Utility of the NeuroTrax Computerized Battery for Cognitive Screening in Parkinson's Disease: Comparison with the MMSE and the MoCA
Bibliographic record
Abstract
To determine the utility of a computerized assessment in Parkinson's disease (PD), we compared the cognitive performance of 50 PD patients on the NeuroTrax computerized battery relative to the mini-mental state examination (MMSE) and the Montreal Cognitive Assessment (MoCA). The results revealed fair agreement between impairment on the NeuroTrax and the MMSE (kappa=.291, p=.031) but only slight agreement between the NeuroTrax and the MoCA (kappa=.138, p = .054) and between the MoCA and the MMSE (kappa = .168, p = .069). The NeuroTrax identified 52% of the sample as average or above, 40% as below average, and 8% as impaired. The MoCA identified 54% of the sample as impaired (28% average or above and 18% below average), while the MMSE identified 66% as average or above (20% below average and 14% impaired). Several stepwise regressions revealed that executive and verbal functions were the best predictors of cognitive functioning on the NeuroTrax, while memory recall, serial sevens, naming, and abstraction were the best predictors on the MoCA. These results suggest that although the NeuroTrax may be useful in identifying executive cognitive deficits in PD, similar to the MMSE the NeuroTrax may lack optimal sensitivity. While the MoCA is sensitive, it may be too stringent in overclassifying PD patients as impaired.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".