Relationship Between Pain and Neuropathic Symptoms in Chronic Musculoskeletal Pain
Bibliographic record
Abstract
OBJECTIVE: The present study aimed to assess neuropathic symptoms, their stability over time and relationship to pain intensity, pain distribution, and emotional distress in patients with musculoskeletal disorders. DESIGN: This is a prospective study. SETTING: The study was done at the Department of Physical Medicine and Rehabilitation at Ulleval University Hospital. PATIENTS: Eighty-six subjects between 18 years and 70 years with chronic musculoskeletal pain participated. Forty-nine subjects had widespread pain and 39 subjects fulfilled the American College of Rheumatology (ACR) criteria for fibromyalgia. OUTCOME MEASURES: McGill pain drawing, pain intensity (visual analog scales), emotional distress (Hopkins Symptom Checklist v 25), and fibromyalgia impact questionnaire were the recorded predictors, and neuropathic symptoms (Leeds assessment of neuropathic symptoms and signs-LANSS) were the main outcome variable which was assessed over 4 months. RESULTS: The mean LANSS score was 6.7 (standard deviation 5.6). Thirteen percent of the subjects had a score of 12 or more. Self-reported LANSS symptoms did not change over the 4 months follow-up, and the reliability of measurements as evaluated by intraclass correlation coefficient was 0.78. In a backward multiple regression analysis, the presence of fibromyalgia diagnosis and emotional distress remained the final predictors for neuropathic symptoms. CONCLUSIONS: Our study demonstrates that neuropathic symptoms are prominent features of chronic musculoskeletal pain and are stable over time. These symptoms were closely related to emotional distress and to the diagnosis of fibromyalgia. The results lend support to the theory that neuropathic symptoms represent an underlying sensitization.
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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 | 0.015 | 0.007 |
| 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".