A Clinical Prediction Model to Determine Outcomes in Patients with Cervical Spondylotic Myelopathy Undergoing Surgical Treatment
Bibliographic record
Abstract
BACKGROUND: Cervical spondylotic myelopathy is a progressive spine disease and the most common cause of spinal cord dysfunction worldwide. The objective of this study was to develop a prediction model, based on data from a prospective multi-center study, relating a combination of clinical and imaging variables to surgical outcome in patients with cervical spondylotic myelopathy. METHODS: Two hundred and seventy-eight patients diagnosed with cervical spondylotic myelopathy treated surgically were enrolled at twelve different sites in the multi-center AOSpine North America study. Univariate analyses were performed to evaluate the relationship between outcome, assessed with the modified Japanese Orthopaedic Association (mJOA) score, and various clinical and imaging predictors. A set of important candidate variables for the final model was selected on the basis of author consensus, literature support, and statistical findings. Logistic regression was used to formulate the final model. RESULTS: Univariate analyses demonstrated that the odds of a successful outcome decreased with a longer duration of symptoms (odds ratio [OR] = 0.80, 95% confidence interval [CI] = 0.65 to 0.98, p = 0.030); a lower baseline mJOA score (OR = 0.74, 95% CI = 0.65 to 0.84, p < 0.0001); the presence of psychological comorbidities (OR = 0.51, 95% CI = 0.29 to 0.92, p = 0.024); the presence of broad-based, unstable gait (OR = 2.72, 95% CI = 1.47 to 5.06, p = 0.0018) or other gait impairment (OR = 3.56, 95% CI = 1.75 to 7.22, p = 0.0005); and older age (OR = 0.96, 95% CI = 0.93 to 0.98, p = 0.0004). The dependent variable, the mJOA score at one year, was dichotomized for logistic regression: a "successful" outcome was defined as a final score of ≥16 and a "failed" outcome was a score of <16. The final model included age (OR = 0.97, 95% CI = 0.94 to 0.99, p = 0.0017), duration of symptoms (OR = 0.78, 95% CI = 0.61 to 0.997, p = 0.048), smoking status (OR = 0.46, 95% CI = 0.21 to 0.98, p = 0.043), impairment of gait (OR = 2.66, 95% CI = 1.17 to 6.06, p = 0.020), psychological comorbidities (OR = 0.33, 95% CI = 0.15 to 0.69, p = 0.0035), baseline mJOA score (OR = 1.22, 95% CI = 1.05 to 1.41, p = 0.0084), and baseline transverse area of the cord on magnetic resonance imaging (OR = 1.02, 95% CI = 0.99 to 1.05, p = 0.19). The area under the receiver operator characteristic curve was 0.79, indicating good model prediction. CONCLUSIONS: On the basis of the results of the AOSpine North America study, we identified a list of the most important predictors of surgical outcome for cervical spondylotic myelopathy.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".