P2‐299: Brief Neuropsychological Screening Tests for the Detection of Alzheimer's Disease in an Early Phase: A Systematic Review
Bibliographic record
Abstract
Short neuropsychological screening tests form an important and often first step in the process of identifying individuals suffering from cognitive decline. Although plentiful in number, it is still unclear which screening tests are intended to be used for the early detection of Alzheimer's disease (AD) and the quality of the tests are often unclear. The objective of this study was therefore (1) to give an overview of the available short screening tests for the early detection of AD and (2) to review the psychometric properties of these tests. First, a systematic search of titles and/or abstracts of PubMed and Web of Science was conducted. All full-text articles about cognitive screening instruments for the early detection of AD written in English or Dutch were included, resulting in the identification of 30 pen-and-paper tests and 15 computer tests. In a second step the psychometric quality of these instruments was evaluated. Therefore, a search on each individual test was done in the same databases. Thereafter, the sensitivity, specificity, and area under the curve values for the detection of mild cognitive impairment and AD were listed together with the inter-rater and test-retest reliability of each individual test. Out of 1033 papers, 89 were selected that clearly discussed the psychometric properties of the tests. 75 papers discussed pen-and-paper tests of which 67 were validated in a memory clinic setting. Based on the amount of studies (30 papers) and the sensitivity (84%) and specificity (74%) values, the Montreal Cognitive Assessment is a promising screening test for memory clinic testing as well as for population screening. For computer tests, validation studies were only available for 6 out of 15 tests. There are a large number of available screening tests for AD. However, most tests are only validated in a memory clinic setting and research focusing on the psychometric properties of the instruments is limited. Especially computer tests need further research.
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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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.009 |
| Bibliometrics | 0.017 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".