Clinical Validity of the Mattis Dementia Rating Scale-2 in Parkinson Disease With MCI and Dementia
Bibliographic record
Abstract
The utility of the Mattis Dementia Rating Scale 2 (MDRS-2) in screening for dementia in Parkinson disease (PD) is well documented. However, little is known about its sensitivity to mild cognitive impairment in PD (PD-MCI). This study sought to document the validity of the MDRS-2 for diagnoses of PD-MCI and dementia in PD (PDD). Twenty-two healthy controls (HCs), 22 PD-MCI, and 16 PDD were compared on each MDRS-2 subscales and MDRS-2 total standard scores. Patients with PDD performed significantly worse than the other groups (all Ps < .05) on the MDRS-2 total and on all subscales, except attention. PD-MCI had significant lower scores than HCs on the MDRS-2 total and on initiation/perseveration and memory subscales. The optimal cutoff score for PD-MCI diagnosis was ≤ 140/144 and ≤ 132/144 for PDD. These findings suggest that MDRS-2 is a useful tool to identify dementia but that there might be a ceiling effect in the MDRS-2 cutoff score to diagnose MCI in PD.
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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 | 0.001 | 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".