Lindsay R Clark1,2, Rebecca L Koscik1, Christopher R Nicholas2,3, Ozioma C Okonkwo1,2,3, Corinne D Engelman1,4, Lisa C Bratzke1,5, Kirk J Hogan1,6, Kimberly D Mueller1, Barbara B Bendlin2,3, Cynthia M Carlsson1,2,3, Sanjay Asthana1,2,3, Mark A Sager1, Bruce P Hermann1,7, Sterling C Johnson1,2,3. 1. Wisconsin Alzheimer's Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53705, USA. 2. Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53705, USA. 3. Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, WI 53705, USA. 4. Department of Population Health Sciences, University of Wisconsin School of Medicine and Public Health, Madison, WI 53705, USA. 5. School of Nursing, University of Wisconsin-Madison, Madison, WI 53705, USA. 6. Department of Anesthesiology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53705, USA. 7. Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, WI 53705, USA.
Abstract
OBJECTIVE: Detecting cognitive decline in presymptomatic Alzheimer's disease (AD) and early mild cognitive impairment (MCI) is challenging, but important for treatments targeting AD-related neurodegeneration. The current study aimed to investigate the utility and performance of internally developed robust norms and standard norms in identifying cognitive impairment in late middle-age (baseline age range = 36-68; M = 54). METHOD: Robust norms were developed for neuropsychological measures based on longitudinally confirmed cognitively normal (CN) participants (n= 476). Seven hundred and seventy-nine participants enriched for AD risk were classified as psychometric MCI (pMCI) or CN based on standard and robust norms and "single-test" versus "multi-test" criteria. RESULTS: Prevalence of pMCI ranged from 3% to 49% depending on the classification scheme used. Those classified as pMCI using robust norms exhibited greater subjective cognitive complaints, diagnostic stability, and mild clinical symptoms at follow-up. CONCLUSIONS: Results suggest that identifying early clinically relevant cognitive decline in late middle-age is feasible using robust norms and multi-test criteria.
OBJECTIVE: Detecting cognitive decline in presymptomatic Alzheimer's disease (AD) and early mild cognitive impairment (MCI) is challenging, but important for treatments targeting AD-related neurodegeneration. The current study aimed to investigate the utility and performance of internally developed robust norms and standard norms in identifying cognitive impairment in late middle-age (baseline age range = 36-68; M = 54). METHOD: Robust norms were developed for neuropsychological measures based on longitudinally confirmed cognitively normal (CN) participants (n= 476). Seven hundred and seventy-nine participants enriched for AD risk were classified as psychometric MCI (pMCI) or CN based on standard and robust norms and "single-test" versus "multi-test" criteria. RESULTS: Prevalence of pMCI ranged from 3% to 49% depending on the classification scheme used. Those classified as pMCI using robust norms exhibited greater subjective cognitive complaints, diagnostic stability, and mild clinical symptoms at follow-up. CONCLUSIONS: Results suggest that identifying early clinically relevant cognitive decline in late middle-age is feasible using robust norms and multi-test criteria.
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