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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Persistent mild cognitive impairment in geriatric depression
Jung Sik Lee1, Guy G Potter, H Ryan Wagner
1Yong-In Mental Hospital, Yong-In, Korea.
Background:
Cognitive impairment often occurs with geriatric depression and impairments may persist despite remission of depression. Although clinical definitions of mild cognitive impairment (MCI) have typically excluded depression, a neuropsychological model of MCI in depression has utility for identifying individuals whose cognitive impairments may persist or progress to dementia.
Methods:
At baseline and 1-year follow-up, 67 geriatric patients with depression had a comprehensive clinical examination that included depression assessment and neuropsychological testing. We defined MCI by a neuropsychological algorithm and examined the odds of MCI classification at Year 1 for remitted depressed individuals with baseline MCI, and examined clinical, functional and genetic factors associated with MCI.
Results:
Fifty-four percent of the sample had MCI at baseline. Odds of MCI classification at Year 1 were four times greater among patients with baseline MCI than those without. Instrumental activities of daily living were associated with MCI at Year 1, while age and APOE genotype was not.
Conclusions:
These results confirm previous observations that MCI is highly prevalent among older depressed adults and that cognitive impairment occurring during acute depression may persist after depression remits. Self-reported decline in functional activities may be a marker for persistent cognitive impairment, which suggests that assessments of both neuropsychological and functional status are important prognostic factors in the evaluation of geriatric depression.
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