Clinical outcomes of nonoperatively managed degenerative cervical myelopathy: an ambispective longitudinal cohort study in 117 patients
Bibliographic record
Abstract
OBJECTIVE: Degenerative cervical myelopathy (DCM) is among the most common pathologies affecting the spinal cord but its natural history is poorly characterized. The purpose of this study was to investigate functional outcomes in patients with DCM who were managed nonoperatively as well as the utility of quantitative clinical measures and MRI to detect deterioration. METHODS: Patients with newly diagnosed DCM or recurrent myelopathic symptoms after previous surgery who were initially managed nonoperatively were included. Retrospective chart reviews were performed to analyze clinical outcomes and anatomical MRI scans for worsening compression or increased signal change. Quantitative neurological assessments were collected prospectively, including modified Japanese Orthopaedic Association (mJOA) score; Quick-DASH; graded redefined assessment of strength, sensation, and prehension-myelopathy version (GRASSP-M: motor, sensory, and dexterity); grip dynamometer; Berg balance scale score; gait stability ratio; and gait variability index. A deterioration of 10% was considered significant (e.g., a 2-point decrease in mJOA score). RESULTS: A total of 117 patients were included (95 newly diagnosed, 22 recurrent myelopathy), including 74 mild, 28 moderate, and 15 severe cases. Over a mean follow-up of 2.5 years, 57% (95% CI 46%-67%) of newly diagnosed patients and 73% (95% CI 50%-88%) of patients with recurrent DCM deteriorated neurologically. Deterioration was best detected with grip strength (60%), GRASSP dexterity (60%), and gait stability ratio (50%), whereas the mJOA score had low sensitivity (33%) in 50 patients. A composite score had a sensitivity of 81% and a specificity of 82%. The sensitivity of anatomical MRI was 28% (83 patients). CONCLUSIONS: DCM appears to have a poor natural history; however, prospective studies are needed for validation. Serial assessments should include mJOA score, grip strength, dexterity, balance, and gait analysis. The absence of worsening on anatomical MRI or in mJOA scores is not sufficient to determine clinical stability.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".