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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Cognitive screening in persons with chronic diseases in primary care: challenges and recommendations for practice
Ponrathi Athilingam1, Constance Visovsky, Amanda F Elliott
1Morsani College of Medicine, University of South Florida, Tampa, FL, USA. pathilin@health.usf.edu
Abstract:
An integrative literature review was performed to identify the challenges in current cognitive screening. The aim of the review was to serve as an evaluative resource to guide clinicians in the selection of the best available cognitive screening measures for early assessment of mild cognitive impairment (MCI) in people with chronic diseases. The review classified the available cognitive screening measures according to purpose, time to administer, and cognitive domains assessed as: 1) simple/ brief cognitive screening measures, 2) disease specific screening measures, 3) domain specific screening measures, 4) self-administered screening measures, and 5) technology-based screening measures. There is no single optimal cognitive measure for all patient populations and settings. Although disease specific cognitive screening measures are optimal, there is a lack of validated screening measures for many chronic diseases. Technology-based screening measure is a promising avenue for increasing the accessibility of cognitive screening. Future work should focus on translating available screening measures to mobile technology format to enhance the utility in busy primary care settings. Early cognitive screening in persons with chronic disease should enhance appropriate referrals for detailed neurocognitive examination and cognitive interventions to preserve and or minimize cognitive decline.
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