0722 NEURODEGENERATIVE BIOMARKER FREQUENCY IN IDIOPATHIC REM SLEEP BEHAVIOR DISORDER
Bibliographic record
Abstract
The majority of patients with idiopathic REM sleep behavior disorder (iRBD) are thought to have prodromal synucleinopathy. 25–60% of iRBD patients have probable neurodegenerative biomarkers such as olfactory, orthostatic blood pressure, cognitive, or motor function impairments. We aimed to describe frequencies of neurodegenerative biomarkers in the Mayo Clinic iRBD prospective registry cohort. We included adults diagnosed with iRBD by ICSD-3 criteria, and excluded symptomatic RBD patients (i.e., diagnosis of mild cognitive impairment, dementia with Lewy bodies, Parkinson disease, or multiple system atrophy). We considered clinical neurodegenerative biomarker measures as abnormal when subjects met age-gender defined cut-offs for the brief Smell Identification Test (BSIT) and neurocognitive assessments (Montreal Cognitive Assessment (MOCA), “Kokmen” Short Test of Mental Status (STMS) and King-Devick Test (KDT)), orthostatic systolic blood pressure (SBP) drop >10 mm Hg, or timed up and go (TUG) speed > 7.5 seconds. 38 iRBD subjects participated. Mean age was 65.4 (range 21 - 84) years, and 12 (31%) were women. Duration of dream enactment was 11+/-16 years. 18 (47%) were receiving antidepressant medications. Mean (range) measure scores were: BSIT 8.8 (4–12); MOCA, 26.2 (20–30); STMS, 34.3 (30–38); KD, 60.2 (39–125.6); SBP drop, 14.64 (1–49); and TUG, 8.5 (5.3–13.8) seconds. The number (%) with abnormal biomarker measures were: BSIT, 6 (16%); MoCA, 6 (16%); STMS, 0%; KD, 12 (32%); SBP drop, 15 (41%); and TUG, 11 (31%). Overall, 31 (82%) had one or more clinical neurodegenerative biomarkers at baseline, and 20 (52%) had two or more biomarkers at baseline. Antidepressant medication was not associated with abnormality on any of the measures. 82% of iRBD patients had at least one neurodegenerative biomarker present, suggesting that iRBD is a prodromal synucleinopathy. Further longitudinal analyses of this cohort compared to age-gender matched control subjects is planned. Mayo Clinic CCaTS.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".