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Record W2154327787 · doi:10.1186/1546-0096-10-26

Management of temporomandibular joint arthritis in adult rheumatology practices: a survey of adult rheumatologists

2012· article· en· W2154327787 on OpenAlexaboutno aff
Sarah Ringold, Nikolay Tzaribachev, Randy Q. Cron

Bibliographic record

VenuePediatric Rheumatology · 2012
Typearticle
Languageen
FieldMedicine
TopicAutoimmune and Inflammatory Disorders Research
Canadian institutionsnot available
FundersAgency for Healthcare Research and Quality
KeywordsMedicineRheumatologyArthritisInternal medicineTemporomandibular jointRheumatoid arthritisPhysical therapyMethotrexatePathology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.032
GPT teacher head0.311
Teacher spread0.279 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2012
Admission routes1
Has abstractyes

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