Affiliations: [a]
Dementia Research Centre (Singapore), Lee Kong Chian School of Medicine–Nanyang Technological University, Singapore
| [b]
Center for Quantitative Medicine, Duke-NUS Medical School, National University of Singapore, Singapore
Correspondence:
[*]
Correspondence to: A/Prof Nagaendran Kandiah, FRCP, Director, Dementia Research Centre (Singapore), Lee Kong Chian School of Medicine, 11 Mandalay Road, 308232 Singapore. Tel.: +65 6592 2653; E-mail: [email protected].
Abstract: Background:A delay in the detection of mild cognitive impairment (MCI) in the community delays the opportunity for early intervention. Accurate tools to detect MCI in the community are lacking. The Visual Cognitive Assessment Test (VCAT) is a visual based cognitive test useful for multilingual populations without the need for translation. Objective:Here, we evaluate the usefulness of VCAT in detecting MCI in a community population in Singapore. Methods:We recruited 301 participants from the community who completed a detailed neuropsychological assessment and 170 of them completed a 3T magnetic resonance imaging (MRI) brain scan. We performed a receiver operating characteristics analysis to test the diagnostic performance of VCAT compared to Montreal Cognitive Assessment (MoCA) in distinguishing MCI from cognitively normal (CN) by measuring area under the curve (AUC). To test for the association of VCAT with structural MRI, we performed a Pearson’s correlation analysis for VCAT and MRI variables. Results:We recruited 39 CN and 262 MCI participants from Dementia Research Centre (Singapore). Mean age of the cohort was 63.64, SD = 9.38, mean education years was 13.59, SD = 3.70 and majority were women (55.8%). VCAT was effective in detecting MCI from CN with an AUC of 0.794 (95% CI 0.723–0.865) which was slightly higher than MoCA 0.699 (95% CI 0.621–0.777). Among subjects with MCI, VCAT was associated with medial temporal lobe atrophy (ρ = –0.265, p = 0.001). Conclusions:The VCAT is useful in detecting MCI in the community in Singapore and may be an effective measure of neurodegeneration.
