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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Diabetes-Specific Dementia: A Structured Literature Review of Cognitive Assessment Methods
Kelli L Faaitiiti1, Daniel C Jupiter2
1Medical Student, School of Medicine, The University of Texas Medical Branch, Galveston, TX.
Abstract:
Diabetes mellitus is a known risk factor for the development of multiple subtypes of dementia and mild cognitive impairment. Recent research identifies a cause-specific diabetes-related dementia with a unique set of characteristics. Currently, there is no standard cognitive assessment battery recommended to specifically assess dementia that is a direct consequence of chronic diabetes, and some evaluations have been used for decades with minimal revisions, regardless of appropriateness. We performed a systematic review of the dementia/cognition evaluation methods most commonly used in the literature for assessing diabetic patients and identified which cognitive domains are typically assessed in this setting, and whether cognitive changes were more reflective of a vascular pathology, Alzheimer's pathology, or something else entirely. Search results yielded 1089 articles. After screening for appropriateness, a total of 11 full-text articles were assessed. In general, subjects in the reviewed studies were assessed using a variety of testing methods, examining different combinations of cognitive domains. A standard, clear definition of which cognitive domains are the most important to assess in diabetic patients is needed in order to determine what combination of assessment tools are most pertinent. Given the growing subset of the US population, careful reconsideration of cognitive assessment methods is needed to create self-care plans that take into account a specific collection of cognitive challenges for those with diabetes.
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