Developing Novel Therapies for Degenerative Cervical Myelopathy [AO Spine RECODE-DCM Research Priority Number 7]: Opportunities From Restorative Neurobiology
Bibliographic record
Abstract
STUDY DESIGN: Narrative review. OBJECTIVES: To provide an overview of contemporary therapies for the James Lind Alliance priority setting partnership for degenerative cervical myelopathy (DCM) question: 'Can novel therapies, including stem-cell, gene, pharmacological and neuroprotective therapies, be identified to improve the health and wellbeing of people living with DCM and slow down disease progression?' METHODS: A review of the literature was conducted to outline the pathophysiology of DCM and present contemporary therapies that may hold therapeutic value in 3 broad categories of neuroprotection, neuroregeneration, and neuromodulation. RESULTS: Chronic spinal cord compression leads to ischaemia, neuroinflammation, demyelination, and neuronal loss. Surgical intervention may halt progression and improve symptoms, though the majority do not make a full recovery leading to lifelong disability. Neuroprotective agents disrupt deleterious secondary injury pathways, and one agent, Riluzole, has undergone Phase-III investigation in DCM. Although it did not show efficacy on the primary outcome modified Japanese Orthopaedic Association scale, it showed promising results in pain reduction. Regenerative approaches are in the early stage, with one agent, Ibudilast, currently in a phase-III investigation. Neuromodulation approaches aim to therapeutically alter the state of spinal cord excitation by electrical stimulation with a variety of approaches. Case studies using electrical neuromuscular and spinal cord stimulation have shown positive therapeutic utility. CONCLUSION: There is limited research into interventions in the 3 broad areas of neuroprotection, neuroregeneration, and neuromodulation for DCM. Contemporary and novel therapies for DCM are now a top 10 priority, and whilst research in these areas is limited in DCM, it is hoped that this review will encourage research into this priority.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".