Developing Peri-Operative Rehabilitation in Degenerative Cervical Myelopathy [AO Spine RECODE-DCM Research Priority Number 6]: An Unexplored Opportunity?
Bibliographic record
Abstract
STUDY DESIGN: Narrative review. OBJECTIVE: Degenerative cervical myelopathy is one of the most frequent impairments of the spinal cord encountered internationally in adults. Currently, surgical decompression is the recommended treatment for people with DCM (PwCM) presenting with moderate to severe symptoms or neurological deficits. However, despite surgical intervention, not all patients make a complete recovery due to the irreversible tissue damage within the spinal cord. The objective of this review is to describe the state and gaps in the current literature on rehabilitation for PwCM and possible innovative rehabilitation strategies. METHODS: Literature search. RESULTS: In other neurological disorders such as stroke and acute traumatic spinal cord injury (SCI), timely and strategic rehabilitation has been shown to be indispensable for maximizing functional outcomes, and it is imperative that appropriate perioperative rehabilitative interventions accompany surgical approaches in order to enable the best outcomes. In this review, the current state of knowledge regarding rehabilitation for PwCM is described. Additionally, various therapies that have shown to improve outcomes in comparable neurological conditions such as stroke and SCI which may be translated to DCM will be reviewed. CONCLUSIONS: We conclude that locomotor training and arm/hand therapy may benefit PwCM. Further, we conclude that body weight support, robotic assistance, and virtual/augmented reality therapies may be beneficial therapeutic analogs to locomotor and hand therapies.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 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) | 0.005 | 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".