Screening for Alzheimer’s Disease with the Short Cognitive Evaluation Battery
Bibliographic record
Abstract
Because Alzheimer's disease (AD) tends to be underdiagnosed, there is an increasing need for accurate neuropsychological screening tools that are easy to administer by general practitioners or specialists. The aim of the present study was to validate, in French, a sensitive and specific screening battery designed to improve the discrimination between patients with AD, patients with depression and healthy elderly subjects. The Short Cognitive Evaluation Battery (SCEB) consists of 4 brief tests: temporal orientation, 5-word test, clock-drawing test and a semantic verbal fluency task. The SCEB was administered to 123 ambulatory subjects (mean age 76.4+/-2.3 years): 49 patients with mild AD, 27 patients with depressive symptoms and 47 healthy elderly subjects. The mean time for administration of the test was 11.2 min in the AD group, 8.2 min in the depressive group and 7.2 min in the control group (p < 0.001). Multivariate analysis showed that, compared with controls, patients with mild AD were significantly impaired for all four tests. Response operating characteristics analysis of the SCEB showed: 93.8% sensitivity and 85% specificity for discriminating AD from control patients, and 63% sensitivity and 96% specificity for discriminating AD from depressive patients. In summary, the SCEB appears to be a highly sensitive and specific tool for discriminating between patients with mild AD and healthy elderly individuals. Furthermore, in combination with clinical evaluation, the SCEB could improve the specificity of the difficult discrimination between mild AD and depression.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".