Decreased Pain Threshold in Juvenile Idiopathic Arthritis: A Cross-sectional Study
Bibliographic record
Abstract
OBJECTIVE: To examine the pain threshold in children with juvenile idiopathic arthritis (JIA) compared with healthy children by using a digital pressure algometer. METHODS: Fifty-eight children with JIA born between 1995 and 2000 and 91 age-related healthy children participated in the study. We used a digital pressure algometer to measure the pain threshold on 17 symmetric, anatomically predefined joint-related or bone-related areas. All children were asked to rate their current pain on a Faces Pain Scale, and parents of children with JIA were asked to complete a parental revised version of the Child Health Assessment Questionnaire (CHAQ-R). Clinical data were registered on children with JIA. RESULTS: The pain threshold was significantly lower among children with JIA (total mean PT = 1.33 ± 0.69 kg/cm(2)) when compared with the healthy control group (total mean PT = 1.77 ± 0.67 kg/cm(2)). The same pattern was found in all areas measured, including negative control areas that are normally unaffected in JIA (p = 0.0001 to 0.005). Overall, the pain threshold was 34% lower in females than in males in both groups (p < 0.0001). We found no correlation between pain threshold and age, current pain experience, disease duration, or disease activity. CONCLUSION: Children with JIA had a substantially lower pain threshold even in areas usually unaffected by arthritis. Our findings suggest that JIA alters the pain perception and causes decreased pain threshold.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".