Methods for Improving Screening for Vascular Cognitive Impairment Using the Montreal Cognitive Assessment. (11th November 2020)

• Record Type: Journal Article
• Authors: Zaidi, Khush-Bakht; Rich, Jill B.; Sunderland, Kelly M.; Binns, Malcolm A.; Truong, Linda; McLaughlin, Paula M.; Pugh, Bradley; Kwan, Donna; Beaton, Derek; Levine, Brian; Sahlas, Demetrios J.; Dowlatshahi, Dariush; Hassan, Ayman; Mandzia, Jennifer; Troyer, Angela K.; Swartz, Richard H.
• Other Names: collab.
• Is Part Of: Canadian journal of neurological sciences. Volume 47:Number 6(2020)
• Page Start: 756
• Page End: 763
• Publication Date: 2020-11-11
• Subjects: Neurology -- Periodicals; Nervous system -- Surgery -- Periodicals; Electronic journals; 616.8
• DOI: 10.1017/cjn.2020.121
• Languages: English
• ISSNs: 0317-1671

Abstract

ABSTRACT: Background: Vascular cognitive impairment (VCI) post-stroke is frequent but may go undetected, which highlights the need to better screen cognitive functioning following a stroke. Aim: We examined the clinical utility of the Montreal Cognitive Assessment (MoCA) in detecting cognitive impairment against a gold-standard neuropsychological battery. Methods: We assessed cognitive status with a comprehensive battery of neuropsychological tests in 161 individuals who were at least 3-months post-stroke. We used receiver operating characteristic (ROC) curves to identify two cut points for the MoCA to maximize sensitivity and specificity at a minimum 90% threshold. We examined the utility of the Symbol Digit Modalities Test, a processing speed measure, to determine whether this additional metric would improve classification relative to the MoCA total score alone. Results: Using two cut points, 27% of participants scored ≤ 23 and were classified as high probability of cognitive impairment (sensitivity 92%), and 24% of participants scored ≥ 28 and were classified as low probability of cognitive impairment (specificity 91%). The remaining 48% of participants scored from 24 to 27 and were classified as indeterminate probability of cognitive impairment. The addition of a processing speed measure improved classification for the indeterminate group by correctly identifying 65% of these individuals, for an overall classification accuracy of 79%. Conclusions: The utility of the MoCA in detecting cognitive impairment post-stroke is improved when using a three-category approach. The addition of a processing speed measure provides a practical and efficient method to increase confidence in the determined outcome while minimally extending the screening routine for VCI.