Sensory Function and Pain Experience in Arthritis, Complex Regional Pain Syndrome, Fibromyalgia Syndrome, and Pain-Free Volunteers
Bibliographic record
Abstract
OBJECTIVES: This study aimed to identify relationships between sensory function and pain in 3 common pain conditions (arthritis, Complex Regional Pain Syndrome [CRPS] and fibromyalgia syndrome [FMS]) and pain-free participants. Sensory abnormalities are known to be concomitant with some types of chronic pain but comparison across pain conditions using existing research is difficult due to methodological differences. Pragmatic Quantitative Sensory Testing (QST) methods were used. MATERIALS AND METHODS: Hot and cold sensitivity, light touch threshold (LTT), two-point discrimination and pain threshold were assessed in 143 participants (n=37 pain-free, n=34 arthritis, n=36 CRPS, n=36 FMS). Outcomes were assessed in the index ("affected" or right) and contralateral arm. Participants also completed the Brief Pain Inventory and the McGill Pain Questionnaire. RESULTS: There were statistically significant differences between groups for all QST outcomes except two-point discrimination. Relative to pain-free participants, FMS displayed heat hyperesthesia in both arms and cold hyperesthesia in the contralateral arm. CRPS demonstrated no changes in thermal sensitivity. Both CRPS and FMS exhibited bilateral pressure hyperalgesia. LTT hypoesthesia was observed bilaterally for CRPS but only in the contralateral arm for FMS. CRPS and FMS had pressure hyperalgesia in the index arm relative to arthritis patients. There were no differences between arthritis and pain-free participants for any QST outcome. In CRPS, there were significant correlations between LTT and pain outcomes bilaterally. DISCUSSION: People with FMS and CRPS demonstrate extensive sensory dysfunction. Arthritis patients had sensory profiles closer to pain-free participants. LTT may provide a clinically relevant and accessible assessment for CRPS.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".