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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.
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http://dx.doi.org/10.1186/s40001-023-01265-6 | DOI Listing |
Alzheimers Dement
September 2025
Department of Population Health Sciences, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA.
Introduction: We compared and measured alignment between the Health Level Seven (HL7) Fast Healthcare Interoperability Resources (FHIR) standard used by electronic health records (EHRs), the Clinical Data Interchange Standards Consortium (CDISC) standards used by industry, and the Uniform Data Set (UDS) used by the Alzheimer's Disease Research Centers (ADRCs).
Methods: The ADRC UDS, consisting of 5959 data elements across eleven packets, was mapped to FHIR and CDISC standards by two independent mappers, with discrepancies adjudicated by experts.
Results: Forty-five percent of the 5959 UDS data elements mapped to the FHIR standard, indicating possible electronic obtainment from EHRs.
Alzheimers Dement
September 2025
Department of Neurology, Beijing TianTan Hospital, Capital Medical University, Beijing, China.
Cognitive impairment and dementia, including Alzheimer's disease (AD), pose a global health crisis, necessitating non-invasive biomarkers for early detection. This review highlights the retina, an accessible extension of the central nervous system (CNS), as a window to cerebral pathology through structural, functional, and molecular alterations. By synthesizing interdisciplinary evidence, we identify retinal biomarkers as promising tools for early diagnosis and risk stratification.
View Article and Find Full Text PDFAlzheimers Dement
September 2025
Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, South Korea.
Introduction: We developed and validated age-related amyloid beta (Aβ) positron emission tomography (PET) trajectories using a statistical model in cognitively unimpaired (CU) individuals.
Methods: We analyzed 849 CU Korean and 521 CU non-Hispanic White (NHW) participants after propensity score matching. Aβ PET trajectories were modeled using the generalized additive model for location, scale, and shape (GAMLSS) based on baseline data and validated with longitudinal data.
Int J Plant Anim Environ Sci
August 2025
Department of Translational Research, College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA 91766, USA.
Neurological disorders, such as Alzheimer's disease, Parkinson's disease, epilepsy, spinal cord injuries, and traumatic brain injuries, represent substantial global health challenges due to their chronic and often progressive nature. While allopathic medicine offers a range of pharmacological interventions aimed at managing symptoms and mitigating disease progression, it is accompanied by limitations, including adverse side effects, the development of drug resistance, and incomplete efficacy. In parallel, phytochemicals-bioactive compounds derived from plants-are receiving increased attention for their potential neuroprotective, antioxidant, and anti-inflammatory properties.
View Article and Find Full Text PDFAlzheimers Dement (Amst)
September 2025
Introduction: Simple screening tools are critical for assessing Alzheimer's disease (AD)-related pre-dementia changes. This study investigated longitudinal scores from the Quick Dementia Rating System (QDRS), a brief study partner-reported measure, in relation to baseline levels of the AD biomarker plasma pTau217 in individuals unimpaired at baseline.
Methods: Data from the Wisconsin Registry for Alzheimer's Prevention (N = 639) were used to examine whether baseline plasma pTau217 (ALZpath assay on Quanterix platform) modified QDRS or Preclinical Alzheimer's Cognitive Composite (PACC3) trajectories (mixed-effects models; time = age).