Pattern recognition to objectively differentiate the etiology of cognitive decay in longitudinal cognitive data: Analysis of stroke, Alzheimer’s disease, and normal aging

Authors: Sean Clouston, Lauren Richmond, Stacey Scott, Christian Luhmann, Ginny Natale, Douglas Hanes, Yun Zhang, Dylan Smith

Published: 2020-12-07

DOI: 10.1002/alz.041098

Source: Full article


Abstract

AbstractBackgroundEstimates suggest that Alzheimer’s disease and stroke account for a majority of age‐related cognitive decay. This study utilized novel pattern‐recognition protocols to estimate the extent to which cognitive decay might be attributable to Alzheimer’s disease and stroke.MethodSecondary analyses of data collected for the Health & Retirement Study (N=17,579) were used to objectively type Alzheimer’s disease and stroke‐related cognitive decay. Patterns of decay in episodic memory were the measure, while rate of linear decay in episodic memory and, separately, in orientation were the outcome.ResultAfter adjusting for demographics, Alzheimer’s disease and stroke accounted for approximately half of age‐associated decay in cognition (51.07‐55.6% for orientation and episodic memory respectively) and explained variance attributed to random slopes in longitudinal multilevel models.ConclusionResults support prior histopathological and neuroimaging efforts suggesting that approximately half of cognitive decay, commonly attributed directly to aging, may be due to stroke and other cerebrovascular disease, and Alzheimer’s disease.