Neuropathic Pain in Female Patients With Fibromyalgia
Bibliographic record
Abstract
OBJECTIVES: To explore the potential contribution of small fiber pathology (SFP) and COMT enzyme gene Val/158/Met functional polymorphism to neuropathic pain (NP) in female fibromyalgia (FM) patients. METHODS: This case-control study was conducted on 60 women with FM and 60 matched healthy women. All patients were subjected to detailed clinical assessment. Sympathetic skin response (SSR) and cutaneous silent period (CSP) were performed to assess small fiber neuropathy (SFN). Catechol-O-methyl-transferase (COMT) SNP, rs4680 (A/G, missense158Val/Met) were genotyped. RESULTS: FM patients had significantly longer latency and lower amplitude of foot and hand SSR ( P <0.001), with 7 patients having unobtainable foot SSR. Also, they had significantly earlier onset latency, longer duration, and more delayed offset latency of CSP ( P <0.001, from most of them). Regarding the relation between COMT genotypes and different disease characteristics, patients with A/A genotypes had a statistically significant increase in pain severity scores compared with those with G/G genotypes ( P =0.013 for McGill and 0.019 for the Visual Analog Scale). Moreover, there was a significant increase in NP scores ( P =0.004 and 0.001, for pain DETEDT and SFNL, respectively) of A/A and A/G compared with G/G genotypes. CONCLUSIONS: Moderate to severe neuropathic pain was experienced by all the studied patients with FM, and small fiber pathology was suggested to be a significant contributor to neuropathic pain. Moreover, the COMT A/A genotype was found to be associated with the NP and pain severity.
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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 | 0.000 |
| 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) | 0.004 | 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".