Frequency and Clinical Determinants of Poststroke Cognitive Impairment in Nondemented Stroke Patients
Bibliographic record
Abstract
The objective of this study was to examine the prevalence and clinical correlates of poststroke cognitive impairment in Chinese stroke patients in Hong Kong. One hundred seventy-nine stroke patients were interviewed by a psychiatrist 3 months after their stroke. Cognitive impairment was determined according to the Mini-Mental State Examination score. Thirty-nine participants (21.8%) had cognitive impairment. Univariate analysis found that cognitive impairment was associated with age, female sex, level of education, previous stroke, prestroke Rankin score, National Institutes of Health Stroke Scale dysarthria and total scores, urinary incontinence, and cerebral atrophy index. Multivariate logistic regression suggested that female sex, education, National Institutes of Health Stroke Scale dysarthria score, urinary incontinence, and atrial fibrillation were independent risk factors of poststroke cognitive impairment. After removal of 54 patients with previous stroke from the sample, the frequency of cognitive impairment decreased to 18.4%. It was concluded that cognitive impairment is common among nondemented Chinese stroke patients in Hong Kong.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".