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Record W2952133003 · doi:10.1097/brs.0000000000003124

Treatment of Mild Cervical Myelopathy

2019· article· en· W2952133003 on OpenAlexaffabout
Michael Bond, Greg McIntosh, Charles G. Fisher, Bradley Jacobs, Michael G. Johnson, Christopher S. Bailey, Sean Christie, Raphaële Charest-Morin, Jérôme Paquet, Andrew Nataraj, David W. Cadotte, J. A. Wilson, Neil Manson, Hamilton Hall, Kenneth Thomas, Y. Raja Rampersaud, Nicolas Dea

Bibliographic record

VenueSpine · 2019
Typearticle
Languageen
FieldMedicine
TopicCervical and Thoracic Myelopathy
Canadian institutionsSpinal Cord Injury BCCanada East Spine CentreSaint John Regional HospitalUniversity of AlbertaUniversity of TorontoDalhousie UniversityWestern UniversityCentre hospitalier universitaire de QuébecUniversity of ManitobaUniversity of CalgaryUniversity of British Columbia
Fundersnot available
KeywordsMedicineMyelopathyProspective cohort studyLogistic regressionQuality of life (healthcare)SurgeryCohortInternal medicinePhysical therapySpinal cord

Abstract

fetched live from OpenAlex

STUDY DESIGN: Prospective Cohort OBJECTIVE.: The aim of this study was to evaluate which demographic, clinical, or radiographic factors are associated with selection for surgical intervention in patients with mild cervical spondylotic myelopathy (CSM). SUMMARY OF BACKGROUND DATA: Surgery has not been shown superior to best conservative management in mild CSM comparative studies; trials of conservative management represent an acceptable alternative to surgical decompression. It is unknown what patients benefit from surgery. METHODS: This is a prospective study of patients with mild CSM, defined as modified Japanese Orthopaedic Association Score (mJOA) ≥15. Patients were recruited from seven sites contributing to the Canadian Spine Outcomes Research Network. Demographic, clinical, radiographic and health related quality of life data were collected on all patients at baseline. Multivariate logistic regression modeling was used to identify factors associated with surgical intervention. RESULTS: There were 122 patients enrolled, 105 (86.0%) were treated surgically, and 17 (14.0%) were treated nonoperatively. Overall mean age was 54.8 years (SD 12.6) with 80 (65.5%) males. Bivariate analysis revealed no statistically significant differences between surgical and nonoperative groups with respect to age, sex, BMI, smoking status, number of comorbidities and duration of symptoms; mJOA scores were significantly higher in the nonoperative group (16.8 [SD 0.99] vs. 15.9 [SD 0.89], P < 0.001). There was a statistically significant difference in Neck Disability Index, SF12 Physical Component, SF12 Mental Component Score, EQ5D, and PHQ-9 scores between groups; those treated surgically had worse baseline questionnaire scores (P < 0.05). There was no difference in radiographic parameters between groups. Multivariable analysis revealed that lower quality of life scores on EQ5D were associated with selection for surgical management (P < 0.018). CONCLUSION: Patients treated surgically for mild cervical myelopathy did not differ from those treated nonoperatively with respect to baseline demographic or radiographic parameters. Patients with worse EQ5D scores had higher odds of surgical intervention. LEVEL OF EVIDENCE: 3.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.018
GPT teacher head0.287
Teacher spread0.269 · 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 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

Citations27
Published2019
Admission routes2
Has abstractyes

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