Matthew J Hollocks1, Rebecca L Brookes1, Robin G Morris2, Hugh S Markus1. 1. Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK. 2. Department of Psychology, King's College London, Institute of Psychiatry, Psychology, and Neuroscience, London, UK.
Abstract
OBJECTIVE: While there are several cognitive screening tests available for the detection of cortical dementias such as Alzheimer's disease (AD), these are rarely designed to be sensitive to vascular cognitive impairment (VCI). The Brief Memory and Executive Test (BMET) is a screening measure designed to be sensitive to the cognitive profile of both VCI and AD. This study investigated the ability of the BMET to detect AD, and to differentiate between VCI and AD. METHODS: This study included 150 patients, with either SVD, both with (n = 48) and without VCI (n = 51), or AD (N = 51) and 51 healthy controls. Participants were aged between 40 and 90 years of age and completed both the BMET and the MMSE. RESULTS: Receiver operator characteristic (ROC) curve analysis showed as before the BMET is a good predictor SVD. Additionally, the BMET was a good predictor of AD (AUC = 0.96) and performed at least as well as the MMSE (AUC = 0.92) when differentiating AD patients from healthy controls. The BMET had a sensitivity of 86% and specificity of 100% for detecting AD patients from control subjects. Using the difference in cognitive profile between the AD and VCI group, we developed an index score which correctly classified 76% of patients as either having VCI or AD. CONCLUSION: The BMET is a brief and sensitive tool for the detection of cognitive impairment due to both SVD and AD and can be used to aid in the differentiation of the 2 diseases.
OBJECTIVE: While there are several cognitive screening tests available for the detection of cortical dementias such as Alzheimer's disease (AD), these are rarely designed to be sensitive to vascular cognitive impairment (VCI). The Brief Memory and Executive Test (BMET) is a screening measure designed to be sensitive to the cognitive profile of both VCI and AD. This study investigated the ability of the BMET to detect AD, and to differentiate between VCI and AD. METHODS: This study included 150 patients, with either SVD, both with (n = 48) and without VCI (n = 51), or AD (N = 51) and 51 healthy controls. Participants were aged between 40 and 90 years of age and completed both the BMET and the MMSE. RESULTS: Receiver operator characteristic (ROC) curve analysis showed as before the BMET is a good predictor SVD. Additionally, the BMET was a good predictor of AD (AUC = 0.96) and performed at least as well as the MMSE (AUC = 0.92) when differentiating ADpatients from healthy controls. The BMET had a sensitivity of 86% and specificity of 100% for detecting ADpatients from control subjects. Using the difference in cognitive profile between the AD and VCI group, we developed an index score which correctly classified 76% of patients as either having VCI or AD. CONCLUSION: The BMET is a brief and sensitive tool for the detection of cognitive impairment due to both SVD and AD and can be used to aid in the differentiation of the 2 diseases.