Epidermal Neurite Density in Skin Biopsies From Patients With Juvenile Fibromyalgia
Bibliographic record
Abstract
OBJECTIVE: Fibromyalgia (FM) is defined by idiopathic, chronic, widespread musculoskeletal pain. In adults with FM, a metaanalysis of lower-leg skin biopsy demonstrated 45% pooled prevalence of abnormally low epidermal neurite density (END). END < 5th centile of the normal distribution is the consensus diagnostic threshold for small-fiber neuropathy. However, the clinical significance of END findings in FM is unknown. Here, we examine the prevalence of small-fiber pathology in juvenile FM, which has not been studied previously. METHODS: We screened 21 patients aged 13-20 years with FM diagnosed by pediatric rheumatologists. Fifteen meeting the American College of Rheumatology criteria (modified for juvenile FM) underwent lower-leg measurements of END and completed validated questionnaires assessing pain, functional disability, and dysautonomia symptoms. The primary outcome was proportion of FM patients with END < 5th centile of age/sex/race-based laboratory norms. Cases were systematically matched by ethnicity, race, sex, and age to a group of previously biopsied healthy adolescents with selection blinded to biopsy results. All 23 controls matching demographic criteria were included. RESULTS: < 0.001). As expected, patients with FM reported more functional disability, dysautonomia, and pain than healthy controls. CONCLUSION: Abnormal END reduction is common in adolescents with FM, with similar prevalence in adults with FM. More studies are needed to fully characterize the significance of low END in FM and to elucidate the clinical implications of these findings.
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 | 0.003 |
| 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) | 0.001 | 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".