Brief screening tests during acute admission in patients with mild stroke are predictive of vascular cognitive impairment 3–6 months after stroke
Bibliographic record
Abstract
OBJECTIVES: To determine the prognostic value of brief cognitive screening tests administered in the subacute stroke phase (initial 2 weeks) for the detection of significant cognitive impairment 3-6 months after stroke, the authors compared the Montreal Cognitive Assessment (MoCA) and the Mini-Mental State Examination (MMSE). METHODS: Patients with ischaemic stroke and transient ischaemic attack were assessed with both MoCA and MMSE within 14 days after index stroke, followed by a formal neuropsychological evaluation of seven cognitive domains 3-6 months later. Cognitive outcomes were dichotomised as either no-mild (impairment in ≤2 cognitive domains) or moderate-severe (impairment in ≥ 3 cognitive domains) vascular cognitive impairment. Area under the receiver operating characteristic (ROC) curve analysis was used to compare discriminatory ability. RESULTS: 300 patients were recruited, of whom 239 received formal neuropsychological assessment 3-6 months after the stroke. 60 (25%) patients had moderate-severe VCI. The overall discriminant validity for detection of moderate-severe cognitive impairment was similar for MoCA (ROC 0.85 (95% CI 0.79 to 0.90) and MMSE (ROC 0.83 (95% CI 0.77 to 0.89)), p=0.96). Both MoCA (21/22) and MMSE (25/26) had similar discriminant indices at their optimal cutoff points; sensitivity 0.88 versus 0.88; specificity 0.64 versus 0.67; 70% versus 72% correctly classified. Moreover, both tests had similar discriminant indices in detecting impaired cognitive domains. CONCLUSIONS: Brief screening tests during acute admission in patients with mild stroke are predictive of significant vascular cognitive impairment 3-6 months after stroke.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".