Characterizing mJOA-defined post-surgical recovery patterns in patients with degenerative cervical myelopathy
Bibliographic record
Abstract
Background: Degenerative cervical myelopathy is a spinal disorder resulting in progressive cord compression and neurological deficits that are assessed using the modified Japanese Orthopedic Association (mJOA) questionnaire. It is difficult to predict which patients will recover neurological function after surgery, making it challenging for clinicians to set postoperative patient expectations. In this study, we used mJOA subscores to identify patterns of recovery and recovery timelines in patients with moderate and severe myelopathy. Methods: Fifty-three myelopathy patients were enrolled and completed the mJOA questionnaire both pre-surgery, and six weeks and six months post-surgery. Pearson chi-square tests were performed to assess relationships of both recovery patterns and recovery timelines with severity of disease. Results: Moderate myelopathy patients were significantly more likely than severe myelopathy patients to experience full recovery of upper extremity, lower extremity, and sensory domains. Disease severity did not significantly impact the timeline during which recovery occurs. Overall, >90% of patients experienced at least partial recovery by six months post surgery, 80% of which demonstrated it within the first six weeks. Conclusions: This study shows the more severe the disease experienced by myelopathy patients, the more likely they will be left with permanent disabilities despite surgery. Early identification and treatment are therefore necessary to prevent worsening quality of life and increased costs of functional dependence. The recovery timelines for each subscore are similar and provide new values to guide patient expectations in their potential post-operative recovery. The overall recovery timeline is more generalizable though potentially lacking the specificity patients seek.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".