Detecting the Cognitive Prodrome of Dementia with Lewy Bodies: A Prospective Study of REM Sleep Behavior Disorder
Bibliographic record
Abstract
Study Objectives: Long-term studies in REM sleep behavior disorder (RBD) have shown a high rate of conversion into synucleinopathies. We aimed to prospectively follow-up a large cohort of RBD patients to identify cognitive markers for early detection of prodromal dementia. Methods: Seventy-six idiopathic RBD patients underwent polysomnography and a complete neuropsychological and neurological assessment and were then followed for a mean of 3.6 years. Cognitive characteristics at baseline were compared between patients who remained disease-free and those who developed a synucleinopathy, and between those who developed dementia first and those who developed parkinsonism first. Receiver operating characteristic curves were calculated to assess the diagnostic value of cognitive tests for detecting prodromal dementia. Results: At follow-up, 34 patients developed a neurodegenerative disease: 19 parkinsonism-first and 15 dementia-first. RBD patients who first developed dementia were impaired at baseline in all cognitive domains (attention/executive functions, learning/memory, and visuospatial) compared to patients who developed parkinsonism. Moreover, 93% of patients who first developed dementia had mild cognitive impairment at baseline compared to 42% of patients who developed parkinsonism. RBD patients who developed parkinsonism first were similar at baseline to disease-free RBD patients on cognition. In dementia-first patients, two cognitive tests assessing attention and executive functions (Stroop Color Word Test and Trail Making Test) reliably predicted dementia (area under the curve ≥0.85) compared to parkinsonism-first patients or controls. Conclusions: This study shows that cognitive tests assessing attention and executive functions strongly predict conversion to dementia in RBD patients, and may be useful endpoints to determine the effectiveness of interventions to prevent cognitive deterioration in RBD 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".