Differentiating among stages of cognitive impairment: Comparisons of versions two and three of the National Alzheimer’s Coordinating Center (NACC) Uniform Data Set (UDS) neuropsychological test battery
Bibliographic record
Abstract
Abstract Background National Institute on Aging (NIA)‐funded Alzheimer’s Disease Centers in the United States have been using a standardized neuropsychological test battery as part of the National Alzheimer’s Coordinating Center (NACC) Uniform Data Set (UDS) since 2005. Version 3 (V3) of the UDS was implemented in 2015 and included several changes to its neuropsychological battery, replacing the previous version [Version 2 (V2)]. The current study compares the V3 and V2 neuropsychological batteries with respect to their ability to distinguish among categories of cognitive impairment captured by the Clinical Dementia Rating (CDR) global scores representing either no cognitive impairment (CDR=0), questionable or mild cognitive impairment (CDR=0.5) or mild stage of dementia (CDR=1.0). Method Data from the NACC UDS V2 and V3 neuropsychological batteries were examined. There were 16,935 unique subjects from V2 and 5022 unique subjects from V3 aged 60 years and older with CDR global score ≤ 1. To reduce the influence of practice effects, only data from their first assessment was used. To control for inequalities in sample sizes between V2 and V3, we identified an approximately equal number of subjects from V2 within each CDR group. Receiver Operating Characteristics Area under Curve (ROC‐AUC) in differentiating stages of cognitive impairment were compared and optimal cut‐points based on Youden’s J scores were calculated. Result ROC‐AUCs from all of the V3 neuropsychological tests were comparable in their ability to differentiate CDR global scores with the corresponding tests in V2, despite the fact that V3 participants included more subjects at earlier stage of CDR 0.5. UDS V3 composite scores yielded similar ROC‐AUCs to the best performing individual test within each domain, while the Montreal Cognitive Assessment (MoCA) total score yielded higher ROC‐AUCs than any individual MoCA index scores. Racial differences in differentiating between CDR=0 and CDR=0.5 were also found. Conclusion A nonproprietary suite of neuropsychological tests in UDS V3 provided similar discriminative ability to tests in UDS V2 to distinguish categories of cognitive impairment. Optimal cut‐points calculated in this study will be useful for clinical diagnosis.
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".