Alzheimer's disease staging by instrumental activities of daily living (IADL): a crosswalk with the Montreal Cognitive Assessment (MoCA)
Bibliographic record
Abstract
BACKGROUND: Alzheimer's disease progression is typically staged using cognitive tests. This study aimed to define clinical stages measured by Instrumental Activities of Daily Living (IADL) using a crosswalk with Montreal Cognitive Assessment (MoCA) scores. METHOD: Patients with mild cognitive impairment (MCI) or Alzheimer's dementia (AD) were identified from the Veteran's Affairs Healthcare System (VAHS) database from 2020 - 2024. Paired MoCA and Lawton-Brody IADL scores were analyzed to generate IADL score means, standard deviations (SD), medians, and ranges. Linear and repeated measures mixed effects analysis was performed adjusting for patient demographics. RESULT: The study sample (N = 1,327) had a mean age of 80.1 years (97.4% men, 18.4% Black, and 12.0% Hispanic). MoCA cut-offs for Normal, MCI, Mild, Moderate, and Severe AD stages were ≥29, 26,18, 11 and ≤10, respectively. Corresponding mean (SD) and median IADL score cutoffs separating disease stages were: normal (n = 14), 7.0 (1.8) and 8; MCI (n = 96), 6.4 (2.3) and 8; mild (n = 666) 5.9 (2.5) and 7; moderate (n = 393) 4.0 (2.9) and 3; severe (n = 158), 2.4 (2.6) and 1. IADL tests resulted in ranges of 3-8 for normal, 1-8 for MCI, and 0-8 for other stages. The IADL linear least squares (LS) means were distributed as >7.6, 6.9-7.6, 5.1-6.9, 3.5-5.1, <3.5 for normal, MCI, mild, moderate, and severe stages projected by MoCA cutoffs, respectively (adjusted R-squared=0.25). The LS means from categorical regression were 7, 6.5, 6.0, 4.2, and 2.6 for normal, MCI, mild, moderate and severe stages, respectively (adjusted R-squared=0.23). Similarly, LS means from repeated measures analysis found IADL score ranges for normal to severe AD were >7.3, 6.7-7.3, 5.1-6.7, 3.6-5.1, and <3.6. CONCLUSION: This study identified IADL score thresholds corresponding to clinical stages from normal to severe AD according to a regressional crosswalk with MoCA. The findings from categorial regression allowed greater spread of the IADL cut-offs from mild to severe AD stages compared to linear and repeated measures regressions, accommodating nonlinearity in the cut-off score distribution.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".