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Background: Past studies identified a link between weight loss and dementia, but lacked consistent conclusions. We sought to establish this link by examining the weight change profiles before and after dementia diagnosis., Methods: Using data from the Health and Retirement Study (1996-2020), we examined 13,123 participants. We conducted a nested case-control analysis to assess differences in biennial weight change profile while controlling for BMI, longevity polygenic risk scores, and APOE gene variants., Results: Participants with a memory disorder lost weight (-0.63%) biennially, whereas those without a diagnosis did not (+0.013%, p -value < 0.0001). Our case-control study shows a significant difference ( p -value < 0.01) in pre-dementia % weight changes between the cases (-0.29%) and controls (0.19%), but not in post-dementia weight changes. The weight loss group have the highest risk (OR = 2.01; p -value < 0.0001) of developing a memory disorder compared to the stable weight and weight gain groups. The observations hold true after adjusting for BMI, longevity polygenic risk scores, and APOE variant in a multivariable model., Conclusions: We observe that weight loss in dementia is a physiological process independent of genetic factors associated with BMI and longevity. Pre-dementia weight loss may be an important prognostic criterion to assess a person's risk of developing a memory disorder.

Introduction: Ophthalmic conditions and dementia appear to overlap and may share common pathways, but research has not differentiated dementia subtypes., Methods: Diagnoses of cataracts, age-related macular degeneration (AMD), diabetic retinopathy (DR), and glaucoma were based on medical histories and International Classification of Diseases, Ninth Revision (ICD-9) codes for 3375 participants from the Cardiovascular Health Study. Dementia, including Alzheimer's disease (AD) and vascular dementia (VaD), was classified using standardized research criteria., Results: Cataracts were associated with AD (hazard ratio [HR] = 1.34; 95% confidence interval [CI] = 1.01-1.80) and VaD/mixed dementia (HR = 1.41; 95% CI = 1.02-1.95). AMD was associated with AD only (HR = 1.87; 95% CI = 1.13-3.09), whereas DR was associated with VaD/mixed dementia only (HR = 2.63; 95% CI = 1.10-6.27)., Discussion: Differential associations between specific ophthalmic conditions and dementia subtypes may elucidate pathophysiologic pathways. Lack of association between glaucoma and dementia was most surprising from these analyses., (© 2021 the Alzheimer's Association.)

Purpose: The long-term effects of acetylcholinesterase inhibitors (AChEIs) used in the treatment of patients with various types of dementia remain unclear, largely due to challenges in the study of their discontinuation. We present several unexpected results from a discontinuation trial that might merit further investigation., Methods: This double-blind, placebo-controlled study of the discontinuation of AChEI medications was conducted in 62 US veterans. Participants were randomized to receive continued treatment with their medication (sham-taper group) or to treatment discontinuation via tapering (real-taper group), over a period of 6 weeks. The primary end point was the patient's/family caregiver's decision to discontinue the study medication., Findings: The study was underpowered to detect a significant between-group difference in the primary end point, but examination of the discontinuation process generated several unexpected results: (1) recruitment proved extremely challenging for a variety of reasons, with <5% of potentially eligible participants enrolled; (2) all 3 patients with Parkinson disease-associated dementia showed a worsening of symptoms when they discontinued their AChEI medication, but they showed improvement after they restarted it; (3) changes in symptom-scale scores varied quite broadly across participants, regardless of treatment arm; (4) unusual effects were noted in the sham-taper arm; and (5) the only significant predictor of the decision to discontinue the study medication was a worsening in the caregiver's mood., Implications: These findings argue for the use of caution in discontinuing AChEIs in patients with Parkinson disease-associated dementia, although there may be potential benefits of a "drug holiday." The findings also urge the consideration of distress on the part of the caregiver while making medication treatment decisions in dementia. Future research must address challenges with recruitment and symptom fluctuations., Competing Interests: Disclosures The authors have indicated that they have no conflicts of interest with regard to the content of this article., (Copyright © 2021. Published by Elsevier Inc.)

Background: Dementia is underdiagnosed in both the general population and among Veterans. This underdiagnosis decreases quality of life, reduces opportunities for interventions, and increases health-care costs. New approaches are therefore necessary to facilitate the timely detection of dementia. This study seeks to identify cases of undiagnosed dementia by developing and validating a weakly supervised machine-learning approach that incorporates the analysis of both structured and unstructured electronic health record (EHR) data., Methods: A topic modeling approach that included latent Dirichlet allocation, stable topic extraction, and random sampling was applied to VHA EHRs. Topic features from unstructured data and features from structured data were compared between Veterans with (n = 1861) and without (n = 9305) ICD-9 dementia codes. A logistic regression model was used to develop dementia prediction scores, and manual reviews were conducted to validate the machine-learning results., Results: A total of 853 features were identified (290 topics, 174 non-dementia ICD codes, 159 CPT codes, 59 medications, and 171 note types) for the development of logistic regression prediction scores. These scores were validated in a subset of Veterans without ICD-9 dementia codes (n = 120) by experts in dementia who performed manual record reviews and achieved a high level of inter-rater agreement. The manual reviews were used to develop a receiver of characteristic (ROC) curve with different thresholds for case detection, including a threshold of 0.061, which produced an optimal sensitivity (0.825) and specificity (0.832)., Conclusions: Dementia is underdiagnosed, and thus, ICD codes alone cannot serve as a gold standard for diagnosis. However, this study suggests that imperfect data (e.g., ICD codes in combination with other EHR features) can serve as a silver standard to develop a risk model, apply that model to patients without dementia codes, and then select a case-detection threshold. The study is one of the first to utilize both structured and unstructured EHRs to develop risk scores for the diagnosis of dementia.

Introduction: Ophthalmic conditions and dementia appear to overlap and may share common pathways, but research has not differentiated dementia subtypes. Methods: Diagnoses of cataracts, age‐related macular degeneration (AMD), diabetic retinopathy (DR), and glaucoma were based on medical histories and International Classification of Diseases, Ninth Revision (ICD‐9) codes for 3375 participants from the Cardiovascular Health Study. Dementia, including Alzheimer's disease (AD) and vascular dementia (VaD), was classified using standardized research criteria. Results: Cataracts were associated with AD (hazard ratio [HR] = 1.34; 95% confidence interval [CI] = 1.01‐1.80) and VaD/mixed dementia (HR = 1.41; 95% CI = 1.02‐1.95). AMD was associated with AD only (HR = 1.87; 95% CI = 1.13‐3.09), whereas DR was associated with VaD/mixed dementia only (HR = 2.63; 95% CI = 1.10‐6.27). Discussion: Differential associations between specific ophthalmic conditions and dementia subtypes may elucidate pathophysiologic pathways. Lack of association between glaucoma and dementia was most surprising from these analyses. [ABSTRACT FROM AUTHOR]

Advancements in Alzheimer's disease and related dementias (ADRD) research on the U.S. population acknowledge the importance of the high burden of ADRD on segments of the population and yet-to-be characterized risks attributable to the burden of multiple chronic diseases (multimorbidity). These realizations suggest successful strategies in caring for people with ADRD and their caregivers will rely not only on clinical treatments but also on more refined and comprehensive models of ADRD that take its broad effects on the whole-person and the whole of society into consideration. To this end, it is critical to characterize and address the relationship between ADRD and multimorbidity combinations that complicate care and lead to poor outcomes, particularly with regard to racial and ethnic disparities in the occurrence, course, and effects of ADRD. Several research and policy recommendations are presented to address the intersection of ADRD, multimorbidity, and underrepresented populations most at risk for adverse outcomes. [ABSTRACT FROM AUTHOR]