Screening for Impaired Cognitive Domains in a Large Parkinson's Disease Population and Its Application to the Diagnostic Procedure for Parkinson's Disease Dementia
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Dementia is a new focus of research on improved treatment for Parkinson's disease (PD). In 2007, a screening tool for PD dementia (PD-D) was developed by the Movement Disorder Society (Level I testing), which still requires verification by a large population study. METHODS: We conducted a cross-sectional and multicenter study including 13 institutions administering the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) to 304 PD patients (mean age: 70.6 ± 8.3 years; mean Hoehn and Yahr stage: 2.7 ± 0.7). RESULTS: In all, 34.5% of the patients had MMSE scores <26; 94.3% of these patients had impairments in ≥2 cognitive domains and met the criteria for probable PD-D by Level I testing. Executive dysfunction combined with attention and memory impairment was most common (51.4%). In the Level I subtests of executive function, the score for phonemic fluency declined by <50% in patients with high MoCA scores (24-30 points) and lacked specificity for PD-D. No patient had visuospatial impairment (measured by the pentagon copying subtest) alone, and the score for pentagon copying stayed at ≥70% even in patients with low MMSE scores (12-25 points), therefore lacking sensitivity for PD-D. CONCLUSIONS: Level I testing with administration of the MMSE and MoCA is a practical and efficient screening tool for PD-D. However, the phonemic fluency and pentagon copying tests should be replaced by more specific/sensitive ones when screening for PD-D.
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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 | 0.000 | 0.001 |
| 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 it