A case–control study of temporomandibular disorders: symptomatic disc displacement
Bibliographic record
Abstract
This case-control study was designed to investigate the risk factors for disc displacement (DD) without myofascial pain (MFP). The study population included 59 cases with DD without MFP, selected in two hospital dental clinics, and 100 concurrent controls selected in one of these clinics. The association with DD was evaluated for bruxism, head-neck trauma, orthodontic treatment, and sociodemographic characteristics by using unconditional logistic regression. In the multivariate analysis, excluding psychological factors, an association was found between DD and clenching-grinding (OR=3.57; 95% CI: 1.27-9.98). This association persisted when anxiety (OR=3.07; 95% CI: 1.08-8.70) or depression (OR=4.02; 95% CI: 1.43-11.31) was included in the model. A positive association was noted between orthodontic treatment and DD (OR=3.10; 95% CI: 1.06-9.65). The effect between orthodontic treatment and DD remained and increased with the inclusion of anxiety (OR=3.65; 95% CI: 1.15-11.61) or depression (OR=3.20; 95% CI: 1.06-9.65). A high level of anxiety (OR=2.40; 95% CI: 1.01-5.73), was positively related to DD. We concluded that clenching combined with grinding, and orthodontic treatment are factors related to DD. The interpretation of these associations, however, requires caution because of the inclusion of prevalent cases.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".