Management of mild degenerative cervical myelopathy and asymptomatic spinal cord compression: an international survey
Bibliographic record
Abstract
STUDY DESIGN: Cross-sectional survey. OBJECTIVE: Currently there is limited evidence and guidance on the management of mild degenerative cervical myelopathy (DCM) and asymptomatic spinal cord compression (ASCC). Anecdotal evidence suggest variance in clinical practice. The objectives of this study were to assess current practice and to quantify the variability in clinical practice. METHODS: Spinal surgeons and some additional health professionals completed a web-based survey distributed by email to members of AO Spine and the Cervical Spine Research Society (CSRS) North American Society. Questions captured experience with DCM, frequency of DCM patient encounters, and standard of practice in the assessment of DCM. Further questions assessed the definition and management of mild DCM, and the management of ASCC. RESULTS: A total of 699 respondents, mostly surgeons, completed the survey. Every world region was represented in the responses. Half (50.1%, n = 359) had greater than 10 years of professional experience with DCM. For mild DCM, standardised follow-up for non-operative patients was reported by 488 respondents (69.5%). Follow-up included a heterogeneous mix of investigations, most often at 6-month intervals (32.9%, n = 158). There was some inconsistency regarding which clinical features would cause a surgeon to counsel a patient towards surgery. Practice for ASCC aligned closely with mild DCM. Finally, there were some contradictory definitions of mild DCM provided in the form of free text. CONCLUSIONS: Professionals typically offer outpatient follow up for patients with mild DCM and/or asymptomatic ASCC. However, what this constitutes varies widely. Further research is needed to define best practice and support patient care.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".