Bayesian estimation for the accuracy of three neuropsychological tests in detecting Alzheimer's disease and mild cognitive impairment: a retrospective analysis of the ADNI database.

Eur J Med Res

Department of Maternal and Child Health, School of Public Health, Capital Medical University, No. 10, Xi Toutiao You Anmenwai, Beijing, 100069, People's Republic of China.

Published: October 2023

AI Article Synopsis

  • - The study investigates the effectiveness of three neuropsychological tests (MoCA, MMSE, ADAS-cog) for diagnosing Alzheimer's disease (AD) and Mild Cognitive Impairment (MCI) in individuals over 65, as direct neuropathological confirmation isn't typically available.
  • - Results show that ADAS-cog has the highest diagnostic accuracy for identifying both AD and MCI, outperforming MoCA and MMSE in sensitivity and Youden's Index, especially for AD.
  • - The research concludes that ADAS-cog and MoCA are reliable tools for detecting AD and MCI due to AD, with the prevalence rates estimated at 20% for AD and 24.8% for MCI among the

Article Abstract

Background: The neuropathological confirmation serves as the gold standard for diagnosing Alzheimer's disease (AD), but it is usually not available to the living individuals. In addition, the gold standard for diagnosing Mild Cognitive Impairment (MCI) remains unclear yet. Neuropsychological testing, such as the Montreal Cognitive Assessment (MoCA), Mini-Mental State Examination (MMSE) and Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-cog), is commonly used tests in identifying AD and MCI, offering convenience, affordability, non-invasiveness, and accessibility in clinical settings. We aimed to accurately evaluate the discriminative ability of the three tests administrated at the same visit simultaneously in detecting AD and MCI due to AD in the absence of a gold standard.

Methods: A total of 1289 participants aged over 65 were included from the baseline visits of Alzheimer's disease Neuroimaging Initiative. Bayesian latent class models, accounting for conditional dependence between MoCA and MMSE, were conducted to assess the diagnostic accuracy of the three tests for detecting AD and MCI.

Results: In detecting AD, the ADAS-cog had the highest Youden's Index (0.829), followed by the MoCA(0.813) and MMSE(0.796). The ADAS-cog and MoCA showed similar sensitivity (0.922 vs 0.912) and specificity (0.907 vs 0.901), while the MMSE had lower sensitivity (0.874) and higher specificity (0.922). For MCI detection, the ADAS-cog had the highest Youden's Index (0.704) compared to the MoCA (0.614) and MMSE (0.478). The ADAS-cog exhibited the highest sensitivity, closely followed by the MoCA and MMSE (0.869 vs 0.845 vs 0.757), and the ADAS-cog also had good specificity (0.835 vs 0.769 vs 0.721). The estimated true prevalence of AD among individuals aged over 65 was 20.0%, and the estimated true prevalence of MCI due to AD was 24.8%.

Conclusions: The findings suggest that the ADAS-cog and MoCA are reliable tools for detecting AD and MCI, while the MMSE may be less sensitive in detecting these conditions. A large underdiagnosis of the MCI and Alzheimer's population still remains in clinical screening.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10568914PMC
http://dx.doi.org/10.1186/s40001-023-01265-6DOI Listing

Publication Analysis

Top Keywords

alzheimer's disease
16
accuracy three
8
tests detecting
8
mild cognitive
8
cognitive impairment
8
gold standard
8
standard diagnosing
8
three tests
8
detecting mci
8
moca mmse
8

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!