Degenerative Cervical Myelopathy
Bibliographic record
Abstract
Cervical spinal cord dysfunction can result from either traumatic or nontraumatic causes, including tumors, infections, and degenerative changes. In this article, we review the range of degenerative spinal disorders resulting in progressive cervical spinal cord compression and propose the adoption of a new term, degenerative cervical myelopathy (DCM). DCM comprises both osteoarthritic changes to the spine, including spondylosis, disk herniation, and facet arthropathy (collectively referred to as cervical spondylotic myelopathy), and ligamentous aberrations such as ossification of the posterior longitudinal ligament and hypertrophy of the ligamentum flavum. This review summarizes current knowledge of the pathophysiology of DCM and describes the cascade of events that occur after compression of the spinal cord, including ischemia, destruction of the blood-spinal cord barrier, demyelination, and neuronal apoptosis. Important features of the diagnosis of DCM are discussed in detail, and relevant clinical and imaging findings are highlighted. Furthermore, this review outlines valuable assessment tools for evaluating functional status and quality of life in these patients and summarizes the advantages and disadvantages of each. Other topics of this review include epidemiology, the prevalence of degenerative changes in the asymptomatic population, the natural history and rates of progression, risk factors of diagnosis (clinical, imaging and genetic), and management strategies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".