A Clinical Prediction Rule for Functional Outcomes in Patients Undergoing Surgery for Severe Degenerative Cervical Myelopathy: Analysis of an International AOSpine Prospective Multicentre Dataset of 254 Subjects
Bibliographic record
Abstract
Introduction Patients with cervical spondylotic myelopathy (CSM) may be severely impaired, have reduced quality of life and present with deleterious signs and symptoms. Patients with severe myelopathy (mJOA < 12) often improve following surgery; however, some may not achieve a minimum clinically important difference (MCID), whereas others may have exceptional outcomes. Due to varying prognoses among this group, it is important to predict outcome in these patients and use this knowledge to manage expectations. This study aims to determine the most important clinical predictors of surgical outcome in patients with severe CSM. Material and Methods Of the 757 patients enrolled in the CSM-North America or International studies, 254 (33.55%) presented with severe myelopathy as classified by a mJOA < 12 points. A prediction model was developed to distinguish between patients who improve to mild or moderate myelopathy postoperatively (mJOA≥12) and those who remain significantly impaired (mJOA < 12). Univariate analyses evaluated the relationship between this outcome and various clinical predictors. Multivariate Poisson regression was used to formulate the final prediction model and to compute the relative risks. A secondary model was constructed to predict which patients would achieve a MCID on the mJOA, defined as a change score of three or more points in patients with severe disease. Results Our cohort consisted of 153 men and 101 women with ages ranging from 28 to 86 (mean: 60.09 ± 12.06 years). The mean preoperative mJOA was 9.42 ± 1.67. One hundred and fifty-four (60.63%) patients improved to a score ≥12 at 1-year postoperative, whereas 145 (57.09%) achieved a MCID on the mJOA. Baseline severity score (RR: 1.07, 95%C.I.: 1.02–1.13), hyperreflexia (RR: 0.83, 95%C.I.: 0.72–0.96), lower limb spasticity (RR: 0.75, 95%C.I.: 0.65–0.86), and age (RR: 0.97, 95%C.I.: 0.95–0.99) were significant predictors of a mJOA≥12 following univariate analysis. The final model consisted of three statistically significant variables and one clinically relevant predictor: baseline severity score (RR: 1.09, 95%C.I.: 1.03–1.15), duration of symptoms (RR: 0.94, 95%C.I.: 0.89–0.99), co-morbidity score (RR: 0.96, 95%C.I.: 0.91–1.00) and the sign lower limb spasticity (RR: 0.76, 95%C.I.: 0.66–0.87). The AUC for this model was 0.75 (95%C.I.: 0.67, 0.83). Improvement by the MCID could not be effectively predicted by a combination of clinical variables. Conclusion Severe patients were more likely to achieve a score ≥12 on the mJOA if they had a higher preoperative mJOA score and a shorter duration of symptoms; a lower co-morbidity score (fewer and less severe concomitant disease); and did not have lower limb spasticity.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".