Taking the Time to Assess Cognition in Parkinson’s Disease: The Clock Drawing Test
Bibliographic record
Abstract
BACKGROUND: Cognitive impairment is common and disabling in Parkinson's disease (PD). Cognitive testing can be time consuming in the clinical setting. One rapid test to detect cognitive impairment in non-PD populations is the Clock Drawing Test (CDT), which calls upon the brain's executive and visuospatial abilities to draw a clock designating a certain time. OBJECTIVE: Test the hypothesis that PD participants would perform worse on CDT compared to controls and that CDT would correlate with other measures of cognition. METHODS: This study evaluated two independent CDT scoring systems and differences in CDT performance between PD (N = 97) and control (N = 54) participants using a two-sample t-test. Pearson's correlations were conducted between the CDT and tests of sleepiness (Epworth Sleepiness Scale) and vigilance (Psychomotor Vigilance Test); executive function (Trails B-A); and global cognition (Montreal Cognitive Assessment). Receiver operating characteristic curves were used to determine cut points on the CDT that identify individuals who need additional cognitive testing. RESULTS: PD participants had worse performance on CDT compared to controls. The CDT was correlated with executive function (Trails B-A) and global cognition (Montreal Cognitive Assessment). The CDT correlated with vigilance (Psychomotor Vigilance Task) only in healthy controls. However, the CDT was not correlated with measures of sleepiness (Epworth Sleepiness Scale) in either group. A cut point of 9 on the Rouleau scale and 18 on the Mendez scale identified PD participants with cognitive impairment. CONCLUSION: The CDT is a rapid clinical cognitive assessment that is feasible in PD and correlates with other measures of cognition.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".