The Restless Spinal Cord in Degenerative Cervical Myelopathy
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The spinal cord is subject to a periodic, cardiac-related movement, which is increased at the level of a cervical stenosis. Increased oscillations may exert mechanical stress on spinal cord tissue causing intramedullary damage. Motion analysis thus holds promise as a biomarker related to disease progression in degenerative cervical myelopathy. Our aim was characterization of the cervical spinal cord motion in patients with degenerative cervical myelopathy. MATERIALS AND METHODS: Phase-contrast MR imaging data were analyzed in 55 patients (37 men; mean age, 56.2 [SD,12.0] years; 36 multisegmental stenoses) and 18 controls (9 men, P = .368; mean age, 62.2 [SD, 6.5] years; P = .024). Parameters of interest included the displacement and motion pattern. Motion data were pooled on the segmental level for comparison between groups. RESULTS: In patients, mean craniocaudal oscillations were increased manifold at any level of a cervical stenosis (eg, C5 displacement: controls [n = 18], 0.54 [SD, 0.16] mm; patients [n = 29], monosegmental stenosis [n = 10], 1.86 [SD, 0.92] mm; P < .001) and even in segments remote from the level of the stenosis (eg, C2 displacement: controls [n = 18], 0.36 [SD, 0.09] mm; patients [n = 52]; stenosis: C3, n = 21; C4, n = 11; C5, n = 18; C6, n = 2; 0.85 [SD, 0.46] mm; P < .001). Motion at C2 differed with the distance to the next stenotic segment and the number of stenotic segments. The motion pattern in most patients showed continuous spinal cord motion throughout the cardiac cycle. CONCLUSIONS: Patients with degenerative cervical myelopathy show altered spinal cord motion with increased and ongoing oscillations at and also beyond the focal level of stenosis. Phase-contrast MR imaging has promise as a biomarker to reveal mechanical stress to the cord and may be applicable to predict disease progression and the impact of surgical interventions.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".