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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Mild Cognitive Impairment Diagnosis and Care Algorithms and the Role of Digital Interventions: Expert Consensus
Nagaendran Kandiah1,2, Yee Fai Chan3, Darwin Dasig4
1Dementia Research Centre, Singapore, Singapore.
Background:
Mild cognitive impairment (MCI) is a clinically recognized condition, often being a prodromal dementia state with a risk of further cognitive decline. While there is currently no definitive diagnostic test for MCI, early identification and intervention are important.
Methods:
To assist clinicians in the diagnosis and treatment of MCI, the ASian Clinical Expert group on Neurocognitive Disorders (ASCEND) convened to identify ongoing gaps in MCI management primarily in Asia, and to discuss the existing body of literature with a view to providing evidence-based expert recommendations.
Results:
Two novel algorithms and a set of expert recommendations were formulated, addressing the cognitive assessment and clinical diagnosis of MCI, and optimal MCI management approaches. Because many risk factors for cognitive decline are modifiable, the mainstay of intervention comprises a multi-domain approach involving optimizing metabolic health, mitigating cerebrovascular risk, correcting hearing and vision loss, treating depression, encouraging engagement in cognitive exercises and social connection, and avoiding harmful substances. Digital interventions are becoming increasingly important as tools for cognitive assessment, as well as for cognitive stimulation and to help patients self-manage and maintain their independence. Pharmacologic approaches for MCI management include medical management of cardiovascular risk, reducing cholinergic burden and the use of drugs known to sedate or affect cognitive function, and evidence-based medications that have demonstrated benefit specifically in MCI.
Conclusions:
These evidence-based recommendations are intended to support clinicians, particularly in primary care, to identify MCI and plan an intervention strategy to help slow age-related cognitive decline.
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