bluuebunny/crossref_metadata_2025_split huggingface dataset:
Interactive care: A web‐based platform for remote caregiving and functional independence in older adults with cognitive impairment
Authors: Weakley Alyssa , Liu Xin , Duvvur Sanjna , Kaushal Harshita , Mussi Nicola , Namboodiri Sudev , Choi Yong , Farias Sarah Tomaszewski 
Published: December 2021

AbstractBackgroundRemote family caregiving of cognitively impaired older adults has many challenges including lack of evidence‐based interventions that meets the needs of both stakeholders. Further, physical distance may lead to emotional distance including feelings of loneliness and depression in the care receiver as well as helplessness and burden in the caregiver. To fill this gap, our team sought to develop the Interactive‐Care (I‐Care) platform which transforms and augments the traditional whiteboard, a compensatory cognitive rehabilitation tool for dementia care, to a digital format accessible from any device. I‐Care provides 5 main functions: home page (orientation information), calendar, to‐do list, messaging hub, and brain health center. A beta version of I‐Care was developed based on usability principles from human‐computer interaction literature, caregiving needs assessments, and guidelines for creating technology for older adults with cognitive impairment. The current project focuses on the first of three rounds (1. experts, 2. caregivers, 3. individuals with mild cognitive impairment/mild dementia) of iterative interface design.MethodIndividual semi‐structured interviews were conducted with experts in dementia caregiving, gerontechnology, and digital health. Prior to each interview, experts were provided with the I‐Care weblink and a project summary for review. All interviews were conducted over live‐stream video and were audio recorded for transcription. The “share screen” function was used to demonstrate the different I‐Care components and feedback was solicited.ResultsOn a scale from 1‐10, with 1 being not at all useful and 10 being very useful, experts rated I‐Care as a useful tool both for individuals with mild cognitive impairment/mild dementia (M = 8.33, SD = 1.53) and remote caregivers (M = 9.33, SD = 1.15). Recommended improvements included minor modifications to the user interface (e.g., text contrast, reorganization of visual components), functionality (e.g., ability to add or subtract features based on level of cognitive impairment), and expansion (e.g., medication tracking with pillbox sensor).ConclusionsAlthough more data is needed, I‐Care is a promising remote caregiving tool with potential to reduce emotional distance despite physical divide. Next steps include conducting similar interviews with caregivers and individuals with cognitive impairment followed by a pilot study with 10 care dyads.
Higher dietary inflammatory index scores are associated with increased incidence of all‐cause dementia in the Framingham Heart Study
Authors: van Lent Debora Melo , Himali Jayandra J , Gokingco Hannah , Aparicio Hugo J , Gonzales Mitzi M , Salinas Joel , Beiser Alexa S , Seshadri Sudha , Jacob Mini Elizabeth 
Published: December 2021

AbstractBackgroundNutrition is hypothesized to protect against systemic chronic inflammation, which plays an important role in the development and progression of disease including dementia. We evaluated whether higher (i.e. pro‐inflammatory) Dietary Inflammatory Index (DII) scores were associated with increased incidence of all‐cause dementia and Alzheimer’s disease (AD) in the community‐based Offspring Framingham Heart Study (FHS).Method1021 older adults (mean age 69 years [standard deviation (SD)], 5;52.3% women]) completed a validated 126‐item Food Frequency Questionnaire (FFQ). We created a DII score (based on the published method by Shivappa et al. 2014) based on previous studies linking individual dietary factors to six inflammatory markers (i.e. C‐reactive protein, interleukin (IL)‐1β , IL‐4, IL‐6, IL‐10 and tumor necrosis factor‐alpha, consisting of 31 components. A cumulative DII score was calculated by averaging across a maximum of three FFQs (administered at FHS exams 5 (1991‐1995), 6 (1995‐1998), and 7 (1998‐2001)). Exam 7 was considered as study baseline and participants were followed over a mean 12.6 years (SD 5.5). We excluded participants aged <60 years, those with prevalent dementia and/or other neurological conditions, and/or no dementia follow‐up.Result150 participants developed all‐cause dementia (including 118 participants who developed AD). Higher DII scores were associated with an increased incidence of all‐cause dementia following adjustment for age and sex (HR1.11,95%CI 1.01‐1.22,p=0.03). The relationship remained after additional adjustment for education, apolipoprotein e4, body mass index, smoking status, physical activity index score, total energy intake, lipid lowering medication and total cholesterol:high‐density lipoprotein‐ratio (HR1.14,95%CI 1.01‐1.29,p=0.04). We observed no relationship between higher DII scores and incident AD. Additionally, we observed no significant interactions between higher DII scores and sex, the presence of an APOE ε4 allele, or physical activity in their associations with incident all‐cause dementia or AD.ConclusionHigher DII scores were associated with a higher risk of incident all‐cause dementia, but not incident AD. Although these promising findings need to be replicated and further validated, our results suggest that diets which correlate with low DII scores could prevent late‐life dementia. Further, future studies are encouraged to test our findings among older adults of other race and ethnic groups and over a longer follow‐up period.
Augmented reality to detect subtle alterations in the early stages of Alzheimer’s disease: Preliminary results of the RADAR‐AD study
Authors: Muurling Marijn , de Boer Casper , Bügler Maximilian , Harms Robbert , Tarnanas Ioannis , Kouzak Rouba , Verheij Herman , Nies Vera J.M. , Daskalova Yoanna , Stolk Pieter , Durudas Andre , Curcic Jelena , Hannesdottir Kristin , Erdemli Gul , Hinds Chris , Wu Yuhao , Lucivero Federica , Stavropoulos Thanos G. , Owens Andrew P. , Narayan Vaibhav A. , Aarsland Dag , Visser Pieter Jelle ,   the RADAR‐AD Consortium
Published: December 2021

AbstractBackgroundThe ‘Remote Assessment of Disease and Relapse – Alzheimer’s Disease’ (RADAR‐AD) study is assessing functional decline in Alzheimer’s disease (AD) using remote monitoring techniques (RMT’s). Compared to traditional pen‐and‐paper clinical assessments, RMT’s can continuously and objectively monitor function during activities of daily living (ADL), which are arguably more sensitive to the earliest stages of AD. The aim of this abstract is to compare the results of the augmented reality task ‘Altoida’, that recreates an ADL requiring spatial navigation and memory, implemented as a tablet application, between 1) healthy controls, preclinical AD and prodromal AD, and with 2) standard clinical tests for cognitive and functional decline.MethodWe included amyloid negative cognitively normal (healthy controls, n=10), amyloid positive cognitively normal (preclinical AD, n=7) and amyloid positive mild cognitive impaired (prodromal AD, n=4) participants (Table 1) from the RADAR‐AD study. The outcome of the Altoida test, consisting of a motor task and two tasks in which participants have to hide‐and‐seek virtual objects, is the validated Neuromotor Index (NMI), with higher scores reflecting normative scoring, according to age, sex and education. Cognition was measured using a word‐list‐learning test, digit symbol substitution test (DSST), Rey complex figure, verbal fluency and Boston naming test. Functional decline was assessed using the Amsterdam Instrumented Activities of Daily Living (AIADL) questionnaire.ResultIn our preliminary sub‐sample, healthy controls showed higher NMI scores compared to the preclinical AD and prodromal AD participants (p=0.02) (Figure 1). The NMI was related to the DSST only (Figure 2).ConclusionNMI scores differed between cognitively normal healthy controls and cognitively normal preclinical AD participants, while no differences could be found in cognitive and functional tests between these groups. The sample size will increase in the coming months, but despite the currently small sample, the preliminary results are promising in evidencing that digital biomarkers are potentially more sensitive than standard clinical tests in detecting the early stages of AD, which could be helpful in developing new endpoints in clinical trials. This work has received support from the EU/EFPIA Innovative Medicines Initiative Joint Undertaking RADAR‐AD (grant No 806999) and their associated partners.
Cerebrovascular disease and depressive symptomatology in individuals with subjective cognitive decline: A community‐based study
Authors: Diaz‐Galvan Patricia , Cedres Nira , Figueroa Nerea , Barroso Jose , Westman Eric , Ferreira Daniel 
Published: December 2021

AbstractBackgroundSubjective cognitive decline (SCD) may be the first sign of Alzheimer’s disease (AD), but it can also reflect other pathologies such as cerebrovascular disease or conditions like depressive symptomatology. The role of depressive symptomatology in SCD is controversial. In this study, we investigated the association between depressive symptomatology, cerebrovascular disease, and SCD. We hypothesized three different scenarios, where depressive symptomatology would co‐exist, contribute to, or be a consequence of SCD (Figure).MethodWe recruited 225 cognitively unimpaired individuals from a prospective community‐based study (mean age (SD) = 54.64 (10.18); age range 35 – 77 years; 55% women; 102 individuals without any subjective cognitive complaint, 123 individuals with one or more complaints). SCD was assessed with a scale of 9 memory and non‐memory subjective complaints. Depressive symptomatology was assessed with established questionnaires. We used magnetic resonance imaging markers of white matter signal abnormalities (WMSA) and mean diffusivity (MD) to assess cerebrovascular disease. We combined correlation, multiple regression, and mediation analyses to investigate the association between depressive symptomatology, cerebrovascular disease, and SCD.ResultsWe found that SCD was associated with higher cerebrovascular disease (WMSA: r=0.210, p<0.002; MD: r=0.216, p=0.001), older age (r=0.373, p<0.001), and increased depressive symptomatology (r=0.340, p<0.001). In turn, depressive symptomatology was not associated with cerebrovascular disease (WMSA: r=0.003, p<0.961; MD: r=0.076, p<0.321) or age (r=0.069, p<0.030). We also studied whether abnormalities in white matter MD in SCD may be due to cerebrovascular disease. Results showed that variability in MD was mediated by WMSA burden (p=0.026), presumably reflecting cerebrovascular disease.ConclusionIn our community‐based cohort, depressive symptomatology co‐exists with SCD and reflects emotional factors, but does not reflect cerebrovascular disease. In addition, depressive symptomatology did not influence the capacity of SCD to predict underlying cerebrovascular disease. We suggest that therapeutic interventions for depressive symptomatology could alleviate the psychological burden of negative emotions in people with SCD, and intervening on vascular risk factors to reduce cerebrovascular disease should be tested as an opportunity to minimize neurodegeneration in SCD.
Stability of the novel blood‐based biomarkers under pre‐analytical sample handling conditions: Results of the SABB‐GBSC working group
Authors: Verberk Inge M.W. , Misdorp Els O. , Koelewijn Jannet , Ball Andrew J. , Blennow Kaj , Dage Jeffrey L. , Fandos Noelia , Hansson Oskar , Hirtz Christophe , Janelidze Shorena , Lee Ryan , Rissman Robert A. , Shan Dandan , Shaw Leslie M. , Yarasheski Kevin E. , Zetterberg Henrik , Edelmayer Rebecca M. , Teunissen Charlotte E. 
Published: December 2021

AbstractBackgroundPre‐analytical sample handling might affect the results of Alzheimer’s blood‐based biomarkers. In this collaborative study of the SABB‐GBSC working group guided by the Alzheimer’s Association, we elucidate the effects of the most common sample handling variations on blood‐based amyloid and non‐amyloid biomarkers.MethodFreshly collected blood was differentially treated, to create sample sets (n=10 per condition). We investigated the effect of collection tube type, and of EDTA plasma handling variations: delayed centrifugation, centrifugation temperature, aliquot volume, delayed storage, and freeze‐thawing. Frozen aliquots were shipped to participating labs, to measure amyloid beta (Abeta) peptides (with different technologies: C2N LS‐mass spectrometry (MS), Shimadzu MALID‐MS, N4PE and N3PA Simoa, Euroimmun and Araclon ELISA), Abeta oligomerization tendency (OAβ; PeopleBio), glial fibrillary acidic protein (GFAP; Quanterix), neurofilament light (NfL; Quanterix), total tau (tTau; Quanterix) and phosphorylated tau181 (pTau181; Eli Lilly Simoa assay). Data analysis was descriptive.ResultUsing other sample types than EDTA plasma resulted in different absolute levels for most of the measured biomarkers (figures 1‐4), with generally higher levels in lithium‐heparin plasma, lower levels in sodium‐citrate plasma, and variable but comparable levels in serum. Independent of the technology used, when EDTA plasma was kept at room temperature pre‐ or post‐centrifugation, Abeta42 and Abeta40 levels remained stable for up to 3 hours, while at 24 hours levels were decreased. When kept at 2‐8°C, Abeta levels were stable for up to 24 hours delayed centrifugation or storage (figure 1 and 2). The Abeta42/40 ratio mitigated some of the variability noted in Abeta42 and Abeta40 levels for some of the technologies and conditions, but not for all (figure 3). Abeta42 and Abeta40 levels were robust to differences in tube filling, short‐term ‐20°C storage, and up to 4 freeze‐thaw cycles (figure 1 and 2). While the other biomarkers OAβ, GFAP, NfL and pTau181 were mostly resistant to pre‐analytical sample handling variations, tTau levels were affected by delayed centrifugation and by centrifugation temperature (figure 4).ConclusionBased on the current findings, we construct a standardized operating procedure for pre‐analytical blood sample handling, that will facilitate swift introduction of blood‐based biomarkers into research and clinical settings.
Being a frail older person at the time of the COVID‐19 pandemic
Authors: Chen Yaohua Sophie , Rohr Susanne , Werle Berenice Maria , Romero‐Ortuno Roman 
Published: December 2021

AbstractBackgroundDuring the COVID‐19 pandemic, frail older individuals have been identified as a particularly vulnerable group for poor health outcomes, including cognitive decline and dementia. We aimed to reflect on the interaction between frailty and COVID‐19 with regards to health consequences.MethodUsing a rapid literature review approach, we aimed to identify what it means to be a frail older individual in the COVID‐19 pandemic from the perspective of three different settings: community, hospitals, and nursing homes. Four researchers from 4 countries (Ireland, France, Germany, and Brazil) reviewed articles from the MEDLINE database and grey literature including public policy briefs from their countries.ResultsIn the community, some governments advised to practice “cocooning”, i.e. stay‐at‐home‐orders for older individuals. This brought unprecedented restrictions to lifestyles, leading to a potential frailty cascade among older adults. Social frailty likely caused mental ill‐health, cognitive and functional decline, increasing the risk for dementia. In hospitals, frailty affected from disease onset to survivorship. The clinical presentation was rather atypical, and the biological findings were more heterogenous. Some resource allocation strategies based on the Clinical Frailty Scale remained questionable and should take into account patients’ and carers’ needs. A quarter of patients had increased care needs at discharge. However, availability of rehabilitation and support services in the community has been reduced. Frail older adults living in nursing homes were the most vulnerable group. Isolating residents and limiting the spread of COVID‐19 was a key difficulty. Reduced visits from relatives, cancelled physical activities, and lack of social engagement worsened cognitive, behavioral, and physical conditions of the residents. There were also positive aspects such as the boom of digital literacy and telemedicine and a renewed debate on age and ageing.ConclusionsThe COVID‐19 pandemic spotlights the ageing population that is rapidly growing worldwide. Prolonged lifestyle restrictions during the pandemic led to poor health outcomes in frail older individuals, including cognitive decline and dementia. Lessons learned from how frail older individuals are getting through the pandemic provide a unique chance to improve health outcomes, community and health services and how we want to live as ageing societies.
Predicting the risk of incident dementia in older adults: The ADNI‐dementia risk score
Authors: Ezzati Ali , Thompson Paul M , Davatzikos Christos , Harvey Danielle J , Lipton Richard B 
Published: December 2021

AbstractBackgroundThere are many risk factors associated with incident dementia in older adults, however predicting the timeframe of progression to dementia is difficult. We aimed to develop a novel, machine learning‐derived model to predict the risk of incident dementia among non‐demented older adults.MethodUsing data from 1837 non‐demented participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI), we used random survival forest (RSF) methods, a nonparametric decision tree machine learning approach, to identify predictors of incident dementia. Three sets of features were used: Model 1: Demographics (age, sex, race/ethnicity, years of education, BMI, marital status); Model 2: Demographics + Neuropsychological test scores and depression (NP; Alzheimer's Disease Assessment Scale – Cognitive (ADAS‐cog), Mini‐Mental State Examination (MMSE), geriatric depression scale (GDS)); and Model 3: Demographics + NP + Biomarkers (APOE4 status, hippocampal volume, global β‐amyloid PET‐SUVR). An integer‐based score was developed to estimate the 10‐year risk of incident dementia using regression coefficients from Cox Proportional Hazard models.ResultOver up to 10 years of follow up (mean = 3.19), 377 participants (20.5%) developed incident dementia. The RSF models 2 and 3 demonstrated good discrimination (C‐index for Model 1, 0.58 [95% CI 0.53–0.59]; model 2, 0.68 [95% CI 0.65–0.71]; and model 3, 0.66 [0.62–0.69]. Performance of RSF models was similar to Cox‐based models, which used the same features. From the identified top‐performing predictors (listed in figure 1), an integer‐based risk score for 10‐year dementia incidence was created: ADNI‐Dementia risk score 1, 2, and 3. The cumulative 10‐year incidence of dementia increased in a graded fashion from quartile 1 to quartile 4 for all risk scores (Figure 2). Risk score 3, which included biomarkers, was the most specific model for detecting individuals unlikely to progress to dementia.ConclusionWe developed a new risk score that integrates readily available demographic, clinical, and biomarker data to predict the risk of dementia among non‐demented older adults. Using this simple tool is practical in clinical setting.
Gait speed is associated with changes in number of depression symptoms in older adults with type 2 diabetes
Authors: Lavie Inbar , Beeri Michal Schnaider , Schwartz Yonatan , Soleimani Laili , Heymann Anthony , Ravona‐Springer Ramit 
Published: December 2021

AbstractBackgroundWe examined the longitudinal relationships between motor function and number of depression symptoms, both important predictors of poor health‐related outcomes, including cognitive impairment, in old age. Analyses were based on initially cognitively normal older adults with type 2 diabetes (T2D) participating in the longitudinal Israel Diabetes and Cognitive Decline (IDCD) study.MethodSubjects [n=984; mean age 72 (SD=5); 40.4% female] underwent evaluations of motor functions‐ gait speed, measured by time to walk 3 meters (mean = 4.37 seconds; SD=2.35) and handgrip strength (mean 29 Kg; SD=10), and number of depression symptoms, assessed by the 15‐item version of the Geriatric Depression Scale (GDS) (mean=2, SD=2), at baseline and approximately every 18 months thereafter. Hierarchical Linear Mixed Models (HLMM), adjusting for demographic and cardiovascular risk factors as well as overall cognition, modeled the effects of motor function on repeated GDS scoresResultLower mean gait speed (based on all gait speed measurements) was associated with higher mean GDS scores (p=0.003) (based on all GDS measurements). A greater change in gait speed between measurements was associated with greater degree of change in GDS scores over the study period (p=0.034). Handgrip strength was not associated with number of depression symptoms or with their change over timeConclusionIn older adults with T2D, lower gait speed was associated with a greater number of depression symptoms. The degree of change in walking speed was associated with degree of change in GDS, such that greater increase in 3‐meters' walking time was associated with a greater increase in number of depression symptoms over time. Future studies should examine why gait speed, but not grip strength, was associated with depression. Slower gait speed due to depression, i.e. reverse causality, cannot be ruled out. Whether strategies for improvement of gait speed (e.g. physical activity) are effective in treatment or prevention of depressive symptoms in older adults with T2D merits investigation.