Details

Autor(en) / Beteiligte

• Thomas, Kelsey R.
• Edmonds, Emily C.
• Eppig, Joel S.
• Wong, Christina G.
• Weigand, Alexandra J.
• Bangen, Katherine J.
• Jak, Amy J.
• Delano-Wood, Lisa
• Galasko, Douglas R.
• Salmon, David P.
• Edland, Steven D.
• Bondi, Mark W.

Titel

MCI-to-normal reversion using neuropsychological criteria in the Alzheimer's Disease Neuroimaging Initiative

Ist Teil von

• Alzheimer's & dementia, 2019-10, Vol.15 (10), p.1322-1332

Ort / Verlag

United States: Elsevier Inc

Erscheinungsjahr

2019

Link zum Volltext

Quelle

Wiley Online Library Journals

Beschreibungen/Notizen

• The low mild cognitive impairment (MCI) to cognitively normal (CN) reversion rate in the Alzheimer's Disease Neuroimaging Initiative (2-3%) suggests the need to examine reversion by other means. We applied comprehensive neuropsychological criteria (NP criteria) to determine the resulting MCI to CN reversion rate. Participants with CN (n = 641) or MCI (n = 569) were classified at baseline and year 1 using NP criteria. Demographic, neuropsychological, and Alzheimer's disease biomarker variables as well as progression to dementia were examined across stable CN, reversion, and stable MCI groups. NP criteria produced a one-year reversion rate of 15.8%. Reverters had demographics, Alzheimer's disease biomarkers, and risk-of-progression most similar to the stable CN group and showed the most improvement on neuropsychological measures from baseline to year 1. NP criteria produced a reversion rate that is consistent with, albeit modestly improved from, reversion rates in meta-analyses. Reverters’ biomarker profiles and progression rates suggest that NP criteria accurately tracked with underlying pathophysiologic status. •Neuropsychological criteria for MCI produced a reversion rate of 15.8%.•A 15.8% reversion rate is consistent with, or modestly improved, relative to the literature.•Reverters had AD biomarkers and dementia risk similar to the stable normal group.•Neuropsychological criteria offer an empirically proven MCI classification method.•Results extend previous work that these MCI criteria may reduce diagnostic error.