Analysis of recovery trajectories in degenerative cervical myelopathy to facilitate improved patient counseling and individualized treatment recommendations
Bibliographic record
Abstract
OBJECTIVE: There is a need to better understand and predict postsurgical outcomes for degenerative cervical myelopathy (DCM) patients, particularly to support treatment decisions for patients with mild DCM. The goal of this study was to identify and predict outcome trajectories for DCM patients up to 2 years postsurgery. METHODS: The authors analyzed two North American multicenter prospective DCM studies (n = 757). Functional recovery and physical health component quality of life were assessed in DCM patients at baseline, 6 months, and 1 and 2 years postoperatively using the modified Japanese Orthopaedic Association (mJOA) score and Physical Component Summary (PCS) of the SF-36, respectively. Group-based trajectory modeling was used to identify recovery trajectories for mild, moderate, and severe DCM. Prediction models for recovery trajectories were developed and validated in bootstrap resamples. RESULTS: Two recovery trajectories were identified for the functional and physical components of quality of life: good recovery and marginal recovery. Depending on outcome and myelopathy severity, one-half to three-fourths of the study patients followed the good recovery trajectory characterized by improvement in mJOA and PCS scores over time. The remaining one-half to one-fourth of patients followed the marginal recovery trajectory, experiencing little improvement and, in certain cases, worsening postoperatively. The prediction model for mild DCM had an area under the curve of 0.72 (95% CI 0.65-0.80), with preoperative neck pain, smoking, and posterior surgical approach noted as dominant predictors of marginal recovery. CONCLUSIONS: Surgically treated DCM patients follow distinct recovery trajectories in the first 2 years postoperatively. While most patients experience substantial improvement, a significant minority experience little improvement or worsening. The ability to predict DCM patient recovery trajectories in the preoperative setting facilitates the formulation of individualized treatment recommendations for patients with mild symptoms.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".