Could transient hypoxia be associated with rhythmic masticatory muscle activity in sleep bruxism in the absence of sleep‐disordered breathing? A preliminary report
Bibliographic record
Abstract
Sleep bruxism (SB) is a repetitive jaw-muscle activity characterised by clenching or grinding of the teeth during sleep. Sleep bruxism activity is characterised by rhythmic masticatory muscle activity (RMMA). Many but not all RMMA episodes are associated with sleep arousal. The aim of this study was to evaluate whether transient oxygen saturation level change can be temporally associated with genesis of RMMA/SB. Sleep laboratory or home recordings data from 22 SB (tooth grinding history in the absence of reported sleep-disordered breathing) and healthy subjects were analysed. A total of 143 RMMA/SB episodes were classified in four categories: (i) no arousal + no body movement; (ii) arousal + no body movement; (iii) no arousal + body movement; (iv) arousal + body movement. Blood oxygen levels (SaO2 ) were assessed from finger oximetry signal at the baseline (before RMMA), and during RMMA. Significant variation in SaO2 over time (P = 0·001) was found after RMMA onset (+7 to +9 s). No difference between categories (P = 0·91) and no interaction between categories and SaO2 variation over time (P = 0·10) were observed. SaO2 of six of 22 subjects (27%) remained equal or slight increase after the RMMA/SB onset (+8 s) compared to baseline; 10 subjects (45%) slightly decreased (drop 0·01-1%) and the remaining (27%) decreased between 1% and 2%. These preliminary findings suggest that a subgroup of SB subjects had (i) a minor transient hypoxia potentially associated with the onset of RMMA episodes, and this (ii) independently of concomitant sleep arousal or body movements.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".