Dream Content Predicts Motor and Cognitive Decline in Parkinson's Disease
Why this work is in the frame
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Bibliographic record
Abstract
ABSTRACT Background Dream content alterations in Parkinson's disease (PD) are associated with motor and cognitive dysfunction cross‐sectionally. Although recent studies suggest abnormal dream content in PD might also predict cognitive decline, the relationship between dream content and motor decline in PD remains unknown. Objective To investigate whether abnormal dream content in PD predicts both motor and cognitive decline. Methods Data were obtained from the Parkinson's Progression Markers Initiative cohort study. Patients were evaluated at baseline and at the 60‐month follow‐up, with validated clinical scales, including the REM Sleep Behavior Disorder Screening Questionnaire (RBDSQ), Montreal Cognitive Assessment (MoCA), and the Movement Disorder Society–Unified Parkinson's Disease Rating Scale Part III (MDS‐UPDRS III). Patients were dichotomized using RBDSQ item 2, which inquires whether they frequently experience aggression in their dreams. Regression analyses were used to assess whether frequent aggressive dreams at baseline predicted longitudinal changes in MDS‐UPDRS III and MoCA scores as well as progression to Hoehn and Yahr stage 3 (H&Y ≥ 3) and cognitive impairment. Results Of the patients, 58/224 (25.9%) reported frequent aggressive dreams at baseline. Aggressive dreams predicted a faster increase in MDS‐UPDRS III scores (β = 4.64; P = 0.007) and a faster decrease in MoCA scores (β = −1.49; P = 0.001). Furthermore, they conferred a 6‐fold and 2‐fold risk for progressing to H&Y ≥ 3 (odds ratio [OR] = 5.82; P = 0.005) and cognitive impairment (OR, 2.35; P = 0.023) within 60 months. These associations remained robust when adjusting for potential confounders. Conclusions This study demonstrates for the first time that frequent aggressive dreams in newly diagnosed PD may independently predict early motor and cognitive decline.
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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 | 0.001 | 0.072 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it