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Background <p>Accurate 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.</p> Methods <p>The 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.</p> Results <p>648 healthy individuals and 150 patients with acute stroke were assessed. The mean completion time was 9&#xa0;min for healthy individuals and 15&#xa0;min for stroke patients. All Q-CAS subtests&#xa0;demonstrated&#xa0;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 (&gt; 0.8), whereas perception and attention showed the best specificity (&gt; 0.8).</p> Conclusion <p>The 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.</p>

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The Queen Square cognitive assessment screen (Q-CAS): normative data and validation in acute stroke

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月20日

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  • Edgar Chan,
  • Maria del Rocio Hidalgo Mas,
  • Adrian So,
  • Robert Simister,
  • David J. Werring,
  • Parashkev Nachev,
  • Lisa Cipolotti

摘要

Background

Accurate 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.

Methods

The 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.

Results

648 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).

Conclusion

The 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.