The Clock Drawing Test as a predictor of cognitive decline in non-demented stroke patients
Bibliographic record
Abstract
BACKGROUND: The early detection of patients at risk of post-stroke cognitive impairment (PSCI) may help planning subacute and long-term care. We aimed to determine the predictivity of two screening cognitive tests on the occurrence of mild cognitive impairment or dementia in acute stroke patients. METHODS: A cognitive assessment within a few days of ischemic or hemorrhagic stroke was performed in patients consecutively admitted to a stroke unit over 14 months by means of the Clock Drawing Test (CDT) and the Montreal Cognitive Assessment-Basic (MoCA-B). RESULTS: Out of 191 stroke survivors who were non-demented at baseline, 168 attended at least one follow-up visit. At follow-up (mean duration ± SD 12.8 ± 8.7 months), 28 (18.9%) incident cases of MCI and 27 (18%) cases of dementia were recorded. In comparison with patients who remained cognitively stable at follow-up, these patients were older, less educated, had more comorbidities, a higher score on the National Institutes of Health Stroke Scale (NIHSS) at admission, more severe cerebral atrophy, and lower MoCA-B and CDT scores at baseline. In multi-adjusted (for age, education, comorbidities score, NIHSS at admission and atrophy score) model, a pathological score on baseline CDT (< 6.55) was associated with a higher risk of PSCI at follow-up (HR 2.022; 95% CI 1.025-3.989, p < 0.05) with respect to non-pathological scores. A pathological baseline score on MoCA-B (< 24) did not predict increased risk of cognitive decline at follow-up nor increased predictivity of stand-alone CDT. CONCLUSION: A bedside cognitive screening with the CDT helps identifying patients at higher risk of PSCI.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".