The Times They Are a-Changin’
Bibliographic record
Abstract
Identification of individuals who will eventually develop dementia is critical for early intervention, treatment, and care planning. The clock drawing test (CDT) is a widely used cognitive screening tool that has been well accepted among clinicians and patients for its ease of use and short administration time. This review explores the value of the CDT for predicting the later development of dementia in cognitively intact older adults and patients with mild cognitive impairment (MCI). Additionally, we reviewed studies that examined the ability of the CDT to monitor declines in cognitive functioning over time. A PubMed literature search for articles that included a longitudinal analysis of the CDT was conducted. The search included articles published up to June 2013 and manual cross-referencing of bibliographies. Relevant studies were categorized, summarized, and critiqued. The consensus from the studies reviewed suggests that the CDT is a useful measure of cognitive decline over time. Conceptual clock drawing errors (eg, misrepresentation of time) detected this decline most effectively. In addition, the CDT appears to differentiate at baseline between cognitively intact older adults who will develop dementia up to 2 years postbaseline. Finally, the CDT has been found to differentiate between patients with MCI who will progress to dementia up to 6 years postbaseline. The CDT appears useful for the longitudinal assessment of cognitive impairment and together with other validated measures may be helpful for predicting conversion to dementia. Cost-effective and practical ways of predicting risk of dementia will become increasingly critical as we develop disease-modifying treatments.
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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 | 0.004 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".