Evidence of the Sensitivity of the MoCA Alternate Forms in Monitoring Cognitive Change in Early Alzheimer's Disease
Bibliographic record
Abstract
BACKGROUND/AIMS: There is an increasing interest in using the Montreal Cognitive Assessment (MoCA) test as a monitoring tool in Alzheimer's disease (AD) in both research and clinical settings. Our aim was to investigate the utility of alternate forms of the MoCA in detecting cognitive deterioration in a sample of early AD patients followed longitudinally in an outpatient memory clinic. METHOD: Twenty-five patients with early-stage AD (prodromal or mild dementia) were administered the original version and one of two previously validated alternate forms of the MoCA within an interval of about 1 year. The decline over time and the rate of change of the MoCA were compared to the total score of a standardized neuropsychological assessment battery (Consortium to Establish a Registry of Alzheimer's Disease; CERAD-Plus). Responsiveness to change was determined by calculating standard response means and the respective effect sizes. RESULTS: Sixty percent of the sample showed a clinical decline on the clinical dementia rating (CDR) scale. There was significant deterioration in the MoCA and CERAD total scores. CONCLUSION: The results demonstrate that the MoCA is capable of detecting change over time and seems to be a valid tool with small to moderate sensitivity for monitoring cognitive change in early AD.
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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 | 0.035 | 0.100 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".