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BackgroundParticipant eligibility for the A4 Study was determined by amyloid PET imaging. Given the disadvantages of amyloid PET imaging in accessibility and cost, blood-based biomarkers may serve as a sufficient biomarker and more cost-effective screening tool for patient enrollment into preclinical AD trials.ObjectiveTo determine if a blood-based screening test can adequately identify amyloid burden in participants screened into a preclinical AD trial.MethodsIn this cross-sectional study, 224 participants from the A4 Study received an amyloid PET scan (18Florbetapir) within 90 days of blood sample collection. Blood samples from all study participants were processed within 2 h after phlebotomy. Plasma amyloid measures were quantified by Shimazdu and C2 N Diagnostics using mass spectrometry-based platforms. A corresponding subset of blood samples (n = 100) was processed within 24 h after phlebotomy and analyzed by C2 N.ResultsPlasma Aβ42/Aβ40 demonstrated the highest association for Aβ accumulation in the brain with an AUC 0.76 (95%CI = 0.69, 0.82) at C2 N and 0.80 (95%CI = 0.75, 0.86) at Shimadzu. Blood samples processed to plasma within 2 h after phlebotomy provided a better prediction of amyloid PET status than blood samples processed within 24 h (AUC 0.80 versus 0.64; p

Aim: Muscle mass and strength correlate with cognitive function; however, it remains unclear whether dynapenia (i.e., muscle weakness with preserved muscle mass) is relevant. This study aimed to explore whether dynapenia is associated with global cognitive function in community‐dwelling older Japanese adults. Methods: This cross‐sectional study used data from the Integrated Research Initiative for Living Well with Dementia Cohort Study, which pooled data from five community‐based geriatric cohorts. Dynapenia was defined as muscle weakness without muscle mass loss according to the Asian Working Group for Sarcopenia criteria. Cognitive function was assessed using the Mini‐Mental State Examination (MMSE). An ordered logistic regression analysis was conducted with dynapenia as the exposure and with cognitive decline stages, defined as an MMSE score of 27–30 for normal cognition, 24–26 for possible cognitive decline, and <24 for cognitive decline, as the outcome, stratified by sex and adjusted for age, muscle mass, education, alcohol consumption, smoking habits, living alone, and non‐communicable diseases. Results: We analyzed data for 3338 participants (2162 female) with preserved muscle mass. Of these, 449 (13.5%) had dynapenia, and 79 (2.4%) exhibited cognitive decline. Multivariate odds ratios (95% confidence interval) for cognitive decline among those with dynapenia, compared with those without dynapenia, were 1.51 (1.02–2.24) for males and 2.08 (1.51–2.86) for females. Conclusions: Muscle weakness is associated with cognitive decline, even in individuals with preserved muscle mass. Further studies are needed to better understand the association between muscle weakness and cognitive decline over time in order to develop dementia prevention strategies for those with dynapenia. Geriatr Gerontol Int 2024; 24: 123–129. [ABSTRACT FROM AUTHOR]

Introduction: We examined the relationship between previous fluctuations in Mini-Mental State Examination (MMSE) scores, future changes in MMSE scores, and attrition from follow-up surveys, which helps in a more comprehensive interpretation of repeatedly collected MMSE scores. Methods: This 4-year longitudinal study included 2,073 community-dwelling older adults aged ≥65 years in Japan. The MMSE was administered at baseline (T0), 2 years (T1), and 4 years (T2) follow-up. We performed multinomial logistic regression analysis with the dependent variable, indicating the change in MMSE score from T1 to T2 (categorized as increase, no change [reference category], and decrease) and attrition at T2. The independent variables included the change in MMSE scores from T0 to T1 and MMSE scores at T0 and T1. Results: The mean MMSE score was 29 across the three time points. A one-point decrease in MMSE score from T0 to T1 was associated with 79% (95% confidence interval: 1.62, 1.97) higher odds of an increase in MMSE score from T1 to T2 and 28% (1.17, 1.40) higher odds of attrition at T2. A one-point decrement in the MMSE score at T0 and T1 was also associated with an increase in the MMSE score from T1 to T2 and attrition at T2. Conclusion: Focusing on cognitive fluctuation for 2 years, rather than cognitive function at a point in time, would have no remarkable advantage when focusing on future cognitive function and attrition. Our results emphasize the need for further studies to identify factors that distinguish between those who continue to attend follow-up surveys and show improvements in cognitive test scores and those who drop out. [ABSTRACT FROM AUTHOR]

The article discusses the importance of early identification of prefrailty and frailty in older adults within the community, emphasizing collaboration among healthcare professionals for proactive frailty interventions. It introduces the Prefrailty scale for Appearance Observation by Nurses (PAON) as a simple yet effective tool for identifying prefrailty through clinical observations by nurses, highlighting its potential to improve early detection and intervention strategies for frailty.

Background: With increasingly aging societies, a comprehensive strategy for dementia research is important. The Organized Registration for the Assessment of dementia by the Nationwide General consortium toward Effective treatment (ORANGE) Registry is the first longitudinal multicenter prospective trial-ready cohort in Japan.Objective: To establish a large cohort for use in clinical trials and research in Japan.Methods: This registry, based on communities, hospitals, and nursing homes, covers three dementia stages (preclinical, mild cognitive impairment [MCI], and advanced dementia), and includes more than 30 hospitals. We analyzed enrollment and 1-year follow-up data for disease progression.Results: There were 1450 registered patients (649 men, 801 women; mean age, 77.92±6.70 years; mean Mini-Mental State Examination [MMSE] score, 25.19±2.76). The conversion rates from MCI to dementia and MCI to normal were 14.3% and 1.1%, respectively. High Clinical Dementia Rating score (odds ratio [OR] = 11.085, 95% confidence interval [CI]:1.619-75.913, p = 0.014), low MMSE score (OR = 0.835, 95% CI: 0.761-0.917, p < 0.001), high Geriatric Depression Scale score (OR = 1.093, 95% CI: 1.005-1.189, p = 0.038), and low body mass index (OR = 0.895, 95% CI: 0.829-0.967, p = 0.005) at enrollment were significant factors for conversion.Conclusion: The ORANGE MCI Registry is an established registry that facilitates creation of trial-ready cohorts to accelerate promotion of clinical trials with low reversion rates as it originates from a hospital. One-year follow-up analysis suggested assessing various factors for conversion risk. Further analyses will be possible in future with registry expansion. We will continue to refine this registry, including how it can be used more efficiently. [ABSTRACT FROM AUTHOR]