidemiology, the prevalence of degenerative changes in the asymptomatic population, the natural history and rates of progression, risk factors of diagnosis (clinical, imaging and genetic), and management strategies.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.128
GPT teacher head0.382
Teacher spread0.254 · 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

Citations262
Published2015
Admission routes1
Has abstractyes

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