Cognitive screening improves the predictive value of stroke severity scores for functional outcome 3–6 months after mild stroke and transient ischaemic attack: an observational study
Bibliographic record
Abstract
OBJECTIVES: To investigate the prognostic value of the neurocognitive status measured by screening instruments, the Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE), individually and in combination with the stroke severity scale, the National Institute of Health Stroke Scale (NIHSS), obtained at the subacute stroke phase or the baseline (≤2 weeks), for functional outcome 3-6 months later. DESIGN: Prospective observational study. SETTING: Tertiary stroke neurology service. PARTICIPANTS: 400 patients with a recent ischaemic stroke or transient ischaemic attack (TIA) received NIHSS, MoCA and MMSE at baseline and were followed up 3-6 months later. PRIMARY OUTCOME MEASURES: At 3-6 months following the index event, functional outcome was measured by the modified Rankin Scale (mRS) scores. RESULTS: Most patients (79.8%) had a mild ischaemic stroke and less disability (median NIHSS=2, median mRS=2 and median premorbid mRS=0), while a minority of patients had TIA (20.3%). Baseline NIHSS, MMSE and MoCA scores individually predicted mRS scores at 3-6 months, with NIHSS being the strongest predictor (NIHSS: R(2) change=0.043, p<0.001). Moreover, baseline MMSE scores had a small but statistically significant incremental predictive value to the baseline NIHSS for mRS scores at 3-6 months, while baseline MoCA scores did not (MMSE: R(2) changes=0.006, p=0.03; MoCA: R(2) changes=0.004, p=0.083). However, in patients with more severe stroke at baseline (defined as NIHSS>2), baseline MoCA and MMSE had a significant and moderately large incremental predictive value to the baseline NIHSS for mRS scores at 3-6 months (MMSE: R(2) changes=0.021, p=0.010; MoCA: R(2) changes=0.017, p=0.021). CONCLUSIONS: Cognitive screening at the subacute stroke phase can predict functional outcome independently and improve the predictive value of stroke severity scores for functional outcome 3-6 months later, particularly in patients with more severe stroke.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".