Management of temporomandibular joint arthritis in adult rheumatology practices: a survey of adult rheumatologists
Bibliographic record
Abstract
BACKGROUND: The temporomandibular (TMJ) is frequently involved in juvenile idiopathic arthritis (JIA), however little is known about management of this joint once a patient transitions from pediatric to adult care and about how rheumatologists approach TMJ involvement in rheumatoid arthritis (RA). The objective of this project was to describe adult rheumatologists' approaches to the diagnosis and treatment of TMJ arthritis in adults with JIA or RA. FINDINGS: One hundred and eighteen rheumatologists responded to an online survey of adult rheumatologists in the United States and Canada. Respondents estimated that 1-25% of their patients with RA or JIA had TMJ arthritis. Respondents reported lower rates of MRI use (19%) and higher rates of use of splinting/functional devices (50%) than anticipated. Approximately 80% of respondents reported that their practice had a standardized approach to the evaluation of patients with TMJ arthritis. The most commonly used medical therapies were non-steroid anti-inflammatory drugs, anti-tumor necrosis factor alpha medications, and methotrexate. CONCLUSIONS: Despite the majority of respondents stating that their practices had a standardized approach to the diagnosis and treatment of TMJ disease, there nevertheless appeared to be a range of practices reported. Standardizing the evaluation and treatment of TMJ arthritis across practices may benefit both adult and pediatric patients.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".