Staging Alzheimer's disease using the Functional Assessment Screening Tool (FAST): a crosswalk with the Montreal Cognitive Assessment (MoCA)
Bibliographic record
Abstract
BACKGROUND: The Functional Assessment Screening Tool (FAST) evaluates functional changes over the course of Alzheimer's disease. This study aimed to evaluate the extent to which FAST scores correspond to cognitive disease staging by the Montreal Cognitive Assessment (MoCA) test. METHOD: Paired MoCA and FAST scores were analyzed in patients with mild cognitive impairment (MCI) or Alzheimer's dementia (AD) in the Veteran's Affairs Healthcare System (2020-2024). FAST score stage cut-off means, standard deviations (SD), medians, and ranges were generated. Linear and repeated measures mixed effects analysis was performed adjusting for patient demographics. RESULT: The study sample (N = 405) had a mean age of 77.9 years (95.6% men, 11.1% Black, and 6.2% 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 FAST score cut-offs separating disease stages were: normal (n = 1), 2.0 and 2; MCI (n = 21), 3.3 (1.7) and 3; mild (n = 206), 3.8 (1.5) and 4; moderate (n = 118), 4.8 (1.4) and 5; severe (n = 59), 5.8 (1.0) and 6. FAST tests resulted in score ranges of 1-7 for MCI-moderate stages and 4-7 for severe AD. Of note, more than half the patients (n = 205) scored in the normal/preclinical ranges of FAST (1 or 2); while, only 1 patient scored normal on the MoCA. FAST linear least squares (LS) means were distributed as <3.6, 3.6-<4.0, 4.0-<5.1, 5.1-6.0, >6 for normal, MCI, mild, moderate, and severe stages projected by MoCA cut-offs, respectively (adjusted R-squared=0.25). The LS means from categorical regression were 2.8, 4.2, 4.5, 5.5, and 6.5, normal, MCI, mild, moderate, and severe stages, respectively (adjusted R-squared=0.24). Similarly, LS means from repeated measures analysis found FAST score ranges for normal to severe AD were <3.9, 3.9-<4.2, 4.2-<5.1, 5.1-5.9, and >5.9. CONCLUSION: This study identified FAST score thresholds corresponding to clinical stages from normal to severe AD according to a regressional crosswalk with MoCA. FAST provides a global functional assessment; however, our data suggest that it may underestimate disease severity relative to MoCA. Nonetheless, FAST is widely used in clinical practice, providing an alternative clinical tool for staging disease progression.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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) | 0.004 | 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".