Bruxism: An umbrella review of systematic reviews
Bibliographic record
Abstract
OBJECTIVES: To synthesise available knowledge about both sleep (SB) and awake bruxism (AB) as depicted by previous published systematic reviews (SR). METHODS: SR investigating any bruxism-related outcome were selected in a two-phase process. Searches were performed on seven main electronic databases and a partial grey literature search on three databases. Risk of bias of included SR was assessed using the "University of Bristol's tool for assessing risk of bias in SR". RESULTS: From 1038 studies, 41 SR were included. Findings from these SR suggested that (a) among adults, prevalence of AB was 22%-30%, SB (1%-15%), and SB among children and adolescents (3%-49%); (b) factors consistently associated with bruxism were use of alcohol, caffeine, tobacco, some psychotropic medications, oesophageal acidification and second-hand smoke; temporomandibular disorder signs and symptoms presented a plausible association; (c) portable diagnostic devices showed overall higher values of specificity (0.83-1.00) and sensitivity (0.40-1.00); (d) bruxism might result in biomechanical complications regarding dental implants; however, evidence was inconclusive regarding other dental restorations and periodontal impact; (e) occlusal appliances were considered effective for bruxism management, although current evidence was considered weak regarding other therapies. CONCLUSIONS: Current knowledge from SR was mostly related to SB. Higher prevalence rates were found in children and adolescents than in adults. Associated factors and bruxism effects on stomatognathic structures were considerably heterogeneous and inconsistent. Overall good accuracy regarding portable diagnostic devices was found. Interventions' effectiveness was mostly inconclusive regarding the majority of available therapies, with the exception of occlusal appliances.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.064 | 0.200 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.009 |
| Bibliometrics | 0.047 | 0.038 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".