ArticleJournal of neurology2026
The Queen Square cognitive assessment screen (Q-CAS): normative data and validation in acute stroke.
Article in Journal of neurology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundAccurate and comprehensive assessment of cognition after stroke is crucial for diagnosis and rehabilitation. However, detailed assessment by a Neuropsychologist is often not feasible or practical. Although many screening tools exist, none fulfill three critical criteria: 1) assess all stroke-relevant domains, 2) consider demographic variables of gender, age, education level, and whether English is a first or second language, and 3) is brief and can be easily administered.
methodsThe Q-CAS was developed by adapting well-validated neuropsychological tests. Cognitive domains include verbal/spatial memory, naming, perception, attention, executive functions, processing speed, and mood. We administered the Q-CAS to healthy individuals and patients with acute mild-to-moderate stroke, and examined aspects of reliability, convergent and divergent validity, and diagnostic accuracy against reference-standard neuropsychological testing.
results648 healthy individuals and 150 patients with acute stroke were assessed. The mean completion time was 9 min for healthy individuals and 15 min for stroke patients. All Q-CAS subtests demonstrated clinically acceptable convergent and divergent validity against neuropsychological tests. ROC curve analyses showed good discrimination for all cognitive domains and were comparable for left- and right-hemisphere lesions. Using a novel simple scoring method which incorporates demographic variables, executive function, speed, and memory showed the best sensitivity (> 0.8), whereas perception and attention showed the best specificity (> 0.8).
conclusionThe Q-CAS is a brief cognitive screening tool assessing six core cognitive domains and mood. Validated in acute stroke, it demonstrates good discrimination across domains and offers a practical first-line approach that mitigates limitations of existing tools while balancing brevity and thoroughness.
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