Can clock drawing differentiate Alzheimer's disease from other dementias?
Bibliographic record
Abstract
BACKGROUND: Studies have shown the clock-drawing test (CDT) to be a useful screening test that differentiates between normal, elderly populations, and those diagnosed with dementia. However, the results of studies which have looked at the utility of the CDT to help differentiate Alzheimer's disease (AD) from other dementias have been conflicting. The purpose of this study was to explore the utility of the CDT in discriminating between patients with AD and other types of dementia. METHODS: A review was conducted using MEDLINE, PsycINFO, and Embase. Search terms included clock drawing or CLOX and dementia or Parkinson's Disease or AD or dementia with Lewy bodies (DLB) or vascular dementia (VaD). RESULTS: Twenty studies were included. In most of the studies, no significant differences were found in quantitative CDT scores between AD and VaD, DLB, and Parkinson's disease dementia (PDD) patients. However, frontotemporal dementia (FTD) patients consistently scored higher on the CDT than AD patients. Qualitative analyses of errors differentiated AD from other types of dementia. CONCLUSIONS: Overall, the CDT score may be useful in distinguishing between AD and FTD patients, but shows limited value in differentiating between AD and VaD, DLB, and PDD. Qualitative analysis of the type of CDT errors may be a useful adjunct in the differential diagnosis of the types of dementias.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".