bluuebunny/crossref_metadata_2025_split huggingface dataset:
Muscular function: An alternative way to identify cognitive impairment—secondary analysis from SABE‐Colombia
Authors: Garcia‐Cifuentes Elkin , Botero‐Rodríguez Felipe , Velandia Felipe Ramirez , Iragorri Angela , Márquez Isabel C , Gelvis Geronimo , Acosta Maria‐Fernanda , Jaramillo‐Jimenez Alberto , Lopera Francisco , Cano‐Gutierrez Carlos Alberto 
Published: December 2021

AbstractBackgroundTraditionally, the identification of cognitive impairment is based on neuropsychological tests and supported with not widely available biomarkers. This study aimed to establish the association between motor function (Gait Speed and Handgrip Strength) and the performance in a global cognitive performance and various cognitive domains. Our secondary objective was to determine a cut‐off point for Gait Speed and Handgrip Strength to classify older adults as cognitively impaired.MethodThis is a secondary analysis from the SABE Colombia study (Health, Well‐Being, and Aging) conducted in 2015. We performed linear regression models, to establish association with motor function, clinical, and sociodemographic variables, and predict the scores of the Mini‐mental State Examination and its domains (i.e. orientation, recall, counting, and language). The evaluation of the motor function variables as an instrument to separate cognitively impaired older adults was evaluated by developing a receiving operating characteristic curve (ROC).ResultGait speed was associated with orientation (r2 = 0.16), language (r2 = 0.15), recall memory (r2 = 0.14) and counting (r2 = 0.08). Similarly, handgrip strength was associated with orientation (r2 = 0.175), language (r2 = 0.164), recall memory (r2 = 0.137), and counting (r2 = 0.08). Slow gait had a cut‐off point of 0,59 m/s, with an area under the curve (AUC) of 0.629 (0.613‐0.646), whereas a weak handgrip strength had an AUC of 0.653 (0.645‐0.661), with a cut‐off point of 17.50 Kg for separating those older adults with cognitive impairment.ConclusionGait Speed or Handgrip Strength are similarly associated with cognitive performance, exhibiting the larger associations with orientation and language domains. Gait Speed and Handgrip Strength can be easily performed by any clinician and seems to be useful screening tools to detect cognitive impairment.
Compact MoCA: A shortened alternative for MCI screening among healthy aging individuals
Authors: Muadmanee Wisawin , Hiransuthikul Akarin , Chunharas Chaipat , Thongkam Achitpol , Petchlorlian Aisawan , Praditpornsilpa Kearkiat 
Published: December 2021

AbstractBackgroundThe increasing number of elderlies highlights the important of clinical screening for cognitive impairment in healthcare setting. Montreal Cognitive Assessment (MoCA) is a widely used tool for mild cognitive impairment (MCI) screening, particularly among resource‐limited settings. Although originally claims to be a time‐saving tool of approximately 10 minutes, it takes much longer in real‐world settings, which consequently led to lack of MCI screening in many busy clinic settings. In order to shorten the duration for testing, we aimed to determine the performance of a compact MoCA which excludes domain(s) that does not correlate well with the total score.MethodData of Thai healthy adults aged ≥60 years from a prospective cohort conducted in King Chulalongkorn Memorial Hospital, a tertiary care center in Bangkok, Thailand was included. MoCA was used to assess cognitive performance. Cognitive domain that showed poor correlation to the total score was excluded to build a compact MoCA in order to shorten the time of assessment. Sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC) were used to evaluate the performance of the compact MoCA.ResultA total of 2,799 participants who completed MoCA were enrolled. Correlation analysis showed that naming and orientation had the lowest degree of correlation to the total MoCA score (coefficients of 0.355 and 0.364, respectively) and delayed recall had the highest degree of correlation (coefficients of 0.609). After excluding naming, MoCA showed 100% sensitivity and 96.05% at a cut‐off score of 25. After excluding orientation, MoCA showed 100% sensitivity and 97.60% specificity at a cut‐off score of 19. After excluding both naming and orientation, MoCA showed 100% sensitivity and 93.4% specificity at a cutoff score 16. AUROC of MoCA after excluding naming, orientation, and both naming and orientation was 0.996, 0.998 and 0.994, respectively.ConclusionThe compact MoCA which excludes either naming or orientation showed great performance with 100% sensitivity and >95% specificity, suggesting a possible alternative method to shorten the duration for MCI screening while maintaining the quality of the test. An on‐going MCI screening using an electronic MoCA is on‐going to precisely assess time use per each domain.
Statistical data harmonization for neuropsychological test battery conversion
Authors: Wilkins‐Reeves Steven , Chen Yen‐Chi , Chan Kwun Chuen Gary 
Published: December 2021

AbstractBackgroundA current problem scientists and clinicians face when studying cognitive impairment is how to harmonize scores across neuropsychological tests evaluating the same cognitive domains in a longitudinal analysis. Prior point conversion methods typically do not allow quantification of uncertainty and may be based on strong distributional assumptions. Our framework was motivated by an interest in assessing the uncertainty when converting scores.MethodWe established new statistical methodology for converting C1 and C2 neuropsychological batteries of the National Alzheimer’s Coordinating Center Uniform Data Set collected by the NIA Alzheimer’s Disease Research Centers Program. We adapted methodology from the measurement error and latent variable statistical modeling techniques and proposed an algorithm to give point and interval conversions. We developed parametric and non‐parametric models to achieve this task, allowing one to control for important traits such as age, education level and sex at birth. Additionally, we developed variational inference and functional Expectation Maximization algorithms to fit these models and implemented them in R. This method was compared to existing methodology using Z‐score conversions or quantile matching.ResultWe assessed our model by converting C1 scores (e.g. Mini‐Mental State Examination) to C2 scores (e.g. Montreal Cognitive Assessment). We trained our method on 18092 cognitively normal individuals with either a C1 or C2 score observed. The method was validated on a set 420 individuals with both scores observed using the Hellinger and Total Variation probability metrics to compare conversion distributions. Both methods outperformed prior methods in describing intrinsic variability (Table 1), which is the difference of scores from subsequent visits. Additionally, the non‐parametric model outperformed the others in matching the extrinsic variability, which is the difference of scores for individuals with multiple same day tests used to verify a model is capturing the conversion uncertainty (Table 1; Figures 1,2,3).ConclusionOur framework provides a statistically grounded approach to convert scores with uncertainty, a significant step towards understanding cognitive progression in settings where different neuropsychological batteries are used over time. This work establishes groundwork for future study including detection of Mild Cognitive Impairment when multiple testing batteries are used during an individual’s lifetime.
Quantifying patterns of pathology: A characterization of the 3D spatial distribution of tau tangles and amyloid plaques in Alzheimer’s disease using multi‐modal image registration with a scattering transform
Authors: Stouffer Kaitlin M , Wang Zhenzhen , Xu Eileen , Lee Karl S , Lee Paige , Mori Susumu , Troncoso Juan C , Saito Atsushi , Albert Marilyn S. , Miller Michael I , Tward Daniel J 
Published: December 2021

AbstractBackgroundVolumetric measures of MRI scans have consistently shown medial temporal lobe (MTL) atrophy in individuals across the spectrum of AD. However, these measures are not considered to be specific for AD, partly because a direct link to tau and amyloid pathology has not been demonstrated (Jack et. al, 2018). To address this limitation, we developed multi‐modal image registration and analysis tools to integrate neuropathological data from 2D histology images with 3D postmortem MRI images in the same brain region, in order to quantify the density of tangles and plaques.MethodsWe imaged tissue excised from the MTL at 0.125 mm resolution with an 11T MR scanner (fig 1a) and manually segmented it into subregions (fig 1b). We sliced the tissue into 10um thick sections, 1mm apart, and digitally imaged them with a light microscope after staining for amyloid (6E10) or tau (PHF‐1) (fig 1c). Locations of tangles and plaques on histology were estimated with a deep convolutional neural network (UNET) trained on a smaller set of annotated data (fig 1d). To align histology images with the MRI images, we first computed scattering transforms of histology to capture high resolution textural information (fig 1e). This was then used to find both optimal spatial and intensity profile transformations between the two imaging modalities (fig 1f). We rigidly aligned MRI images to the Mai Paxinos atlas for interpretability.ResultsWe localized tau tangles and amyloid plaques from histology sections of a person with severe AD, and in corresponding 3D MRI images of the brain tissue from the same individual. We quantified density of particles per region. Initial findings demonstrated the highest amount of tau in the entorhinal cortex, subiculum, and CA1 (fig 2) compared to other subregions in the MTL, consistent with Braak staging. No obvious differential distribution of amyloid was observed.ConclusionOur detailed localization of tangles and plaques in 3D offers the opportunity to study spatial distribution of pathology within brain regions among patients that span the spectrum of disease, which will foster more robust comparison with MRI atrophy, and potentially shed new light on the progression of AD.
Greater COVID‐19 impact for underrepresented racial and ethnic minority groups: A survey study on the Wisconsin Alzheimer’s Disease Research Center participants
Authors: Ma Yue , Spalitta Alice , Wahoske Michelle L , Blazel Hanna , Chappell Richard J , Chin Nathaniel A , Johnson Sterling C , Asthana Sanjay , Gleason Carey E , Carlsson Cynthia M 
Published: December 2021

AbstractBackgroundThe COVID‐19 pandemic has posed substantial impact on people’s life and wellbeing, especially for the aging population who are at greater risk. This study compared the difference in the impact between older adults from underrepresented racial/ethnic groups (URGs) versus non‐URGs.MethodThe National Alzheimer’s Coordinating Center COVID‐19 Impact Survey was self‐reported by 221 participants aged 49‐99 years from the Wisconsin Alzheimer’s Disease Research Center clinical core between August and December, 2020. 43 participants who reported “Black or African American” or “American Indian or Alaska Native” in primary or secondary race or reported “Yes” to Hispanic” ethnicity were classified as URGs. The remaining 178 participants who reported only “White” or “Asian” in the primary and secondary races and “No” to “Hispanic” ethnicity were classified as non‐URGs. The survey inquired on (1) COVID‐19 symptoms, testing, diagnosis, and hospitalization; (2) worrying, social isolation, and disruption on everyday life associated with the pandemic; (3) related cognitive, psychiatric, and behavioral changes; and (4) change of willingness in research participation. Group differences on survey responses were tested using Fisher’s exact test, non‐parametric Kruskal‐Wallis test, and binary or ordinal logistic regressions.ResultNo significant group difference was found in sex, age, and clinical diagnosis. However, URG participants had lower education and higher Clinical Dementia Rating (CDR) scores (Table 1). URGs were approximately doubled non‐URGs in the percentages of experiencing COVID‐19 symptoms, having a positive diagnosis, and reporting “very much” or “extremely” worrying about getting COVID‐19 and changing willingness to participate in clinical research. Controlling for sex, age, education, and CDR score, URGs were more likely to be tested for COVID‐19 (Odds Ratio = 2.37), have significantly reduced income (OR=4.74), experience change in memory or thinking (OR=2.97), and report a greater total number of psychiatric or behavioral changes (OR=2.04). However, URGs felt less isolated from family or friends (OR=0.55).ConclusionURGs had greater medical, psychological, and economical consequences than non‐URGs, which implied racial/ethnic disparities associated with the pandemic. Future research is needed to identify inequities in the social determinants and understand their association with disparities, which would help inform policies and strategies to achieve health equity.
The effect of sad mood on subjective appraisal of memory performance in older people with and without subjective memory complaints: An experimental study
Authors: Farmer Hilary Faithfull , Bahar‐Fuchs Alex , Bryant Christina 
Published: December 2021

AbstractBackgroundSubjective memory complaints (SMC) have been identified as a possible precursor to cognitive decline and may indicate a need for an early intervention for at‐risk older adults. However, it is well‐established that low mood is associated with SMC, leading to claims that memory concerns in older people may often reflect primarily psychological symptoms. This study aimed to determine the effect of low mood on subjective memory appraisal in older adults.MethodWe used a film‐based mood induction procedure (MIP) to test the effect of sad vs. neutral mood on subjective appraisal of memory performance in an experimental 2X2 between‐subjects design. Participants were 98 cognitively unimpaired older people (n=45 with SMC), randomised to the sad MIP (n=56) or the neutral MIP (n=42). All participants completed measures of trait SMC and ruminative self‐focused attention (RSFA) as well as perceived performance and metacognitive experience (ME) following the MIP and completion of a face‐name and a maze‐learning task.ResultParticipants in the sad MIP condition (M=42.75, SD=30.97) reported significantly greater sadness than those in the neutral condition following the manipulation (M=11.57, SD=18.44). The association between objective and subjective memory performance was stronger for cued recall on the face‐name task (r=.61, p=.001) and was weaker free recall on the face‐name task (r=.26, p=0.016) as well on the maze‐learning task (r=‐.16, p=.200). Contrary to expectation, there was no significant effect of mood condition on perceived performance on Face‐Name learning task (MD=‐2.43, p=498), but sad mood was associated with better perceived performance on the maze‐learning task (MD=13.34, p=.015). Results also indicated that RSFA and ME were implicated as mechanisms in subjective memory performance appraisal.ConclusionFindings indicate that SMC is a complex multifaceted phenomenon which may be underpinned by maladaptive self‐regulation and attentional systems, suggesting that psychological interventions may be appropriate for many older adults with SMC.
Longitudinal tau accumulation in cognitively normal older adults is associated with baseline age, pathology, and activation
Authors: Adams Jenna N. , Harrison Theresa M. , Maass Anne , Baker Suzanne L. , Jagust William J. 
Published: December 2021

AbstractBackgroundPredictors of longitudinal tau accumulation have not yet been fully characterized, but are critical for understanding progression from normal aging to Alzheimer’s disease (AD). We investigated whether baseline AD pathology, demographic risk factors, and activation during a memory task predicted longitudinal tau deposition in cognitively normal older adults (OA).MethodTau pathology was measured with [18F] Flortaucipir (FTP) at ≥2 time points (44 2TPs; 24 3TPs; 2 4TPs; 2.5±1.1 years follow‐up) in 70 OA (mean age 77 years, 59% female). FTP scans were processed with a longitudinal pipeline using an eroded white matter reference region. Linear mixed models were used to calculate FTP slope in entorhinal cortex (EC), inferior temporal gyrus (IT), and a MetaROI composed of AD‐vulnerable temporal regions. Aβ was measured with global PiB DVR. A subset of 37 OA received baseline fMRI while performing a memory task, and task activation (all images vs. perceptual baseline contrast) was calculated for EC and hippocampus.ResultThere was significant group‐level tau accumulation in EC, IT, and MetaROI across the full sample, and within Aβ+ and Aβ‐ groups (one‐sample t‐tests, all ps<0.001; Figure 1). Older age at baseline was specifically associated with increased FTP slope in EC (Figure 2A). Higher baseline PiB DVR was associated with increased FTP slope in EC, IT, and MetaROI (Figure 2B). ApoE ε4+ was associated with greater FTP slope in IT and MetaROI, but not EC (Figure 2C). Multiple regression models including age, sex, ApoE, and baseline EC FTP and PiB DVR showed a significant interaction between baseline EC FTP and PiB DVR, and an independent effect of ApoE ε4+, in predicting FTP slope in IT and MetaROI (predictor ps<0.01). In the subset with fMRI data, greater task activation in EC and hippocampus was associated with increased EC FTP slope (Figure 3).ConclusionAge was a specific risk factor for tau accumulation in EC, while baseline Aβ and ApoE ε4+ were related to tau accumulation in neocortical regions. Positive associations between activation and tau change within EC support theories of activity‐related tau accumulation. Our findings help elucidate potential underlying causes of tau accumulation in aging.
Prevalence of mild behavioral impairment subdomains: A meta‐analysis
Authors: Pan Yining , Shea Yat Fung , Ismail Zahinoor , Li Victor OK , Lam Jacqueline CK 
Published: December 2021

AbstractBackgroundMild behavioral impairment (MBI) is a neurobehavioral syndrome characterized by later life emergence of neuropsychiatric symptoms. Our previous meta‐analysis showed that the pooled prevalence of MBI among cognitively normal (CN), subjective cognitive impairment (SCI) and mild cognitive impairment (MCI) subjects are 17%, 35.8% and 45.5% respectively. The main aim of this study is to calculate the pooled prevalence of MBI subdomains.MethodA search of the literature on MBI in MCI, CN, and SCI and CN but at risk (CN‐AR) subjects published between 1 January 2003 and 14 January 2021 was conducted. Meta‐analysis using a random effects model was performed to determine the pooled estimate of the prevalence of MBI subdomains. Meta‐regression was performed to identify factors contributing to the variance of prevalence rate.ResultNine studies conducted among 11568 subjects (9259 CN, 1057 SCI & 1252 MCI) with retrievable subdomain data underwent meta‐analysis, revealing pooled prevalence of affective dysregulation (AFD), impulse dyscontrol (IDS), decreased motivation (DMT), social inappropriateness (SIP) and abnormal perception/ thought (APT) of 31.2% (95% CI 24.6‐38.5%), 27.9% (95% CI 22.2‐34.6%), 11.5% (95% CI 7‐g18.5%), 7.4% (95% CI 4.1‐12.9%), and 3.4% (95% CI 1.7‐6.7%) respectively. Although all subdomains demonstrate ordinal increase in pooled prevalence from CN, SCI and MCI subgroups, meta‐regression demonstrated no significant difference in subdomains prevalence among cognitive subgroups. The pooled prevalence of AFD and IDS are greater than that of SIP and APT among all cognitive subgroups. Among MCI subjects, racial group (Asian vs. Caucasians) could account for variance between the studies in prevalence of IDS (coefficient 1.5908, 95% CI 0.7850‐2.3966, R2 analogue 0.63, p<0.001).ConclusionAFD and IDS are two most prevalent MBI subdomains and remain the same with cognitive deterioration. This finding is potentially relevant to clinical practice.
Novel oddity detection task differentiates early Alzheimer’s disease and major depression
Authors: Frei Marlen , Berres Manfred , Kivisaari Sasa L , Monsch Andreas U. , Kressig Reto W. , Krumm Sabine 
Published: December 2021

AbstractBackgroundThe differentiation between early Alzheimer’s disease (AD) and Major depression (MD) is a common clinical challenge. AD‐related neurofibrillary tau‐pathology starts in the perirhinal cortex (PRC) whereas little to no neurodegeneration is found in MD. Thus, testing PRC functioning could help distinguishing these pathologies. The PRC is involved, amongst others, in visual discrimination of complex objects. We assessed the ability of a novel visual oddity detection task to differentiate adults in early stages of AD from those with MD and healthy controls (HCs).MethodParticipants had to choose the odd figure out of six highly ambiguous, simultaneously presented Kanji‐like stimuli. The sample included 28 patients in early stages of AD (8 amnestic mild cognitive impairment, 20 Alzheimer's dementia, 14 female, age = 75.74±6.72 years, education = 13.51±3.13 years, MMSE = 26.29±1.94), 26 patients with MD (14 female, age = 61.88±10.82 years, education = 13.31±3.04 years, MMSE = 28.77±1.27), and 25 HCs (11 female, age = 68.98±10.74 years, education = 14.26±3.91 years, MMSE = 29.01±1.04). As proof of concept, only AD patients showed distinct PRC thinning adjusted for age and total intracranial volume (HC vs. AD: t = ‐3.355, p = .001; HC vs. MD: t = ‐.596, p = .553). Logistic regressions were performed using demographically adjusted z‐scores of task performance.ResultIncorrect responses predicted group membership of AD vs. MD patients (odds ratio [OR] = 0.45, 95% confidence interval [CI; 0.22, 0.77], p = .011), as well as AD patients vs. HCs (OR = 0.45, 95% CI [0.22, 0.79], p = .012). Furthermore, correct responses predicted group membership of AD patients vs. HCs (OR = 0.35, 95% CI [0.16, 0.66], p = .004), but not between AD patients vs. MD (p = .11). Omitted responses did not have a distinct effect (AD vs. MD: p =.36; AD vs. HC: p = .051).ConclusionA novel oddity detection task differentiated patients in early stages of AD from MD patients and HCs. Although further validation is needed, these findings indicate that the task detects early cognitive impairment related to AD and may support differential diagnosis.