Vitamin D Levels Are Associated With Pain and Pain Catastrophizing in Patients With Fibromyalgia Syndrome
Bibliographic record
Abstract
Objective: Low vitamin D (VD) levels may increase pain sensitivity, particularly by enhancing central sensitivity. Fibromyalgia is associated with disruptions in neurotransmitters and inflammatory pathways within the central nervous system, leading to an increased sensitivity of pain signals. This study aimed to investigate the relationship between vitamin D levels and pain, pain catastrophizing, function, depression, and anxiety. Materials and Methods: This study included 153 patients with Fibromyalgia Syndrome (FMS) and 153 healthy individuals. Vitamin D levels were measured using 5 ml blood samples obtained from both patients and healthy individuals. The Hospital Anxiety and Depression Scale (HADS), Pain Catastrophizing Scale (PCS), McGill Pain Questionnaire-Short Form (MPQ), and Fibromyalgia Impact Questionnaire (FIQ) were used to evaluate pain, pain catastrophizing, psychological symptoms, and function, respectively. Results: VD levels were statistically lower in the FMS group (17.71±9.32 ng/ml) compared to the control group (20.40±9.33 ng/ml) (p<0.05). No statistical difference was found among groups classified according to vitamin D subgroups in terms of FIQ, MPQ, PCS, and HADS scores (p>0.05). There was a negative correlation between VD levels and MPQ, as well as all subgroups of PCS (p>0.05), while no significant correlation was found between VD levels and depression, anxiety, or function. Conclusion: VD levels in patients with FMS were found to be lower than those in healthy individuals, and VD levels were associated with pain and pain catastrophizing in this study. Physician-supervised VD supplementation may improve pain catastrophizing in patients with FMS.
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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 | 0.001 | 0.001 |
| 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".