Sleep and awake bruxism in adults and its relationship with temporomandibular disorders: A systematic review from 2003 to 2014
Bibliographic record
Abstract
OBJECTIVE: In order to establish a relationship between bruxism and temporomandibular disorders (TMDs), a systematic review was performed. MATERIALS AND METHODS: A systematic research was performed based on PubMed, Cochrane Library, Medline, Embase, BIREME, Lilacs and Scielo data bases, between 2003 and 2014 including all languages. Descriptive clinical cases were identified. Two independent authors selected the articles. PICO format was used to analyse the studies and the Newcastle-Ottawa Scale (NOS) was used to verify the quality of the evidence. RESULTS: Thirty-nine studies (n = 39) were analysed in this review. According to bruxism diagnosis, articles were grouped as follows: polysomnographic diagnosis (PSG) (n = 7), clinical diagnosis (n = 11) and survey/self-report (n = 21). Thirty-three articles (n = 33) established a positive relation between bruxism and TMD and six (n = 6) did not. Quality of evidence was low to moderate. In general, the most part of the studies showed shortcomings on their design with bias risk, and also had a low sensitivity on bruxism diagnosis. CONCLUSIONS: The evidence based on PSG was not as conclusive as the studies that used surveys and clinical exam to diagnosis bruxism, when bruxism was related to TMD. Sleep bruxism could be associated with myofascial pain, arthralgia and joint pathology as disc displacement and joint noises. Although the evidence at present is inconclusive and does not provide information according to the type of bruxism (bruxism sleep and wakefulness), it is possible to suggest that bruxism would be 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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".