P2‐092: Comparisons of trajectories of mmse and MoCA scores in frontotemporal dementia and Alzheimer's disease
Bibliographic record
Abstract
The Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) are widely used for tracking cognitive dysfunction in dementias, such as frontotemporal dementia (FTD) and Alzheimer's dementia (AD). Quantitative comparisons of the time-related trajectories of the two tests have not been done; such comparisons are the objective of this study. All behavioral variant FTD (bvFTD, n=21) and AD (n=39) patients first seen in the Young-Onset Dementia Clinic of Johns Hopkins University until April 2013 were included in the study. Illness duration was dichotomized into early (≤ 4 years) and late (> 4 years). Linear mixed effects regression was used to model: 1) the interaction between test type (MMSE vs. MoCA) and test scores in bvFTD (and AD) in early and late disease; 2) the interaction between diagnosis (bvFTD vs. AD) and test scores in early and late disease. In each model, random effects were allowed for the intercept and the coefficient associated with illness duration, but not for the interaction between illness duration and the test type (or diagnosis in model 2). MoCA was associated with a sharp rate of decline than MMSE in early stage bvFTD, and gradual decline in late stage (.05 < p < .10). In AD, MoCA and MMSE slopes did not differ in early disease. However, in late AD, MoCA scores had a gentler slope than MMSE scores accompanied by a smaller intercept (p < .05), indicating earlier floor effects. There were no differences between bvFTD and AD in the MMSE trajectory. MoCA scores in late AD were steeper than those in late bvFTD. The intercept was smaller for bvFTD in this model, although this was not significant. We did not have sufficient data to compare MoCA scores in early AD and bvFTD. the MoCA may be more sensitive to change than the MMSE in early bvFTD. In late AD, the MMSE may have more utility than the MoCA – owing to floor effects in the latter. MoCA was less sensitive to time-related change in late bvFTD than in late AD, and showed less utility for tracking cognitive decline.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.004 | 0.001 |
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".