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Record W2973112778

Degenerative cervical myelopathy: Diagnosis and management in primary care.

2019· article· en· W2973112778 on OpenAlexaff
James Milligan, Kayla Ryan, Michael G. Fehlings, Craig Bauman

Bibliographic record

VenuePubMed · 2019
Typearticle
Languageen
FieldMedicine
TopicCervical and Thoracic Myelopathy
Canadian institutionsCanadian Chiropractic AssociationToronto Western HospitalCentre for Family Medicine
Fundersnot available
KeywordsMedicineMyelopathyAsymptomaticSpinal cord compressionNatural historyWeaknessDiseaseDegenerative diseaseSpinal cordSurgeryPhysical therapyPathologyInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To raise awareness about degenerative cervical myelopathy (DCM) and to help family physicians identify, diagnose, and manage DCM more effectively. SOURCES OF INFORMATION: . MAIN MESSAGE: Owing to limited knowledge of DCM in primary care, along with the large variability of the disease, the diagnosis of DCM is often missed or delayed. The natural course of DCM presents as a stepwise decline, with symptoms ranging from muscle weakness to complete paralysis. All individuals with signs and symptoms should be referred to a spine surgeon for consideration of surgery; those with mild DCM might be offered conservative treatment but should receive a surgical evaluation and opinion nonetheless. Asymptomatic patients with evidence of cord compression on magnetic resonance imaging might need to be referred for assessment; however, surgery is not advised. It is critical to closely monitor asymptomatic individuals or those with mild DCM for neurologic deterioration. CONCLUSION: Degenerative cervical myelopathy is the most common cause of spinal cord dysfunction in adults. This review helps streamline its diagnosis in primary care, allowing for improved chances of early diagnosis and prevention of further neurologic decline among patients.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.631
Threshold uncertainty score0.401

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 integrity0.0000.000
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 head0.016
GPT teacher head0.229
Teacher spread0.213 · 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 designObservational
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

Citations66
Published2019
Admission routes1
Has abstractyes

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