How does dementia with Lewy bodies start? prodromal cognitive changes in REM sleep behavior disorder
Bibliographic record
Abstract
OBJECTIVE: We describe the progression of cognitive decline and identify the predictive values of cognitive tests in three groups of REM sleep behavior disorder (RBD) patients classified at their last follow-up as having Parkinson's disease (PD), dementia with Lewy bodies (DLB), or still-idiopathic. METHODS: Patients (n = 109) underwent polysomnographic, neurological, and neuropsychological assessments. We used linear mixed-model analyses to compare the progression of cognitive test performance between the three groups over a 3-year prodromal period, and performed linear regressions for a 6-year prodromal period. We compared the proportions of patients with clinically impaired performance (z scores < -1.5). DLB patients were pair-matched according to age, sex, and education to healthy controls (2:1 ratio), and receiver operating characteristic curves were performed to identify the psychometric properties of cognitive tests to predict dementia. RESULTS: At follow-up, 38 patients (35%) developed a neurodegenerative disorder: 20 had PD and 18 DLB. Cognitive performance changes over time were strongly associated with later development of dementia. Clear deficits in attention and executive functions were observed 6 years before diagnosis. Verbal episodic learning and memory deficits started later, deviating from normal approximately 5 to 6 years and becoming clinically impaired at 1 to 2 years before diagnosis. Visuospatial abilities progressed variably, with inconsistent prodromal latencies. The Trail Making Test (part B), Verbal Fluency (semantic), and Rey Auditory-Verbal Learning Test (total, immediate, and delayed recalls) were the best predictors for dementia (area under the curve = 0.90-0.97). INTERPRETATION: Prodromal DLB is detectible up to 6 years before onset. For clinical utility, the Trail Making Test (part B) best detects early prodromal dementia stages, whereas Verbal Fluency (semantic) and verbal episodic learning tests are best for monitoring changes over time. Ann Neurol 2018;83:1016-1026.
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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 | 0.000 | 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 | 0.000 |
| 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".