, is gaining recognition as a comprehensive test that covers multiple cognitive domains. The Montreal Cognitive Assessment (MoCA), created by Nasreddine et al. , is a widely used cognitive test and has traditionally been popular in clinical settings. Among these tools, the Mini-Mental State Examination (MMSE), developed by Folstein et al. It offers convenient, cost-effective and non-invasive screening tools in clinical settings, making it an essential cognitive assessment method compared to biomarkers detection or imaging exams. Neuropsychological testing remains crucial in detecting AD and MCI. A purely biological definition is with a low predictive accuracy for AD and insufficient to definitively predict MCI, not readily available in clinical screening as well. The framework of clinical–biological diagnosis for AD is based on a combination of specific clinical phenotypes and in vivo biomarkers. However, there remained a significant underdiagnosis or misdiagnosis of MCI and AD in clinical screening, indicating the need for early accurate detection methods of MCI and AD to ensure timely intervention and appropriate management strategies. The prevalence of AD in individuals aged over 65 is estimated to be around 10.8%, with MCI due to AD ranging from 8 to 12.9%. This leads to increased dependency and disability among the elderly population, contributing significantly to the global burden of non-communicable diseases. AD dementia affects over 55 million individuals worldwide and about 6.5 million Americans aged 65 and older. Approximately one-third of individuals with MCI progress to AD dementia within 5 years, while some may reverse to normal cognition. Mild cognitive impairment (MCI) is a clinical stage that falls between normal aging and dementia. A large underdiagnosis of the MCI and Alzheimer’s population still remains in clinical screening.Īlzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by a gradual and irreversible decline in cognitive function, accounting for 60% to 80% of dementia. 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. 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%. 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). 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 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). In detecting AD, the ADAS-cog had the highest Youden's Index (0.829), followed by the MoCA(0.813) and MMSE(0.796). 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. MethodsĪ total of 1289 participants aged over 65 were included from the baseline visits of Alzheimer’s disease Neuroimaging Initiative. 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. 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. In addition, the gold standard for diagnosing Mild Cognitive Impairment (MCI) remains unclear yet. The neuropathological confirmation serves as the gold standard for diagnosing Alzheimer's disease (AD), but it is usually not available to the living individuals.
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