Open AccessPattern Recognition to Objectively Differentiate the Etiology of Cognitive Decline: Analysis of the Impact of Stroke and Alzheimer’s Disease
Author(s) -
Sean Clouston,
Lauren L. Richmond,
Stacey B. Scott,
Christian C. Luhmann,
Ginny Natale,
David A. Hanes,
Yun Zhang,
Dylan M. Smith
Publication year - 2020
Publication title -
neuroepidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.217
H-Index - 87
eISSN - 1423-0208
pISSN - 0251-5350
DOI - 10.1159/000510133
Subject(s) - cognitive decline , medicine , episodic memory , stroke (engine) , cognition , neuropathology , alzheimer's disease , gerontology , disease , dementia , demography , psychiatry , mechanical engineering , sociology , engineering
Background: Undetected Alzheimer’s disease (AD) and stroke neuropathology is believed to account for a large proportion of decline in cognitive performance that is attributed to normal aging. This study examined the amount of variance in age-related cognitive change that is accounted for by AD and stroke using a novel pattern recognition protocol. Method: Secondary analyses of data collected for the Health and Retirement Study ( N = 17,579) were used to objectively characterize patterns of cognitive decline associated with AD and stroke. The rate of decline in episodic memory and orientation was the outcome of interest, while algorithms indicative of AD and stroke pathology were the predictors of interest. Results: The average age of the sample was 67.54 ± 10.45 years at baseline, and they completed, on average, 14.20 ± 3.56 years of follow-up. After adjusting for demographics, AD and stroke accounted for approximately half of age-associated decline in cognition (51.07–55.6% for orientation and episodic memory, respectively) and explained variance attributed to random slopes in longitudinal multilevel models. Discussion: The results of this study suggested that approximately half of the cognitive decline usually attributed to normal aging are more characteristic of AD and stroke.