0727 TONIC AND PHASIC CHIN EMG DENSITY IN IDIOPATHIC REM SLEEP BEHAVIOR DISORDER
Bibliographic record
Abstract
In 2010, our group published a scoring method for REM sleep phasic and tonic EMG activity in REM sleep behavior disorder (RBD). Cut-off values were reported in a large population of RBD and healthy subjects, but this method was based on 20 sec epochs which limits it current used as a diagnostic tool. The aims of the present study were to confirm results of the previous study in a different RBD cohort using 30 sec epochs, to assess the sensitivity and specificity of cut-off values for tonic and phasic values to diagnose RBD (taken separately or combined), to correlate tonic and phasic values with clinical markers of neurodegeneration, and to look at changes of REM sleep EMG abnormalities over times. Fifty-nine patients with a clinical diagnosis of idiopathic RBD and 50 age- and gender-matched healthy subjects were studied in our sleep laboratory. Tonic and phasic EMG activity were recorded and scored according to our method described previously using 30 sec epochs. Receiver operating curves were drawn to find optimal cut-off values for REM sleep EMG parameters. Clinical markers of neurodegeneration were also studied and a subgroup of patients was recorded again after 12 months. Total correct classification of 89% was found for tonic or phasic chin EMG density ≥15%. This correct classification score increased to 97% when both criteria were applied. A significant positive correlation (r=0.321) was found between tonic EMG and UPDRSIII. Recordings performed after 12 months showed a significant increase of 20% of tonic EMG density. This study confirms the value of a scoring method based on chin EMG and establishes cut-off values to be used for the diagnosis of RBD. Results further document the status of tonic and not phasic REM density as a marker of ongoing neurodegeneration and disease progression. Canadian Institutes of Health Research (CIHR) and by the W Garfield Weston Foundation.
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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 | 0.001 | 0.000 |
| 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 | 0.001 |
| 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".