Basal Ganglia Perfusion in Fibromyalgia is Related to Pain Disability and Disease Impact
Bibliographic record
Abstract
OBJECTIVES: Pain disability is a major impediment to fibromyalgia (FM) patients' quality of life. Neuroimaging studies have demonstrated abnormal pain processing in FM. However, it is not known whether there are brain abnormalities linked to pain disability. Understanding neural correlates of pain disability in FM, independent from pain intensity, could provide a framework to guide future more efficient therapy strategies to improve patients' functional ability. METHODS: We used arterial spin labeling to image cerebral blood flow (CBF) in 23 FM patients and 16 controls. Functional connectivity was also estimated using blood oxygenation level-dependent imaging to further investigate the possible underpinnings of the observed CBF changes. RESULTS: Among patients, CBF in the basal ganglia correlated negatively with pain disability index and positively with the overall impact of FM (Fibromyalgia Impact Questionnaire) but did not correlate with pain intensity. Whole-brain analysis revealed no CBF differences between the 2 groups; however, post hoc analysis in the basal ganglia showed CBF reductions mainly in the right putamen and right lateral globus pallidus in patients, likely reflecting the negative correlation with the pain disability index. However, the connectivity of the corresponding corticobasal ganglia-thalamus loop, that is, motor network (the connection between supplementary motor area, putamen, and thalamus) remained intact. DISCUSSION: Basal ganglia perfusion reflects long-term symptoms, including somatic and psychological components of FM rather than pain intensity. These CBF findings may reflect differences in behavioral and psychological responses between patients.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".