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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Pre-Mild Cognitive Impairment: Can Visual Memory Predict Who Rapidly Convert to Mild Cognitive Impairment?
Eun Hyun Seo1,2, Hoowon Kim1,3, Kyu Yeong Choi1,2
1National Research Center for Dementia, Gwangju, Republic of Korea.
Objective:
Little is known about the natural course of pre-mild cognitive impairment (pre-MCI) and predictors to MCI. We followedup individuals with pre-MCI and cognitively normal (CN) elders to identify neuropsychological predictors for rapid conversion to MCI.
Methods:
Seventy-seven individuals with pre-MCI and 180 CN elders were recruited from the pool of individuals registered at the National Research Center for Dementia in Gwangju, Korea. We followed-up with them after a mean of 14±2.29 months. All participants underwent comprehensive clinical and neuropsychological assessment. Logistic regression analysis examined the ability of neuropsychological tests to predict conversions to MCI.
Results:
Of 257 participants, 142 (55.3%) were eligible for the follow-up study (102 CN, 40 pre-MCI). Logistic regression revealed that spatial delayed recall significantly predicted the conversion from pre-MCI to MCI. In CN, copy for a complex figure significantly predicted the conversion to pre-MCI or MCI.
Conclusion:
Our findings indicated that spatial delayed recall was associated with rapid conversion from pre-MCI to MCI. Spatial organization and planning, measured by complex figure reproduction, were associated with rapid conversion from CN to pre-MCI or MCI. Our study suggests that inclusion of visuospatial reproduction and memory using a complex figure further facilitates early detection of MCI.
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