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Record W2954919231 · doi:10.1371/journal.pone.0219380

A comparison of radiological descriptions of spinal cord compression with quantitative measures, and their role in non-specialist clinical management

2019· article· en· W2954919231 on OpenAlexaff
Jennifer Tempest-Mitchell, Bryn Hilton, Benjamin M. Davies, Aria Nouri, Peter J. Hutchinson, Daniel Scoffings, Richard Mannion, Rikin Trivedi, Ivan Timofeev, John R. Crawford, Douglas Hay, Rodney J. Laing, Mark Kotter

Bibliographic record

VenuePLoS ONE · 2019
Typearticle
Languageen
FieldMedicine
TopicCervical and Thoracic Myelopathy
Canadian institutionsToronto Western HospitalUniversity Health Network
FundersMedical Research CouncilNational Institute for Health and Care ResearchDepartment of Health and Social CareWellcome Trust
KeywordsMedicineSpinal cord compressionMyelopathyRadiological weaponSpinal cordCordRadiologyMagnetic resonance imagingSpinal canalSurgery

Abstract

fetched live from OpenAlex

INTRODUCTION: Magnetic resonance imaging (MRI) is gold-standard for investigating Degenerative Cervical Myelopathy (DCM), a disabling disease triggered by compression of the spinal cord following degenerative changes of adjacent structures. Quantifiable compression correlates poorly with disease and language describing compression in radiological reports is un-standardised. STUDY DESIGN: Retrospective chart review. OBJECTIVES: 1) Identify terminology in radiological reporting of cord compression and elucidate relationships between language and quantitative measures 2) Evaluate language's ability to distinguish myelopathic from asymptomatic compression 3) Explore correlations between quantitative or qualitative features and symptom severity 4) Investigate the influence of quantitative and qualitative measures on surgical referrals. METHODS: From all cervical spine MRIs conducted during one year at a tertiary centre (N = 1123), 166 patients had reported cord compression. For each spinal level deemed compressed by radiologists (N = 218), four quantitative measurements were calculated: 'Maximum Canal Compromise (MCC); 'Maximum Spinal Cord Compression' (MSCC); 'Spinal Canal Occupation Ratio' (SCOR) and 'Compression Ratio' (CR). These were compared to associated radiological reporting terminology. RESULTS: 1) Terminology in radiological reports was varied. Objective measures of compromise correlated poorly with language. "Compressed" was used for more severe cord compromise as measured by MCC (p<0.001), MSCC (p<0.001), and CR (p = 0.002). 2) Greater compromise was seen in cords with a myelopathy diagnosis across MCC (p<0.001); MSCC (p = 0.002) and CR (p<0.001). "Compress" (p<0.001) and "Flatten" (p<0.001) were used more commonly for myelopathy-diagnosis levels. 3) Measurements of cord compromise (MCC: p = 0.304; MSCC: p = 0.217; SCOR: p = 0.503; CR: p = 0.256) and descriptive terms (p = 0.591) did not correlate with i-mJOA score. 4) The only variables affecting spinal surgery referral were increased MSCC (p = 0.001) and use of 'Compressed' (p = 0.045). CONCLUSIONS: Radiological reporting in DCM is variable and language is not fully predictive of the degree of quantitative cord compression. Additionally, terminology may influence surgical referrals.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.229

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.177
GPT teacher head0.376
Teacher spread0.199 · 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

Citations42
Published2019
Admission routes1
Has abstractyes

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