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Vascular cognitive impairment (VCI) post-stroke is frequent but may go undetected, which highlights the need to better screen cognitive functioning following a stroke.
We examined the clinical utility of the Montreal Cognitive Assessment (MoCA) in detecting cognitive impairment against a gold-standard neuropsychological battery.
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.
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%.
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.
Because individuals develop dementia as a manifestation of neurodegenerative or neurovascular disorder, there is a need to develop reliable approaches to their identification. We are undertaking an observational study (Ontario Neurodegenerative Disease Research Initiative [ONDRI]) that includes genomics, neuroimaging, and assessments of cognition as well as language, speech, gait, retinal imaging, and eye tracking. Disorders studied include Alzheimer’s disease, amyotrophic lateral sclerosis, frontotemporal dementia, Parkinson’s disease, and vascular cognitive impairment. Data from ONDRI will be collected into the Brain-CODE database to facilitate correlative analysis. ONDRI will provide a repertoire of endophenotyped individuals that will be a unique, publicly available resource.
Impairments in learning and recall have been well established in amnestic mild cognitive impairment (aMCI). However, a relative dearth of studies has examined the profiles of memory strategy use in persons with aMCI relative to those with Alzheimer's disease (AD). Participants with aMCI, nonamnestic MCI, AD, and healthy older adults were administered the California Verbal Learning Test-II (CVLT-II). Measures of semantic clustering and recall were obtained across learning and delayed recall trials. In addition, we investigated whether deficits in semantic clustering were related to progression from healthy aging to aMCI and from aMCI to AD. The aMCI group displayed similar semantic clustering performance as the AD participants, whereas the AD group showed greater impairments on recall relative to the aMCI participants. Control participants who progressed to aMCI showed reduced semantic clustering at the short delay at baseline compared to individuals who remained diagnostically stable across follow-up visits. These findings show that the ability to engage in an effective memory strategy is compromised in aMCI, before AD has developed, suggesting that disruptions in semantic networks are an early marker of the disease. (JINS, 2014, 20, 1–11)
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