Is catechol‐O‐methyltransferase gene associated with temporomandibular disorders? A systematic review and meta‐analysis
Bibliographic record
Abstract
BACKGROUND: Temporomandibular disorder (TMD) is a condition, in which multiple factors act synergistically to determine the outcome of the disorder. AIM: A systematic review and meta-analysis was conducted to evaluate the association between genetic polymorphisms in catechol-O-methyltransferase (COMT) and TMD. DESIGN: Observational studies that investigated this association were included. The risk of bias and study quality were evaluated according to the Newcastle-Ottawa tool. The meta-analysis was performed for each polymorphism associated with TMD signs and symptoms. RESULTS: A total of 1903 articles were identified. Ten remained in the qualitative analysis: six were classified as low risk of bias and four with moderate risk of bias, and three were included in the meta-analysis. The polymorphism rs6269, in the genotypic model (0.65; CI = 0.44-0.97; P = .04) and in the allelic model (0.73; CI = 0.54-0.98; P = .04), was associated with myofascial pain. The rs9332377 was associated with myofascial pain in the genotypic model (2.69; CI = 1.51-4.76; P = .0007) and in the allelic model (1.46; CI = 1.01-2.13; P = .05) and with painful TMD in the genotypic model (2.08; CI = 1.27-3.40; P = .004) and in the allelic model (1.34 CI = 0.98-1.82; P = .06). CONCLUSION: The polymorphisms in COMT were significantly associated with TMD.
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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 | 0.011 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.035 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".