1. Data‐driven classification of cognitively normal and mild cognitive impairment subtypes predicts progression in the NACC dataset
- Author
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Edmonds, Emily C, Thomas, Kelsey R, Rapcsak, Steven Z, Lindemer, Shannon L, Delano‐Wood, Lisa, Salmon, David P, and Bondi, Mark W
- Subjects
Biomedical and Clinical Sciences ,Biological Psychology ,Clinical Sciences ,Neurosciences ,Psychology ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Brain Disorders ,Aging ,Neurodegenerative ,Behavioral and Social Science ,Alzheimer's Disease ,Acquired Cognitive Impairment ,Clinical Research ,Dementia ,Neurological ,Humans ,Cognitive Dysfunction ,Disease Progression ,Aged ,Female ,Male ,Neuropsychological Tests ,Cluster Analysis ,Aged ,80 and over ,Risk Factors ,Alzheimer's disease ,cluster analysis ,cognitive subtypes ,dementia ,mild cognitive impairment ,neuropsychology ,preclinical Alzheimer's disease ,subtle cognitive decline ,Geriatrics ,Clinical sciences ,Biological psychology - Abstract
IntroductionData-driven neuropsychological methods can identify mild cognitive impairment (MCI) subtypes with stronger associations to dementia risk factors than conventional diagnostic methods.MethodsCluster analysis used neuropsychological data from participants without dementia (mean age = 71.6 years) in the National Alzheimer's Coordinating Center (NACC) Uniform Data Set (n = 26,255) and the "normal cognition" subsample (n = 16,005). Survival analyses examined MCI or dementia progression.ResultsFive clusters were identified: "Optimal" cognitively normal (oCN; 13.2%), "Typical" CN (tCN; 28.0%), Amnestic MCI (aMCI; 25.3%), Mixed MCI-Mild (mMCI-Mild; 20.4%), and Mixed MCI-Severe (mMCI-Severe; 13.0%). Progression to dementia differed across clusters (oCN
- Published
- 2024