Pain chronobiology in clinical trial participants with fibromyalgia: a comparison with neuropathic pain
Bibliographic record
Abstract
Introduction: Diurnal pain rhythmicity is well recognized for neuropathic pain (NP) and osteoarthritis, however, less is known for fibromyalgia. Objective: We conducted secondary analyses of clinical trial data to describe pain rhythmicity in fibromyalgia compared to NP. Methods: We have compared morning-evening pain differences in fibromyalgia with that of NP by conducting exploratory analyses of data from 2 fibromyalgia trials (68 pooled participants) and 1 NP trial (55 participants). In these trials, pain intensity (0-10 scale) was rated at 8:00 am and 8:00 pm during a 7-day pretrial baseline period and throughout each trial. Analyses evaluated morning vs evening pain intensity differences for each condition as well as possible patient-specific predictors of diurnal variability. Results: Data demonstrated statistically significant morning-evening differences in both conditions such that evening pain was higher than morning pain by approximately 20% in NP (0.97 NRS, CI: 0.77-1.16) and approximately 7% in fibromyalgia (0.38 numerical rating scale (NRS), CI:0.22-0.53). The morning-evening pain intensity difference was significantly greater for NP vs fibromyalgia. In exploratory analyses of participants with fibromyalgia, older age, shorter pain duration, and more severe "hot-burning" pain rating were significantly correlated with greater morning-evening differences. In NP participants, higher body weight and higher pain interference were significantly correlated with lower morning-evening differences. Conclusions: These analyses suggest that fibromyalgia pain is slightly more intense in the evening vs morning. Although it seems less pronounced than with NP, patient subgroups with this pattern should be studied further when investigating and implementing fibromyalgia treatment interventions.
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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 | 0.022 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".