Comparison of Test Your Memory and Montreal Cognitive Assessment Measures in Parkinson’s Disease
Bibliographic record
Abstract
Background. MoCA is widely used in Parkinson's disease (PD) to assess cognition. The Test Your Memory (TYM) test is a cognitive screening tool that is self-administered. Objectives. We sought to determine (a) the optimal value of TYM to discriminate between PD patients with and without cognitive deficits on MoCA testing, (b) equivalent MoCA and TYM scores, and (c) interrater reliability in TYM testing. Methods. We assessed the discriminant ability of TYM and the equivalence between TYM and MoCA scores and measured the interrater reliability between three raters. Results. Of the 135 subjects that completed both tests, 55% had cognitive impairment according to MoCA. A MoCA score of 25 was equivalent to a TYM score of 43-44. The area under the receiver operator characteristic (ROC) curve for TYM to differentiate between PD-normal and PD-cognitive impairment was 0.82 (95% CI 0.75 to 0.89). The optimal cutoff to distinguish PD-cognitive impairment from PD-normal was ≤45 (sensitivity 90.5%, specificity 59%) thereby correctly classifying 76.3% of patients with PD-cognitive impairment. Interrater agreement was high (0.97) and TYM was completed in under 7 minutes (interquartile range 5.33 to 8.52 minutes). Conclusions. The TYM test is a useful and less resource intensive screening test for cognitive deficits in 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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".