0652 Interim Analysis from the REM Sleep Behavior Disorder Associations with Parkinson’s Disease Study (RAPiDS)
Bibliographic record
Abstract
Rapid eye movement sleep behavior disorder (RBD) is a significant risk factor for alpha-synucleinopathies, including Parkinson’s disease (PD); however, there exists no means of predicting prognosis, and a paucity of data regarding further workup. We present an interim cross-sectional analysis of the longitudinal REM Behavior Disorder Associations with Parkinson’s Disease Study (RAPiDS) database and biorepository, which is a protocol to enroll and track 100 patients with RBD and REM sleep without atonia (RSWA). Participants with RBD or RSWA were prospectively recruited from the Weill Cornell Center for Sleep Medicine. Those with a diagnosed neurodegenerative disorder were excluded. Evaluations comprised polysomnography, medical history, and standardized rating scales and examination focused on neurologic, psychiatric, and autonomic function, including a validated test for hyposmia/dysosmia, the University of Pennsylvania Smell Identification Test (UPSIT), that is associated with, but not specific for, pre-motor PD. We evaluated 30 participants with RBD and 3 with RSWA, with mean 2.36±2.0 years since diagnosis. Mean age was 58.2±16.4 years, and 9/33 were women; 36% reported a history of psychiatric illness; 24% were currently taking, and 27% reported ever taking antidepressant medication. Urinary dysfunction was present in 23%, constipation in 23%, and 12/31 (39%) had abnormal Montreal Cognitive Assessment scores. Additionally, UPSIT scores were significantly associated with presence of constipation and urinary dysfunction in these subjects, as well as with slowed gait, impaired balance, and tremor. Despite excluding patients with neurodegenerative disorders, we detected an unexpectedly high incidence of additional symptoms and signs, prompting the proposed term “RBD-plus”. Our RAPiDS cohort is a step in determining what clinical factors should be evaluated further in RBD patients; screening for potential early indicators of alpha-synucleinopathy would not only improve care for RBD patients, but could eventually facilitate inclusion in trials focused on disease prevention or in slowing progression. While it is too early to detect what exactly is implicated in the conversion to alpha-synucleinopathy, our cohort will allow for improved understanding and characterization of which patients are at risk. Private grant.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.005 |
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".