Predictors of Return to Normal Neurological Function After Surgery for Moderate and Severe Degenerative Cervical Myelopathy: An Analysis of A Global AOSpine Cohort of Patients
Bibliographic record
Abstract
BACKGROUND: Multiple studies have established the safety and efficacy of surgical intervention for degenerative cervical myelopathy (DCM). Although the main goal of surgery is symptom stabilization, a subset of patients achieves remarkable improvements. OBJECTIVE: To identify predictors of return to normal neurological function after surgery for moderate or severe DCM. METHODS: This is an analysis of 2 prospective multicenter studies (the AOSpine CSM-North America and CSM-International studies) conducted between 2005 and 2011. For patients with complete preoperative magnetic resonance imaging (MRI) and 2-yr follow-up, characteristics were compared between those who achieved a modified Japanese Orthopaedic Association (mJOA) score of 18 at 2 yr (no signs of myelopathy) vs controls. Only patients with baseline mJOA ≤ 14 (moderate and severe myelopathy) were included to minimize ceiling effects. RESULTS: A total of 51 patients (20.3%) out of 251 with moderate or severe baseline myelopathy achieved an mJOA score of 18 at 2 yr. On stepwise multiple logistic regression analysis, T1-weighted (T1W1)-hypointensity (odds ratio [OR] 0.10; 95% confidence interval [CI], 0.01-0.79; P = .03) and longer walking time on the 30-m walking test (OR 0.95; 95% CI, 0.92-0.99; P = .03) were independent predictors of outcome, with an area under the curve of 0.71 for the model. CONCLUSION: In this study, T1W-hypointensity on MRI and longer walking time were found to predict a less likelihood of achieving return to normal neurological function after surgery for moderate or severe DCM. These findings may provide useful information for patient counseling and perioperative expectations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".