The Relationship Between Preoperative Clinical Presentation and Quantitative Magnetic Resonance Imaging Features in Patients With Degenerative Cervical Myelopathy
Bibliographic record
Abstract
BACKGROUND: Degenerative cervical myelopathy encompasses a group of conditions resulting in progressive spinal cord injury through static and dynamic compression. Although a constellation of changes can present on magnetic resonance imaging (MRI), the clinical significance of these findings remains a subject of controversy and discussion. OBJECTIVE: To investigate the relationship between clinical presentation and quantitative MRI features in patients with degenerative cervical myelopathy. METHODS: A secondary analysis of MRI and clinical data from 114 patients enrolled in a prospective, multicenter study was conducted. MRIs were assessed for maximum spinal cord compression (MSCC), maximum canal compromise (MCC), signal changes, and a signal change ratio (SCR). MRI features were compared between patients with and those without myelopathy symptoms with the use of t tests. Correlations between MRI features and duration of symptoms were assessed with the Spearman ρ. RESULTS: Numb hands and Hoffmann sign were associated with greater MSCC ( P < .05); broad-based, unstable gait, impairment of gait, and Hoffmann sign were associated with greater MCC ( P < .05); and numb hands, Hoffmann sign, Babinski sign, lower limb spasticity, hyperreflexia, and T1 hypointensity were associated with greater SCR ( P < .05). Patients with a T2 signal hyperintensity had greater MSCC and MCC ( P < .001). CONCLUSION: MSCC was associated with upper limb manifestations, and SCR was associated with upper limb, lower limb, and general neurological deficits. Hoffmann sign occurred more commonly in patients with a greater MSCC, MCC and SCR. The Lhermitte phenomenon presented more commonly in patients with a lower SCR and may be an early indicator of mild spinal cord involvement. Research to validate these findings is required.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".