Rhythm disturbances as a potential early marker of Parkinson’s disease in idiopathic REM sleep behavior disorder
Bibliographic record
Abstract
OBJECTIVE: We aimed to identify timing distortions in production and perception of rhythmic events in patients with idiopathic REM sleep behavior disorder (iRBD) as early markers of Parkinson's disease (PD). METHODS: Rhythmic skills, clinical characteristics, dysautonomia, depression, and olfaction were compared in 97 participants, including 21 participants with iRBD, 38 patients with PD, and 38 controls, matched for age, gender, and education level. Rhythmic disturbances can be easily detected with dedicated motor tasks via a tablet application. Rhythm production was tested in two conditions: to examine the ability to generate a spontaneous endogenous rhythm, tapping rate and variability in a finger tapping task without external stimulation was measured, while the ability to synchronize to an external rhythm was tested with finger tapping to external auditory cues. Rhythm perception was measured with a task, in which the participants had to detect a deviation from a regular rhythm. Participants with iRBD had dopamine transporter imaging. RESULTS: Participants with iRBD and PD revealed impaired spontaneous rhythm production and poor rhythm perception compared to controls. Impaired rhythm production was correlated with olfaction deficits, dysautonomia, impaired non-motor aspects of daily living, and dopamine uptake measures. CONCLUSIONS: Participants with iRBD show impaired rhythm production and perception; this impairment is correlated with other early markers for PD. Testing rhythmic skills with short and inexpensive tests may be promising for screening for potential future PD in iRBD patients.
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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 | 0.001 | 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) | 0.001 | 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".