A case–control study on the effect of rhythmic masticatory muscle activity (<scp>RMMA</scp>) clusters on sleep fragmentation and severity of orofacial muscle pain in sleep bruxism
Bibliographic record
Abstract
Rhythmic masticatory muscle activity (RMMA) is a periodic muscle activity that characterises sleep bruxism (SB) events. These can occur as a single event, in pairs, or in clusters. Since RMMA episodes often occur in clusters and the relevance of this occurrence is unknown, we conducted a study to investigate the effect of RMMA clusters on sleep fragmentation and the severity of orofacial muscle pain. This study involved a secondary analysis using data from 184 adult subjects with orofacial muscle pain who underwent definitive polysomnography (PSG) for sleep bruxism diagnosis. Self-reported orofacial muscle pain (OFMP) was assessed using the numeric rating scale, and additional evaluation of side-to-side equivalence (symmetry) was described using a binary system. Among the 184 participants, 60.8% (n = 112) did not exhibit clusters and among the 72 participants with clusters, 36.1% (n = 26) and 63.9% (n = 46) were in the high and low RMMA frequency groups, respectively. The high SB group had significantly three times more phasic RMMA events than the noncluster group. A total of 89.67% (n = 165) of subjects reported orofacial muscle pain. While there was no difference in the severity of OFMP among groups, a significant decrease in symmetry between the severity of temporal muscle pain on the left and right sides was noted in the cluster group compared with the noncluster group. Clustering of RMMA events is associated with sleep fragmentation. The asymmetry of temporal muscle pain is related to the presence of RMMA clusters in sleep bruxism.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.028 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".