The characteristics of chronic pain after non-traumatic, non-compressive myelopathy: Focus on neuropathic pain
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to assess the characteristics of neuropathic pain after non-traumatic, non-compressive (NTNC) myelopathy and find potential predictors for neuropathic pain. DESIGN: We analyzed 54 patients with NTNC myelopathy. The Short Form McGill Pain Questionnaire (SF-MPQ) and the Leeds Assessment of Neuropathic Symptoms and Signs (LANSS) were used to assess pain. Health-related QOL was evaluated by the Short Form 36-item (SF-36) health survey. RESULTS: Out of 48 patients with pain, 16 (33.3%) patients experienced neuropathic pain. Mean age was significantly lower in patients with neuropathic pain than in patients with non-neuropathic pain (39.1 ± 12.5 vs. 49.8 ± 9.3, P = 0.002). There were no statistically significant differences in the other variables including sex, etiology of myelopathy, pain and QOL scores between the two groups. A binary logistic regression revealed that onset age under 40, and non-idiopathic etiology were independent predictors of the occurrence of neuropathic pain. Both SF-MPQ and LANSS scores were significantly correlated with SF-36 scores, adjusted by age, sex, presence of diabetes mellitus, and current EDSS scores (r = -0.624, P < 0.0001 for SF-MPQ; r = -0.357, P = 0.017 for LANSS). CONCLUSION: Neuropathic pain must be one of serious complications in patients with NTNC myelopathy and also affects their quality of life. Onset age and etiology of myelopathy are important factors in the development of neuropathic pain in NTNC myelopathy.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".