Gender differences in temporomandibular disorders in adult populational studies: A systematic review and meta‐analysis
Bibliographic record
Abstract
The objective of this study was to systematically evaluate gender differences in the prevalence of TMD. A systematic review was performed in PubMed, EMBASE, Web of Science and LILACS in duplicate by two independent reviewers. The inclusion criteria were cross-sectional studies that reported the prevalence of TMD for men and women and that used the Research Diagnostic Criteria for Temporomandibular Disorders (RDC/TMD) Axis I group diagnostic criteria:(group I = muscle disorders; group II = disc displacements; group III = arthralgias/arthritis/arthrosis).To be eligible for inclusion, studies must include adult individuals (>18 years) from a non-clinical population (ie without pre-diagnosis of TMD); in other words, from population-based studies. There were no restrictions on the year and language of publication. The quality of the articles was assessed by an adapted version of the Newcastle-Ottawa Scale(NOS), and the publication bias was assessed by a funnel plot graph. Data were quantitatively analysed by meta-analysis using odds ratio (OR) as the measure effect. The electronic search retrieved a total of 6104 articles, of which 112 articles were selected for full-text reading according to the eligibility criteria. By means of manual search, one study was retrieved. Five articles were selected for meta-analysis with a combined sample of 2518 subjects. Women had higher prevalence of TMD in all RDC/TMD diagnostic groups. The meta-analysis yielded the following results: (a) OR = 2.24 for global TMD (groups I, II and III combined), (b) OR = 2.09 for group I, (c) OR = 1.6 for group II and (d) OR = 2.08 for group III. The importance of gender in the development of TMD has been demonstrated, with a two times greater risk of women to develop it as compared to men.
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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 | 0.021 | 0.042 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.029 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 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".