Association between painful temporomandibular disorders and sleep quality: A systematic review
Bibliographic record
Abstract
This review aimed to systematically evaluate the association between painful temporomandibular disorders (TMD) and sleep quality in adults. Observational case-control studies using either RDC/TMD or DC/TMD for TMD diagnostic and validated questionnaires for sleep quality were selected by two reviewers in a two-phase process. A systematic review was conducted in accordance with the PRISMA statement. The search was performed in PubMed/MEDLINE, LILACS, SCOPUS, PsycINFO, Web of Science and Grey literature (ProQuest, Google Scholar and OpenGrey). To be eligible, studies had to include adults (>18 years old), with no language, gender or time of publication restrictions. The quality of the papers was assessed using the Newcastle-Ottawa Scale (NOS). Eight case-control studies were included, with high (4) and moderate (4) quality assessment. Seven studies reported a significant association between the presence of painful TMD and sleep quality (P < .05), while the other found impaired sleep in participants with higher sensitivity to heat pain (P < .001). When pain levels were concerned, using different pain scales, six studies found differences when compared to control groups. One study showed that in non-painful TMD, the PSQI values were not different when compared to the control group. An association exists between painful TMD and sleep quality. The presence of pain seems to strongly impact the sleep quality in TMD patients.
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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 | 0.008 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".