Global scales for cognitive screening in Parkinson's disease: Critique and recommendations
Bibliographic record
Abstract
BACKGROUND: Cognitive impairment is a common nonmotor manifestation of Parkinson's disease, with deficits ranging from mild cognitive difficulties in 1 or more of the cognitive domains to severe dementia. The International Parkinson and Movement Disorder Society commissioned the assessment of the clinimetric properties of cognitive rating scales measuring global cognitive performance in PD to make recommendations regarding their use. METHODS: A systematic literature search was conducted to identify the scales used to assess global cognitive performance in PD, and the identified scales were reviewed and rated as "recommended," "recommended with caveats," "suggested," or "listed" by the panel using previously established criteria. RESULTS: A total of 12 cognitive scales were included in this review. Three scales, the Montreal Cognitive Assessment, the Mattis Dementia Rating Scale Second Edition, and the Parkinson's Disease-Cognitive Rating Scale, were classified as "recommended." Two scales were classified as "recommended with caveats": the Mini-Mental Parkinson, because of limited coverage of executive abilities, and the Scales for Outcomes in Parkinson's Disease-Cognition, which has limited data on sensitivity to change. Six other scales were classified as "suggested" and 1 scale as "listed." CONCLUSIONS: Because of the existence of "recommended" scales for assessment of global cognitive performance in PD, this task force suggests that the development of a new scale for this purpose is not needed at this time. However, global cognitive scales are not a substitute for comprehensive neuropsychological testing. © 2017 International Parkinson and Movement Disorder Society.
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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 | 0.111 | 0.279 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.012 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.012 | 0.004 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".