A recommended scale for cognitive screening in clinical trials of Parkinson's disease
Bibliographic record
Abstract
Cognitive impairment is common in Parkinson's disease (PD). There is a critical need for a brief, standard cognitive screening measure for use in PD trials whose primary focus is not on cognition. The Parkinson Study Group (PSG) Cognitive/Psychiatric Working Group formed a Task Force to make recommendations for a cognitive scale that could screen for dementia and mild cognitive impairment in clinical trials of PD where cognition is not the primary outcome. This Task Force conducted a systematic literature search for cognitive assessments previously used in a PD population. Scales were then evaluated for their appropriateness to screen for cognitive deficits in clinical trials, including brief administration time (<15 minutes), assessment of the major cognitive domains, and potential to detect subtle cognitive impairment in PD. Five scales of global cognition met the predetermined screening criteria and were considered for review. Based on the Task Force's evaluation criteria the Montreal Cognitive Assessment (MoCA), appeared to be the most suitable measure. This Task Force recommends consideration of the MoCA as a minimum cognitive screening measure in clinical trials of PD where cognitive performance is not the primary outcome measure. The MoCA still requires further study of its diagnostic utility in PD populations but appears to be the most appropriate measure among the currently available brief cognitive assessments. Widespread adoption of a single instrument such as the MoCA in clinical trials can improve comparability between research studies on PD.
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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 | 0.334 | 0.481 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.015 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.011 | 0.011 |
| Insufficient payload (model declined to judge) | 0.013 | 0.007 |
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".