Temporomandibular Disorders and Fibromyalgia Prevalence: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
PURPOSE: To evaluate the prevalence of chronic widespread pain (CWP) and fibromyalgia syndrome (FMS) in TMD patients and the prevalence of TMDs in patients with FMS. METHOD: A systematic search was performed in electronic databases. Studies published in English examining the prevalence of comorbid TMDs and CWP/FMS were included. The Newcastle-Ottawa Scale was used to assess study quality, and meta-analyses using defined diagnostic criteria were conducted to generate pooled prevalence estimates. RESULTS: Nineteen studies of moderate to high quality met the selection criteria. Meta-analyses yielded a pooled prevalence rate (95% CI) for TMDs in FMS patients of 76.8% (69.5% to 83.3%). Myogenous TMDs were more prevalent in FMS patients (63.1%, 47.7% to 77.3%) than disc displacement disorders (24.2%, 19.4% to 39.5%), while a little over 40% of FMS patients had comorbid inflammatory degenerative TMDs (41.8%, 21.9% to 63.2%). Almost a third of individuals (32.7%, 4.5% to 71.0%) with TMDs had comorbid FMS, while estimates of comorbid CWP across studies ranged from 30% to 76%. CONCLUSIONS: Despite variable prevalence rates among the included studies, the present review suggests that TMDs and CWP/FMS frequently coexist, especially for individuals with painful myogenous TMDs. The clinical, pathophysiologic, and therapeutic aspects of this association are important for tailoring appropriate treatment strategies.
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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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.029 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".