Is Preoperative Duration of Symptoms a Significant Predictor of Functional Outcomes in Patients Undergoing Surgery for the Treatment of Degenerative Cervical Myelopathy?
Bibliographic record
Abstract
BACKGROUND: Preoperative duration of symptoms may significantly impact outcomes in patients treated surgically for degenerative cervical myelopathy (DCM). OBJECTIVE: To (i) analyze whether duration of symptoms is associated with preoperative functional impairment, disability, and quality of life and (ii) determine the optimal timing for decompressive surgery. METHODS: Patients with DCM were prospectively enrolled in either the AOSpine North American or International study at 26 global sites (n = 757). Postoperative functional impairment was evaluated at 1-yr using the modified Japanese Orthopaedic Association (mJOA) score. Change scores between baseline and 1-yr were computed for the mJOA. Duration of symptoms was dichotomized into a "short" and "long" group at several cut-offs. Analysis of covariance was used to evaluate differences in change scores on the mJOA between duration of symptoms groups in 4-mo increments. RESULTS: Our cohort consisted of 424 men and 255 women, with a mean duration of symptoms of 26.1 ± 36.4 mo (0.25-252 mo). Duration of symptoms was not correlated with preoperative mJOA, Nurick, Neck Disability Index, or Short-Form (SF)-36 Physical and Mental Component Scores. Patients with a duration of symptoms shorter than 4 mo had significantly better functional outcomes on the mJOA than patients with a longer duration of symptoms (>4 mo). Thirty-two months was also a significant cut-off. CONCLUSION: Patients who are operated on within 4 mo of symptom presentation have better mJOA outcomes than those treated after 4 mo. It is recommended that patients with DCM are diagnosed in a timely fashion and managed appropriately.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".