Butler Hospital

BackgroundThe U.S. Study to Protect Brain Health through Lifestyle Intervention to Reduce Risk (U.S. POINTER) is a Phase 3, multicenter, 2‐year, randomized controlled trial assessing the effects of two multidomain lifestyle interventions on cognition in older adults at risk for cognitive decline due to well‐established factors such as sedentary behavior, suboptimal diet, and suboptimal cardiometabolic health. A key aim was to test the generalizability of the FINGER findings in a diverse, representative U.S. cohort. Interventions were modeled on FINGER, adapted to U.S. culture, and delivered in collaboration with community partners.MethodParticipants aged 60‐79 years meeting pre‐specified risk criteria for cognitive decline were randomized (1:1) at five sites to one of two intervention arms. Both arms targeted physical activity, nutrition, cognitive/social challenge and cardiometabolic risk management, but differed in intensity and accountability. The Structured arm (STR) included frequent peer team meetings, regular exercise, the MIND diet, BrainHQ cognitive training, social/cognitive challenge, and monthly blood pressure monitoring. The Self‐Guided arm (SG) included fewer peer team meetings and general health education with support to encourage health behaviors. The primary outcome, assessed at baseline and every six months, was change in global cognition, measured using a composite score based on tests of executive function, episodic memory, and processing speed. Secondary outcomes included domain‐specific cognitive scores, Clinical Dementia Rating‐Sum of Boxes, functional ability, frailty, and intervention response by subgroups (e.g., APOE4 carriers).ResultA total of 2,111 participants (mean age 68±5 years, 69% female, 31% from minoritized ethnoracial groups) were randomized. Retention exceeded 94%, and intervention adherence remained high throughout the 2‐year intervention period. Topline findings on intervention effects for primary and secondary outcomes will be presented. Additionally, two participants will share testimonials about their trial experiences.ConclusionU.S. POINTER, the largest lifestyle intervention trial globally, successfully met ambitious recruitment goals and engaged a diverse, at‐risk cohort while maintaining high retention and participation rates. The topline results will provide pivotal evidence on the effectiveness of multidomain interventions to improve cognition or slow decline in older U.S. adults, with high potential to inform public health initiatives aimed at reducing Alzheimer's disease and related dementia risk.

BackgroundGait impairments in Alzheimer’s disease (AD) and related dementias pose a major fall risk/contribute to morbidity/mortality. The Timed Up and Go (TUG) test is often used to assess mobility, gait changes, and dual‐task performance. The TUG‐Dual Task (TUG‐DT) version adds serial subtraction exercises to evaluate dual‐task cost (DTC). For cognitively unimpaired (CU) individuals or those with mild cognitive impairment (MCI), plasma biomarkers like pTau217, pTau181, and neurofilament light chain (NfL) can help assess the risk of AD. This study aimed to explore the relationship between TUG performance and plasma biomarkers in CU and MCI patients.MethodsParticipants included CU low‐risk (n = 75), CU high‐risk (n = 87), and CI (n = 32) older adults aged 55‐80, mean = .67.28 ± 6.062 years. Cognitive ability was assessed using the Clinical Dementia Rating Scale (CU = 0; CI = 0.5 or 1.0) and the Montreal Cognitive Assessment (CU ≥ 26; 18 ≤ CI ≤ 26). AD‐risk was determined by APOE genotyping and family history for CU groups. Plasma biomarkers pTau217, pTau181, and NfL were analyzed from fasting blood draws. Participants completed the TUG and TUG‐DT. ANOVAs, ANCOVAs, logistic regression, and generalized additive models (GAMs), were used to analyze the relationship between demographic factors, gait performance, and plasma biomarkers, with model comparisons guiding the final choice of GAMs for their flexibility in handling non‐linear relationships.ResultsStep count analysis on the TUG showed that the CU‐high‐risk and MCI groups performed similarly, while the CU‐low‐risk group completed significantly fewer steps than both. Plasma biomarkers, particularly pTau181 and NfL, interacted to predict gait performance only in the CU high‐risk group.ConclusionsThe TUG can predict plasma pTau217 levels with high specificity, distinguishing CU individuals not at risk for AD. Additionally, pTau181 and NfL interacted to predict performance on the TUG and TUG‐DT in the CU‐high‐risk group, suggesting subtle gait changes may signal early AD pathology. The CU‐low‐risk group’s reduced step count compared to others indicates preclinical AD might manifest with subtle mobility impairments. These findings support using simple gait tasks like the TUG for AD risk assessment in older adults.

Background/Objectives: Risk taking, a crucial component of decision-making, is domain-specific. However, most literature has focused on financial risk-taking in relation to cognitive functioning. The current study investigated the association between risk-taking behaviors in five different domains and various cognitive abilities in cognitively normal older adults. Methods: Participants (mean age = 69.55 ± 7.35 years; mean education = 16.69 ± 2.19 years; 58.9% female) completed the Domain-Specific Risk-Taking Scale (DOSPERT), consisting of financial, health, ethical, recreational, and social risk-taking questions. Cognitive performance on associative memory, verbal memory, working memory, verbal fluency, processing speed, and executive function was examined. Linear regression models adjusted for age, gender, and education level were conducted. Results: Two out of five risk-taking domains were associated with various aspects of cognition. Conclusions: Financial risk-aversion was linked to better memory, while health and safety risk-taking was linked to faster processing speed. These findings have practical implications in the context of everyday decision making.

BACKGROUND:Timely identification of mild cognitive impairment (MCI) is critical for maximizing early intervention opportunities in older adults at risk for dementia. This study evaluated the feasibility, acceptability, and validity of novel digital cognitive tests in primary care.METHODS:In a two-phase pilot study across three clinics, 51 older adults completed digital cognitive assessments remotely on personal devices followed by supervised tablet-based cognitive screening in-clinic and the Montreal Cognitive Assessment (MoCA). Surveys and interviews assessed patient and provider acceptability. Digital test completion rates were examined to assess feasibility.RESULTS:Completion rates ranged from 61.5% - 76% for the at-home assessments and 81.8% for in-clinic testing. Participants generally preferred at-home testing. Providers found in-clinic testing acceptable but identified barriers related to device access and EMR integration. All but one digital test showed moderate correlations with the MoCA.CONCLUSION:Digital cognitive screening—whether remote or in-clinic—shows promise for primary care implementation.

Infection control measures in the Department of Veterans Affairs Community Living Centers (CLCs), analogous to nursing homes, during the COVID-19 pandemic may have impacted residents' mental health. The purpose of this study was to examine changes in depressive symptoms before and during the COVID-19 pandemic in CLC residents. This cross-sectional national cohort study evaluated depressive symptoms in Veteran CLC residents from geographically diverse CLCs across four 9-month periods of the COVID-19 pandemic: pre (before COVID-19), early (before vaccine), mid (before booster), and late (after booster). Depressive symptoms were assessed with the Patient Health Questionnaire (PHQ-9), a standardized depression assessment, which is a required measure in the Minimum Data Set (MDS). We computed change in PHQ-9 scores from the initial to the last PHQ-9 assessment for each pandemic period. We also performed a focused analysis of residents with a past year depression diagnosis. The overall sample comprised 47,755 Veteran CLC residents, 43% percent (n=20,554) of whom had a depression diagnosis. The overall cohort mean PHQ-9 scores were similar across pandemic periods (pre=2.64, early=2.48, mid=2.61, late=2.45). There was intra-resident decline in PHQ-9 during each period which was statistically, but not clinically significant (pre=-0.54, early=-0.47, mid=-0.55, late=-0.49). Residents with a depression diagnosis followed a similar pattern for scores and decline in the periods compared with the full sample. PHQ-9 average scores indicated minimal depression even among those with a depression diagnosis, limiting ability to detect changes over time. For CLC residents during the COVID-19 pandemic, PHQ-9 scores were not meaningfully different between time periods. Characteristics of the study (e.g., sample/setting) or of older adults generally (e.g., resilience) may explain the low rates of depression.

<b>Conclusion:</b> Our algorithm reliably detected suspected TD, reaching higher sensitivity and specificity than trained raters using the standard assessment. The algorithm can be used to monitor patients taking antipsychotic medications, allowing scarce resources to assess identified patients for a conclusive diagnosis by psychiatrists.