Postoperative Magnetic Resonance Imaging Can Predict Neurological Recovery After Surgery for Cervical Spondylotic Myelopathy: A Prospective Study With Blinded Assessments
Bibliographic record
Abstract
BACKGROUND: Factors that can predict the recovery of cervical spondylotic myelopathy (CSM) patients postoperatively are of significant interest to physicians and patients and their families. Magnetic resonance imaging (MRI) scans are a common method of examination after surgery, and thus of interest as a predictor of outcome. OBJECTIVE: To investigate whether findings on MRI at 6 months postoperatively could predict recovery at 1 year in CSM patients. METHODS: In 52 consecutive prospective patients, MRI was performed preoperatively and 6 months postoperatively. T1 and T2 signal change (area, height, and segmentation) and spinal cord re-expansion were measured. Outcome measures evaluated at 1 year postoperatively were compared with preoperative values. Univariate and stepwise multiple regressions were undertaken. RESULTS: Using univariate analysis, patients whose cord failed to re-expand had poorer outcome according to the modified Japanese Orthopedic Association score and Nurick score (P = .014) and grip test (P = .006) postoperatively. Stepwise multivariate regression showed lack of cord re-expansion to be predictive of prognosis postoperatively in the modified Japanese Orthopedic Association score (P = .013) and Berg Balance Scale (P = .014), and walking test (P = .011). Postoperative hyperintense T2 signal change was predictive of worse outcome on the Berg Balance Scale (P = .014) and walking test (P = .020), Nurick score (P = .001), and Short Form-36 scores (P = .020). In cases in which the T2 signal intensified, there was a poorer outcome on Nurick scores (P = .013), grip test (P = .017), and Short Form-36 scores (P = .030). CONCLUSION: Findings on postoperative MRI at 6 months is of predictive value in determining outcomes in CSM patients. The persistence and type of T2 signal change and lack of re-expansion of the cord correlate with poorer recovery and likely reflect irreversible structural changes in the spinal cord.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".