Orofacial Symptoms Related to Temporomandibular Joint Arthritis in Juvenile Idiopathic Arthritis: Smallest Detectable Difference in Self-reported Pain Intensity
Bibliographic record
Abstract
OBJECTIVE: Temporomandibular joint (TMJ) inflammation in patients with juvenile idiopathic arthritis (JIA) may lead to mandibular growth disturbances and interfere with optimal joint and muscle function. Orofacial symptoms are common clinical findings in relation to TMJ arthritis in adolescence. Knowledge about their clinical manifestation is important for TMJ arthritis diagnosis, treatment choice, and outcome evaluation. The aim of our prospective observational study was to evaluate and describe the frequency, the main complaints, and the localization of TMJ arthritis-related orofacial symptoms. The smallest detectable differences (SDD) for minimal, average, and maximal pain were estimated. METHODS: Thirty-three patients with JIA and arthritis-related orofacial symptoms in relation to 55 affected TMJ were included in our questionnaire study (mean age 14.11 yrs). Calculation of the SDD was based on a duplicate assessment 45 min after the first questionnaire was completed. RESULTS: The majority of the patients had common orofacial symptoms during mastication and maximal mouth opening procedures. Persistent orofacial symptoms were rare. The TMJ area in combination with the masseter muscle region was the orofacial region where symptoms were most common. The SDD for minimal, average, and maximal pain were between 10 and 14 mm on a visual analog scale. CONCLUSION: Our study offers new knowledge about TMJ arthritis-related orofacial symptoms that may aid diagnosis and clinical decision-making. We suggest that TMJ arthritis-related orofacial symptoms could be understood as products of the primary TMJ inflammation in combination with secondary myogenic and functional issues.
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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 | 0.004 |
| 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".