bluuebunny/crossref_metadata_2025_split huggingface dataset:
Personal history of breast cancer, cognitive function, and conversion in women from the ADNI cohort
Authors: Eastman Jennifer Ann , Yaffe Kristine , Kerlikowske Karla , Brenowitz Willa D , Kornblith Erica S , Inslicht Sabra 
Published: December 2021

AbstractBackgroundSome women with a personal history of breast cancer (PHBC) may experience higher rates of objective/subjective cancer‐related cognitive impairment (CRCI) shortly after treatment, while others have persistent CRCI as many as 20 years after. It is unclear how this impacts cognitive aging years after diagnosis. We explored whether remote PHBC is associated with a specific pattern of cognitive decline or increased dementia diagnosis rates in women.MethodWe performed secondary analysis of data from women enrolled in the Alzheimer Disease Neuroimaging Initiative (ADNI) from October, 2005 ‐ September, 2018. A review of records identified 33 cognitively normal (CN) and 20 mild cognitive impairment (MCI) participants with PHBC, and 268 CN and 270 MCI participants without PHBC. We compared overall rates of PHBC in the MCI/CN groups as well as rates of conversion to MCI (from CN) or Alzheimer’s dementia (AD). Baseline scores on cognitive tests were corrected for age, education, and sex and averaged into composite scores: Structured‐Verbal‐Memory (Logical Memory Learning/Delay) Unstructured‐Verbal‐Memory (RAVLT Learning/Delay/Recognition), Attention/Processing‐Speed (Trails A+B/Number‐Cancellation) and Language (Animal‐fluency/Boston Naming). One‐way ANOVA and χ2 examined differences in PHBC rates, cognitive performance, and dementia conversion.ResultRates of PHBC did not differ significantly between CN(11%) and MCI(7%), (p=0.08). Among women with MCI, those absent PHBC performed significantly worse than those with PHBC on Unstructured‐Verbal‐Memory (p=0.012). Follow‐up examination of individual RAVLT scores revealed intact recognition in the MCI+PHBC women. Women with MCI alone, converted to AD at significantly higher rates than MCI+PHBC (p=0.04). Cognitively normal women with/without PHBC did not differ in cognitive test performance or conversation rates.ConclusionResults suggest no increased risk of MCI or AD in women with a PHBC. In fact, women with MCI+PHBC show lower rates of conversion to AD, a pattern of memory impairment less consistent with AD, and better overall cognition relative to those with MCI alone. This may indicate that the etiology of memory problems in women with PHBC may be related to persistent CRCI rather than a neurodegenerative process like AD, but further research is needed to understand specific factors that contribute to the development of CRCI and their impact on cognitive aging.
Map of Care: 10 smart tools for the evaluation of senior care facilities
Authors: Georgarakos Manos 
Published: December 2021

AbstractBackgroundMany senior care facilities (assisted living, nursing homes, memory care) are of average quality. There is lack of reliable and impartial information on care facilities. Furthermore, most people do not have the specific knowledge to evaluate their various senior care options in order to make the right choice.MethodAn interdisciplinary team of medical doctors, neuropsychologists, senior care industry professionals and information technology/user experience specialists analyzed the needs of older adults and their relatives. These needs were mapped to characteristics of senior care facilities and online tools were developed to assess different aspects of all types of senior care facilities (assisted living, nursing homes, memory care). In addition to a general assessment tool for each facility type, specialized tools (tech tool, design for dementia tool, accessibility tool) were included and in total 10 online tools were developed. These online tools were integrated in the Map of Care online platform for senior living, which features facility locations on an interactive map along with facility reviews and ratings.ResultUsers have the opportunity, after an in‐person visit or a virtual tour of a facility, to assess, compare and finally select the most suitable facility for their needs and preferences using the available online tools. Data from users’ responses to the online tools are collected anonymously, populating the Map of Care database. Continuous processing of this data will allow for the provision of senior care analytics at facility, city, state and national level. Thus, apart from impartial rating of senior care facilities, the Map of Care ecosystem will allow for monitoring of trends, gaps and unmet needs in the field of senior care facilities.ConclusionThrough a democratic participatory process of user‐generated evaluations, reviews and ratings, Map of Care aims to empower older adults and their relatives to make informed choices about care facilities while providing vital insights to the field of senior care facilities with the overall goal of continuously improving the quality of senior care.
Reaction times of correct and incorrect performances are highly correlated no matter age groups but older age affects accuracy and speed relationships in the Wisconsin Card Sorting Test
Authors: Rosales‐Lagarde Alejandra , Martínez‐Alcalá Claudia 
Published: December 2021

AbstractBackgroundThe detection of non‐amnestic Mild Cognitive Impairment with difficult tasks as the Wisconsin Card Sorting Test (WCST) is still under debate. Associations concerning performance and/or speed are not usually evaluated even though speed decreases with age and so, the WCST may be preferentially administered in a computerized format. Therefore, 3 types of relationships were looked for: 1) between reaction times (RT) of correct and incorrect answers; 2) between the percentage of correct responses and RT of correct responses; and lastly, 3) between the percentage of incorrect responses and RT of incorrect responses.MethodTwo age groups, one group of executives of the INEGI (National Institute of Statistics, Geography and Informatics) (n = 12, 46.71 ± 5) and another one of older adults (OAs) who attended a “Centro Gerontológico Integral” in the state of Hidalgo in Mexico (n = 17, 66.35 ± 6) were evaluated.ResultThe RT of correct and incorrect performances were highly correlated for both groups (INEGI group: r = 0.80, p = 0.01; OAs: r = 0.89, p = 0.01). Instead, the correlations between performance and speed were only negatively related for the percentage of correct responses and RT of correct responses in the group of the INEGI (r = ‐ 0.72, p = 0.02), while they had a tendency to be positive in OAs although not significant (r = 0.43, p = 0.10). The percentage of incorrect responses and RT of incorrect responses was positive and significant for the group of the INEGI (r = 0.84, p = 0.01) and tended to be negative and not significant for OAs (r = ‐ 0.48, p = 0.10).ConclusionA positive correlation between RT of correct and incorrect answers was found, suggesting a consistent speed within subjects no matter the performance. A negative correlation was found for the percentage of correct responses and RT of correct responses in the group of the INEGI. However, this late relationship and the one concerning wrong performance was not confirmed for OAs, indicating that speed when decision making and problem solving are assessed suffer from severe alterations with age.
Cognitive performance in former professional football (soccer) players is affected by estimated heading frequency
Authors: Bruno Davide , Rutherford Andrew 
Published: December 2021

AbstractBackgroundThe link between football (soccer) heading and/or head injury is a concern given the popularity of football worldwide. To assess this link, memory ability of former professional footballers (FPFs) was tested, and self‐reported data on positions played, previous head injuries, and frequency of headers were obtained.MethodData were collected by post from 60 male FPFs who had played for teams in England. Each individual received a questionnaire requiring them to self‐report: demographics data; information on playing career, including playing position; information on number of head injuries sustained in training and match play; and an estimate of how many headers they normally took in training and match play. Additionally, the Test Your Memory (TYM) self‐administered memory test also was included. FPFs mean age was 67.5 (9.5), ranging from 39 to 87.ResultBayesian and traditional (frequentist) regression analyses were carried out using the TYM score as outcome (continuous and binary). Age and estimated non‐football head injuries served as covariates (null model). Predictors were playing position, estimated career head injuries, and estimated career headers. As playing position influences likelihood of heading the ball, a rating score was co‐designed with FPFs ranging from 1 (not likely, e.g., goal‐keeper) to 5 (most likely, e.g., centre‐forward). The results of our analyses showed across all tests that estimated career headers, but not playing position or estimated career head injuries, were associated with the overall cognitive outcome. We calculated from our data that the TYM score declined by about 3 points for each 100,000 career headers reported.ConclusionThis is the first study, to our knowledge, to provide evidence in former professional football players that heading the ball may impact cognitive ability.
Reviewing the development of national dementia plans: Implications for Vietnam
Authors: Nguyen Tuan Anh , Tran Kham , Esterman Adrian , Brodaty Henry , Hinton Ladson , Dang Thu Ha , Kurrle Sue , Hoang Phuong , Crotty Maria , Pham Thang , Kim Giang Bao , Le Pham Tuan , Roughead Elizabeth E 
Published: December 2021

AbstractBackgroundVietnam, a country with a rapidly ageing population, is a member of the World Health Organization (WHO) and agreed to develop a national dementia plan consistent with the WHO’s guidelines in 2018. Recently, steps towards this plan have been implemented with national workshops and the development of research activities related to dementia. This paper reviews 32 national dementia plans (NDPs), based on the WHO’s guideline and WHO’s Global Dementia Observatory’s indicators (GDO), to inform the Vietnamese plan.MethodsData were extracted from 32 NDPs identified from the Alzheimer’s Disease International’s website regarding the vision, mission, objectives, framework, principles, priorities, stakeholders, budget, implementation and evaluation. We compared the plans using the WHO’s guideline and GDO.ResultsMost NDPs were from high‐income countries with only two from middle‐income countries and one from a low‐income country. Overarching visions encompassed improving the quality of life for persons with dementia. Principles covered respect, dignity, accessibility and equity. All plans addressed the seven priority areas advocated by the WHO, but differences in priorities were aligned with national situational analyses. There were similarities across NDPs: to improve awareness of dementia, reduce stigma, develop support services, improve quality of care, improve training and education, and improve dementia research. The process of developing the NDPs involved stakeholders including persons with dementia and their carers, civil society, central government units, state or provincial representatives, older people, disability associations, and local non‐governmental and international organisations.ConclusionThis review provides an important resource for countries yet to develop their national dementia plans, both on plan content, the process of development, implementation and evaluation.
Prediction of conversion to dementia in subjects with amnestic mild cognitive impairment with interpretable machine learning
Authors: Chun Min Young , Kim JongHyuk , Jang Hyemin , Kim Kyunga , Seo Sang Won 
Published: December 2021

AbstractBackgroundMild cognitive impairment (MCI), especially the amnestic form, is considered a transitional state between normal aging and Alzheimer's disease (AD). However, not all amnestic MCI (aMCI) patients progress to AD. Thus, developing a predictive model for AD progression in aMCI patients has been considered important. Prametric methods such as logistic regression have been developed, but it is difficult to reflect complex patterns such as nonlinear relationships and interactions between variables. This study aims to improve the predictive power of aMCI patients' conversion to dementia by using an interpretable machine learning (IML) model and to identify factors that increase the risk of individual dementia conversion in each patient.MethodWe obtained 760 aMCI patients, who had been followed at least three years after baseline neuropsychological tests from Samsung Medical Center from 2007 to 2019. We used neuropsychological tests and apolipoprotein E (APOE) genotype data for developing predictive models. Model building and model validation data sets were composed of 565 and 140 patients, respectively. For global interpretation, four models of logistic regression, random forest, support vector machine, and extreme gradient boost were compared. For local interpretation, individual conditional expectations (ICE) and SHapley Additive exPlanations (SHAP) were used to analyze individual patients.ResultAmong 4 models, the extreme gradient boost model showed the best performance with an AUC of 0.83, an accuracy of 0.76, and an f1‐score of 0.65. The variables such as RCFT‐DR, CDR‐SOB, age, K‐MMSE, COWAT‐animal, education, SVLT‐DR, RCFT‐copy time, and APOE genotype were important features for creating the model. Through ICE and SHAP analysis, it was also possible to interpret which variables acted as strong factors for each patient.ConclusionThe present study developed a model for predicting dementia conversion in aMCI patients using IML technique. This predictive IML model is expected to be useful in clinical practice and research field as it can suggest conversion with high accuracy and identify the degree of influence of risk factors for each patient.
The care ecosystem: Outcomes from an integrated healthcare system
Authors: Rosenbloom Michael H , Hanson Leah R , Diaz‐Ochoa Ana , Svitak Aleta , Brombach Ann , Finstad Jennifer , Karrmann Jan , Barclay Michelle , Dulaney Sarah , Possin Kate 
Published: December 2021

AbstractBackgroundThe Care Ecosystem (CE) is a model of dementia care consisting of a multidisciplinary team of nursing, care team navigators (CTNs), and social workers designed to support persons with dementia (PWD) and their caregivers. Developed and tested at the UCSF Memory and Aging Center, the CE has been shown to improve PWD quality of life, reduce emergency department visits, and decrease caregiver depression/burden compared to usual care. We present CE data from a high volume neurology clinic within an integrated healthcare system.MethodA total of 435 patient‐caregiver dyads were enrolled in the CE over a 2.5 year period. Data relating to demographics, dementia severity, caregiver burden, and healthcare utilization were collected at baseline and after one year (n=116). Experience surveys were completed by dyads at 6 and 12 months (n=200). A retrospective review of data captured by RedCap and the electronic medical record was performed.ResultThere was worsening of dementia disease severity (DSRS) and functional impairment (FAQ) over a one year period (figure 1a/b). Both immediate/anticipated caregiver needs (figure 2) and safety concerns (figure 3) decreased over time. For safety, there were particular sizable reduction of caregiver safety concerns for driving (65%), falls (52%), problems getting lost (57%), weight and appetite changes (63%), and medication safety concern (61%) for the PWD. There was a reduction in the number of PWD using >10 medications with the CE (figure 4). The number of ED visits decreased over time whereas hospitalizations increased over the one year (figure 5a/5b). There was a reduction in caregiver depression, difficulty, and burden (6a/b/c). Dyads rated CTNs favorably ranging from 88‐92% of the time.ConclusionOur results suggest that the CE is feasible and effective in an integrated healthcare system setting. Despite worsening of disease state in the PWD, caregiver burden and distress decreased over the one year assessment period, suggesting a favorable impact on caregiver quality of life. PWD and caregivers rated the CTN experience positively. Although these preliminary results favor the CE, further studies are necessary to better understand the impact of the CE on healthcare utilization in integrated healthcare systems.
Differential impact of obstructive sleep apnea on hippocampal structure in late middle‐aged and older women and men
Authors: Martineau‐Dussault Marie‐Ève , André Claire , Daneault Véronique , Blais Hélène , Petit Dominique , Lorrain Dominique , Bastien Célyne , Hudon Carol , Descoteaux Maxime , Montplaisir Jacques , Boré Arnaud , Theaud Guillaume , Thompson Cynthia , Legault Julie , Martinez Guillermo E. , Gilbert Danielle , Carrier Julie , Gosselin Nadia 
Published: December 2021

AbstractBackgroundRecent studies have suggested that obstructive sleep apnea (OSA) could be a modifiable risk factor for dementia. Consequently, efforts have been made to better understand the role of OSA on brain structure integrity, but results between studies are inconsistent. Discrepancies could be partly due to moderating factors (e.g., sex) or complex physiological mechanisms (e.g., oedema) that blur the association between OSA and brain structure. Here, we investigated the association between OSA severity and hippocampal grey matter volume in women and men. We also performed free‐water fraction analyses to understand how oedema could impact hippocampal volumes.MethodSeventy‐three men (age: 65.47±7.22 years; apnea‐hypopnea index [AHI]: 15.52±16.14 events/h; 31 with mild cognitive impairments [MCI]) and 47 women (age: 71.11 ± 6.65; AHI: 11.56 ± 9.92; 22 with MCI) underwent an overnight polysomnography, a neuropsychological evaluation and a magnetic resonance imaging session. Using the hippocampal subfield module in Freesurfer 7.1, total bilateral hippocampal volumes were extracted and normalised to the total intracranial volume. Diffusion data was preprocessed using TractoFlow‐ABS, and Freewater‐Flow and the Sherbrooke Connectivity Imaging Lab scripts were used to extract bilateral hippocampal free‐water fraction. Controlling for age and cognitive status, sex‐stratified linear regressions were performed between (i) the bilateral hippocampal volume or (ii) Free‐water‐corrected bilateral hippocampal volume and log‐transformed AHI.ResultIn women, we observed a positive association between the AHI and bilateral hippocampal volumes (r=0.414; p=0.005), where more severe OSA was associated with higher volumes. This association was not observed in men (p=0.427). When using the free‐water corrected volumes, this association was no longer significant in women (p=0.481), suggesting that the increased hippocampal volume could be due to OSA‐related cytotoxic (intracellular) oedema.ConclusionIn this cohort, while men’s hippocampal volume was unaffected by OSA, women with OSA presented hippocampal hypertrophy likely due to intracellular oedema. Cytotoxic oedema is a known precursor to vasogenic (extracellular) oedema and cell death, suggesting that women might be more vulnerable to the cerebral consequences of OSA than men. Since women have a higher lifetime risk of developing Alzheimer's disease, future studies on OSA should pay a particular attention to women.
Increased adiposity is related to reduced neurite complexity in the hippocampus, fornix, and uncinate fasciculus of cognitively unimpaired adults
Authors: Noughani Hanna M , Ennis Gilda E , Vogt Nicholas M , Johnson Sterling C , Asthana Sanjay , Alexander Andrew L , Beeri Michal Schnaider , Bendlin Barbara B 
Published: December 2021

AbstractBackgroundObesity is a risk factor for dementia. However, results from studies associating obesity to volume in the hippocampus and parahippocampal gyrus, regions underpinning memory, are inconsistent. Null findings could be due to the insensitivity of volumetric MRI to detect early neurodegenerative change. The neurite orientation dispersion and density imaging (NODDI) model provides unique information about neurite microstructure that may be relevant to the earliest stages of neurodegeneration. In cognitively healthy participants, we used NODDI to examine if body mass index (BMI) and waist circumference (WC) were related to the microstructure of the hippocampus and parahippocampal gyrus and white matter (WM) tracts linking these gray matter (GM) regions to the brain (i.e., hippocampal cingulum, uncinate fasciculus, and fornix).MethodParticipants were enrolled in the Wisconsin Alzheimer’s Disease Research Center (ADRC) Clinical Core, had T‐1 weighted and multi‐shell diffusion MRI, and lacked history of stroke and cognitive impairment (Table 1). Microstructure was assessed using neurite density (NDI) and orientation dispersion (ODI) indices obtained from the NODDI model. Higher NDI indicates higher neurite density; higher ODI reflects lower neurite coherence and greater neurite dispersion. N=383 had NODDI indices, height, weight and covariate data. Waist circumference (WC) (n=382) was dichotomized according to sex‐specific thresholds for cardiovascular/diabetes disease risk (females >88cm; males >102cm). Linear regression tested the relationship of BMI and WC to NDI and ODI in regions of interest controlling for age, sex, education, diabetes, hypertension, depression, and APOE4 carrier status.ResultIndividuals with higher BMI and in the higher‐risk WC category had significantly lower hippocampal ODI and fornix NDI when adjusting for covariates (Table 2, Figure 1). Higher BMI was also related to higher uncinate fasciculus ODI.ConclusionIncreased adiposity was related to lower neurite dispersion in the hippocampus and lower neurite density in the fornix. BMI alone was associated with lower neurite coherence in the uncinate fasciculus. These results suggest that increased adiposity may be related to less complex neurite microstructure in regions important for memory. Additional research is needed to determine if adiposity‐related microstructural differences in GM and WM are related to memory decline and presage future development of dementia.