NIHSS is not enough for cognitive screening in acute stroke: A cross-sectional, retrospective study
Bibliographic record
Abstract
The aim of this study was to investigate whether the cognitive subscale of the National Institute of Health Stroke Scale (NIHSS), the Cog-4, can detect cognitive deficits in acute stroke. This was a cross-sectional, retrospective study. The study sample consisted of people with stroke enrolled in an acute stroke unit. The index test Cog-4 was calculated based on admission NIHSS score. The reference standard instrument, the Montreal Cognitive Assessment (MoCA), was performed within 36-48 h of admission. Non-parametric statistics were used for data analyses. The study included 531 participants with a mean age of 69 years. The Cog-4 failed to identify cognitive deficits in 65%, 58%, and 53% of patients when the MoCA thresholds for impaired cognition were set at ≤25 p, ≤23 p, and ≤19 p, respectively, were chosen for impaired cognition. The agreement between the Cog-4 and the MoCA was poor; Cohen's kappa was from -0.210 to -0.109, depending on the MoCA cut-offs. The sensitivity of the Cog-4 was 35%, 42% and 48% for the MoCA thresholds for impaired cognition ≤25, ≤23 and ≤19 points, respectively. The Cog-4 has a limited ability to identify cognitive deficits in acute stroke. More structured and comprehensive tests should be employed as diagnostic tools.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".