Classification Prediction of Alzheimer's Disease and Vascular Dementia Using Physiological Data and ECD SPECT Images.

Alzheimer's disease (AD) and vascular dementia (VaD) are the two most common forms of dementia. However, their neuropsychological and pathological features often overlap, making it difficult to distinguish between AD and VaD. In addition to clinical consultation and laboratory examinations, clinical dementia diagnosis in Taiwan will also include Tc-99m-ECD SPECT imaging examination. Through machine learning and deep learning technology, we explored the feasibility of using the above clinical practice data to distinguish AD and VaD. We used the physiological data (33 features) and Tc-99m-ECD SPECT images of 112 AD patients and 85 VaD patients in the Taiwanese Nuclear Medicine Brain Image Database to train the classification model. The results, after filtering by the number of SVM RFE 5-fold features, show that the average accuracy of physiological data in distinguishing AD/VaD is 81.22% and the AUC is 0.836; the average accuracy of training images using the Inception V3 model is 85% and the AUC is 0.95. Finally, Grad-CAM heatmap was used to visualize the areas of concern of the model and compared with the SPM analysis method to further understand the differences. This research method can quickly use machine learning and deep learning models to automatically extract image features based on a small amount of general clinical data to objectively distinguish AD and VaD.

The feasibility and practicality of auxiliary detection of spatial navigation impairment in patients with mild cognitive impairment due to Alzheimer's disease by using virtual reality.

Background: Spatial disorientation in patients with mild cognitive impairment due to Alzheimer's disease (MCI due to AD) has become a subject of great interest. Medical practitioners are concerned about the serious issue of these patients who are getting lost. Therefore, the early detection of MCI due to AD is crucial. New methods: We designed virtual reality (VR) protocols to test spatial recognition abilities. Our devices mainly included the Vive Pro Eye and the Steam VR program. We tested the three groups: young cognitively unimpaired (YCU), older cognitively unimpaired (OCU) and MCI due to AD. We also administered the Cognitive Abilities Screening Instrument and the Questionnaire on Everyday Navigational Ability for comparison. Results: We adopted the testing results of 2 YCU, 3 OCU, and 4 MCI due to AD for analysis. Concerning cognitive abilities, YCU and OCU had better performance than MCI due to AD respectively. It was consistent with the recent memory and the total scores of the Cognitive Abilities Screening Instrument. Comparison with existing methods: We introduced a real-life setting, the Tzu-Chiang campus at National Cheng Kung University, into the VR environment. It allowed us to assess daily road-recognizing abilities of participants in a controlled testing environment. Conclusions: Several limitations were considered in this study, such as limited number of participants and low-quality images on the screen. Nonetheless, this device has the potential to serve as a screening tool for MCI due to AD based on its feasibility and practicality.

Application of blood-based biomarkers of Alzheimer's disease in clinical practice: Recommendations from Taiwan Dementia Society.

Blood-based biomarkers (BBM) are potentially powerful tools that assist in the biological diagnosis of Alzheimer's disease (AD) in vivo with minimal invasiveness, relatively low cost, and good accessibility. This review summarizes current evidence for using BBMs in AD, focusing on amyloid, tau, and biomarkers for neurodegeneration. Blood-based phosphorylated tau and the Aß42/Aß40 ratio showed consistent concordance with brain pathology measured by CSF or PET in the research setting. In addition, glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) are neurodegenerative biomarkers that show the potential to assist in the differential diagnosis of AD. Other pathology-specific biomarkers, such as α-synuclein and TAR DNA-binding protein 43 (TDP-43), can potentially detect AD concurrent pathology. Based on current evidence, the working group from the Taiwan Dementia Society (TDS) achieved consensus recommendations on the appropriate use of BBMs for AD in clinical practice. BBMs may assist clinical diagnosis and prognosis in AD subjects with cognitive symptoms; however, the results should be interpreted by dementia specialists and combining biochemical, neuropsychological, and neuroimaging information. Further studies are needed to evaluate BBMs' real-world performance and potential impact on clinical decision-making.

Driving practice effects for older drivers with mild cognitive impairment: A preliminary study.

BACKGROUND: Older drivers with mild cognitive impairment (MCI) often show declining driving performance. Evidence is lacking regarding whether their driving skills can be improved after practice. AIMS/OBJECTIVES: To compare the practice effects of older drivers with MCI and drivers with normal cognition in an unfamiliar, standardized driving course with three practices. MATERIALS AND METHODS: Single-blind two-group observational design. Twelve drivers with confirmed MCI as the experimental group and ten with normal cognition (NC) as the control, all ≥ 55 years old. The primary outcome was to assess the practice effects, measured with an in-car global-positioning-system mobile application to compare the speed and directional control of a complex manoeuvre after practices. Secondary outcomes were to assess the pass/fail rate and mistakes observed for the 3rd/final on-road driving practice. No instructions were given during practice. Descriptive statistics and the Mann-Whitney U test were used for data analysis. RESULTS: No significant inter-group difference in the pass/fail rate and number of mistakes. Some MCI drivers performed better in the speed and directional control of the S-Bend manoeuvre after practices. CONCLUSIONS: The driving performance of drivers with MCI may improve with practice. SIGNIFICANCE: Older drivers with MCI may potentially benefit from driver retraining. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov (Identifier: NCT04648735).

The Effect of Agomelatine in Behavioral and Psychological Symptoms of Dementia.

Objective: Moderate and severe behavioral and psychological symptoms of dementia (BPSD) often need medical treatment to improve symptoms. Agomelatine is a selective melatonergic (MT1/MT2) agonist that has normalizing effects on disturbed circadian rhythms and disrupted sleep-wake cycles. Its activity of 5HT-2C receptor antagonism is associated with lessening depression and anxiety and increasing slow-wave sleep. Based on past clinical records and current findings it suggests that agomelatine can improve BPSD for patients. This retrospective cohort study was designed to compare the BPSD before and after using agomelatine. Methods: Records of dementia cases who had ever received agomelatine treatment for BPSD in a general hospital setting during the past 2.5 years were identified and reviewed. Scores from before and after 3 months of treatment with agomelatine were collected for Neuropsychiatric Inventory (NPI), Brief Psychiatric Rating Scale (BPRS), and Clinical Global Impression (CGI) to compare and analyze the difference of psychological and behavioral symptoms pre- and post-agomelatine used. Results: Records of 144 cases of dementia with BPSD who had ever used agomelatine from January 2015 to June 2017 were collected. All of the 112 cases had BPRS and CGI scores, of which 75 cases had additional NPI scores. Among these 112 cases, the BPRS and CGI scores were significantly improved in all types of dementia. NPI scores indicated that the use of agomelatine alleviated obvious symptoms and decreased overall distress, especially in the depression/poor mood, anxiety, and sleep/night behavior. Conclusion: It is consistent with an effective result of agomelatine in improving BPSD.

Evidence of plasma biomarkers indicating high risk of dementia in cognitively normal subjects.

Subjects with comorbidities are at risk for neurodegeneration. There is a lack of a direct relationship between comorbidities and neurodegeneration. In this study, immunomagnetic reduction (IMR) assays were utilized to assay plasma Aß1-42 and total tau protein (T-Tau) levels in poststroke (PS, n = 27), family history of Alzheimer's disease (ADFH, n = 35), diabetes (n = 21), end-stage renal disease (ESRD, n = 41), obstructive sleep apnea (OSA, n = 20), Alzheimer's disease (AD, n = 65). Thirty-seven healthy controls (HCs) were enrolled. The measured concentrations of plasma Aß1-42 were 14.26 ± 1.42, 15.43 ± 1.76, 15.52 ± 1.60, 16.15 ± 1.05, 16.52 ± 0.59, 15.97 ± 0.54 and 20.06 ± 3.09 pg/mL in HC, PS, ADFH, diabetes, ESRD, OSA and AD groups, respectively. The corresponding concentrations of plasma T-Tau were 15.13 ± 3.62, 19.29 ± 8.01, 17.93 ± 6.26, 19.74 ± 2.92, 21.54 ± 2.72, 20.17 ± 2.77 and 41.24 ± 14.64 pg/mL. The plasma levels of Aß1-42 and T-Tau in were significantly higher in the PS, ADFH, diabetes, ESRD and OSA groups than controls (Aß1-42 in PS: 15.43 ± 1.76 pg/mL vs. 14.26 ± 1.42 pg/mL, p < 0.005; T-Tau in PS: 19.29 ± 8.01 vs. 15.13 ± 3.62 pg/mL, p < 0.005, Aß1-42 in ADFH: 15.52 ± 1.60 pg/mL vs. 14.26 ± 1.42 pg/mL, p < 0.001; T-Tau in ADFH: 17.93 ± 6.26 vs. 15.13 ± 3.62 pg/mL, p < 0.005, Aß1-42 in diabetes: 16.15 ± 1.05 pg/mL vs. 14.26 ± 1.42 pg/mL, p < 0.001; T-Tau in diabetes: 19.74 ± 2.92 vs. 15.13 ± 3.62 pg/mL, p < 0.001, Aß1-42 in ESRD: 16.52 ± 0.59 pg/mL vs. 14.26 ± 1.42 pg/mL, p < 0.001; T-Tau in ESRD: 21.54 ± 2.72 vs. 15.13 ± 3.62 pg/mL, p < 0.001, Aß1-42 in OSA: 15.97 ± 0.54 pg/mL vs. 14.26 ± 1.42 pg/mL, p < 0.001; T-Tau in OSA: 20.17 ± 2.77 vs. 15.13 ± 3.62 pg/mL, p < 0.001). This evidence indicates the high risk for dementia in these groups from the perspective of plasma biomarkers.

The application of a neuropsychological measure of executive working memory in older adults with memory impairment.

The component of working memory that the frontal cortex subserves is frequently characterized as the executive working memory (EWM). This study applied a neuropsychological measure of EWM (NPM-EWM) in older adults with memory impairment to investigate the EWM. Thirty-two older adults from the community were recruited as older healthy controls (OHCs), and 58 older adults from a memory clinic were diagnosed with mild cognitive impairment (MCI) and mild dementia (MD). Significant differences were found among the three groups in the Clinical Dementia Rating (CDR), the Chinese version of Mini-Mental State Examination (MMSE-C), and the Cognitive Abilities Screening Instrument (CASI). The NPM-EWM was applied by using the learning task of the Comprehensive Nonverbal Memory Test Battery, where the 7 scores were divided into two categories: mnemonic capacity and executive error. All OHCs, more than 50% MCI, and less than 25% of MD patients passed the NPM-EWM. The MCI-passed and MD-passed subgroups showed similar mnemonic capacity and executive errors, and both the subgroups had significantly worse performance than the OHC group. The MD-passed subgroup had a higher Hamilton Depression Rating Scale (HDRS) score than did the MD-failed subgroup. The MCI-failed subgroup had a higher Hierarchy of Care Required (HCR) level in instrumental activities of daily living (IADL) than did the MCI-passed subgroup. These findings indicated that applying the NPM-EWM for older adults with memory impairment may offer precise and tailored care to a whole person, especially for the MCI patients with poorer EWM and the MD patients with relatively intact EWM.

Assessment of High Risk for Alzheimer's Disease Using Plasma Biomarkers in Subjects with Normal Cognition in Taiwan: A Preliminary Study.

BACKGROUND: In Alzheimer's disease (AD), cognitive impairment begins 10-15 years later than neurodegeneration in the brain. Plasma biomarkers are promising candidates for assessing neurodegeneration in people with normal cognition. It has been reported that subjects with the concentration of plasma amyloid-ß 1-42×total tau protein higher than 455 pg2/ml2 are assessed as having a high risk of amnesic mild impairment or AD, denoted as high risk of AD (HRAD). OBJECTIVE: The prevalence of high-risk for dementia in cognitively normal controls is explored by assaying plasma biomarkers. METHODS: 422 subjects with normal cognition were enrolled around Taiwan. Plasma Aß1-40, Aß1-42, and T-Tau levels were assayed using immunomagnetic reduction to assess the risk of dementia. RESULTS: The results showed that 4.6% of young adults (age: 20-44 years), 8.5% of middle-aged adults (age: 45-64 years), and 7.3% of elderly adults (age: 65-90 years) had HRAD. The percentage of individuals with HRAD dramatically increased in middle-aged and elderly adults compared to young adults. CONCLUSION: The percentage of HRAD in cognitively normal subjects are approximately 10%, which reveals that the potentially public-health problem of AD in normal population. Although the subject having abnormal levels of Aß or tau is not definitely going on to develop cognitive declines or AD, the risk of suffering cognitive impairment in future is relatively high. Suitable managements are suggested for these high-risk cognitively normal population. Worth noting, attention should be paid to preventing cognitive impairment due to AD, not only in elderly adults but also middle-aged adults.

The Feasibility of Differentiating Lewy Body Dementia and Alzheimer's Disease by Deep Learning Using ECD SPECT Images.

The correct differential diagnosis of dementia has an important impact on patient treatment and follow-up care strategies. Tc-99m-ECD SPECT imaging, which is low cost and accessible in general clinics, is used to identify the two common types of dementia, Alzheimer's disease (AD) and Lewy body dementia (LBD). Two-stage transfer learning technology and reducing model complexity based on the ResNet-50 model were performed using the ImageNet data set and ADNI database. To improve training accuracy, the three-dimensional image was reorganized into three sets of two-dimensional images for data augmentation and ensemble learning, then the performance of various deep learning models for Tc-99m-ECD SPECT images to distinguish AD/normal cognition (NC), LBD/NC, and AD/LBD were investigated. In the AD/NC, LBD/NC, and AD/LBD tasks, the AUC values were around 0.94, 0.95, and 0.74, regardless of training models, with an accuracy of 90%, 87%, and 71%, and F1 scores of 89%, 86%, and 76% in the best cases. The use of transfer learning and a modified model resulted in better prediction results, increasing the accuracy by 32% for AD/NC. The proposed method is practical and could rapidly utilize a deep learning model to automatically extract image features based on a small number of SPECT brain perfusion images in general clinics to objectively distinguish AD and LBD.

Time Perception in Prodromal Alzheimer's Dementia and in Prodromal Dementia With Lewy Bodies.

Background: Time perception is a subjective experience or sense of time. Previous studies have shown that Alzheimer's dementia (AD) patients have time perception deficits compared to a cognitively unimpaired control group (CU). There are only a few studies on dementia with Lewy bodies (DLB) patients' time perception in comparison with CU and AD patients. Early intervention and prescription of the right medicine may delay the deterioration of AD and DLB, moreover, knowing how prodromal AD (prAD) and prodromal DLB's (prDLB) time perception differ from each other might be helpful for future understanding of these two dementias. Therefore, the purpose of this study is to explore the difference in time perception performance between prodromal AD and prodromal DLB. Methods: We invited people diagnosed with prAD, prDLB, and CU to participate in this study. Tests of verbal estimation of time and time interval production were used to assess their time perception. We analyzed the average time estimation (ATE), absolute error score (ABS), coefficient of variance (CV), and subjective temporal unit (STU) within the three groups. Results: A total of 40 prAD, 30 prDLB, and 47 CU completed the study. In the verbal estimation test, the CV for the prAD was higher than both prDLB and CU at the 9 s interval, and the CV of prAD was higher than CU at the 27 s interval. In the time interval production test, the subjective time units of prDLB were higher than prAD at the 10 s interval, while those of both prDLB and CU were higher than prAD at the 30 s interval. The percentage of subjects with STU < 1.0 s, indicating overestimation, was higher in prAD than both prDLB and CU. Conclusion: Time perception of prAD patients showed imprecision and overestimation of time, while prDLB tended to underestimate time intervals. No significant difference was found in accuracy among the three groups. It is speculated that the clinical and pathological severity of the two prodromal dementia stages may be different, and some patients have not yet had their time perception affected.

Detection of Alzheimer's disease using ECD SPECT images by transfer learning from FDG PET.

OBJECTIVE: To develop a practical method to rapidly utilize a deep learning model to automatically extract image features based on a small number of SPECT brain perfusion images in general clinics to objectively evaluate Alzheimer's disease (AD). METHODS: For the properties of low cost and convenient access in general clinics, Tc-99-ECD SPECT imaging data in brain perfusion detection was used in this study for AD detection. Two-stage transfer learning based on the Inception v3 network model was performed using the ImageNet dataset and ADNI database. To improve training accuracy, the three-dimensional image was reorganized into three sets of two-dimensional images for data augmentation and ensemble learning. The effect of pre-training parameters for Tc-99m-ECD SPECT image to distinguish AD from normal cognition (NC) was investigated, as well as the effect of the sample size of F-18-FDG PET images used in pre-training. The same model was also fine-tuned for the prediction of the MMSE score from the Tc-99m-ECD SPECT image. RESULTS: The AUC values of w/wo pre-training parameters for Tc-99m-ECD SPECT image to distinguish AD from NC were 0.86 and 0.90. The sensitivity, specificity, precision, accuracy, and F1 score were 100%, 75%, 76%, 86%, and 86%, respectively for the training model with 1000 cases of F-18-FDG PET image for pre-training. The AUC values for various sample sizes of the training dataset (100, 200, 400, 800, 1000 cases) for pre-training were 0.86, 0.91, 0.95, 0.97, and 0.97. Regardless of the pre-training condition ECD dataset used, the AUC value was greater than 0.85. Finally, predicting cognitive scores and MMSE scores correlated (R2 = 0.7072). CONCLUSIONS: With the ADNI pre-trained model, the sensitivity and accuracy of the proposed deep learning model using SPECT ECD perfusion images to differentiate AD from NC were increased by approximately 30% and 10%, respectively. Our study indicated that the model trained on PET FDG metabolic imaging for the same disease could be transferred to a small sample of SPECT cerebral perfusion images. This model will contribute to the practicality of SPECT cerebral perfusion images using deep learning technology to objectively recognize AD.

Neuroimage Biomarker Identification of the Conversion of Mild Cognitive Impairment to Alzheimer's Disease.

An efficient method to identify whether mild cognitive impairment (MCI) has progressed to Alzheimer's disease (AD) will be beneficial to patient care. Previous studies have shown that magnetic resonance imaging (MRI) has enabled the assessment of AD progression based on imaging findings. The present work aimed to establish an algorithm based on three features, namely, volume, surface area, and surface curvature within the hippocampal subfields, to model variations, including atrophy and structural changes to the cortical surface. In this study, a new biomarker, the ratio of principal curvatures (RPC), was proposed to characterize the folding patterns of the cortical gyrus and sulcus. Along with volumes and surface areas, these morphological features associated with the hippocampal subfields were assessed in terms of their sensitivity to the changes in cognitive capacity by two different feature selection methods. Either the extracted features were statistically significantly different, or the features were selected through a random forest model. The identified subfields and their structural indices that are sensitive to the changes characteristic of the progression from MCI to AD were further assessed with a multilayer perceptron classifier to help facilitate the diagnosis. The accuracy of the classification based on the proposed method to distinguish whether a MCI patient enters the AD stage amounted to 79.95%, solely using the information from the features selected by a logical feature selection method.

A cross-sectional examination of a family history of Alzheimer's disease and ApoE epsilon 4 on physical fitness, molecular biomarkers, and neurocognitive performance.

PURPOSE: The present study examined whether the ɛ4 allele of the apolipoprotein E (ApoE) gene impacts molecular biomarkers and neurocognitive performance among individuals at genetic risk for developing Alzheimer's disease (AD). The correlations between physical fitness and molecular/neurocognitive indices were also explored. METHODS: Fasting blood samples were collected from 162 individuals with a family history of AD (ADFH). There were twenty-two carriers of the ApoE-4 variant (ApoE-4 group). For comparison purposes we randomly selected 22 non-ɛ4 carriers (non-ApoE-4 group) from the ADFH individuals. Circulating inflammatory cytokines (e.g., TNF-α, IL-1ß, IL-6, IL-8, and IL-15), neuroprotective growth factors (e.g., BDNF, IGF-1, IGF-2, VEGF, and FGF-2), and Amyloid-ß peptides (e.g., Aß1-40 and Aß1-42), neurocognitive performance [e.g., behavior and brain even-related potentials (ERP)] during a task-switching paradigm, as well as physical fitness scores were measured. RESULTS: The ApoE-4 group relative to the non-ApoE-4 group was similar with respect to molecular biomarkers, physical fitness, and most measures of neurocognitive performance. However, ADFH individuals that were ɛ4 carriers exhibited significantly higher local switching accuracy costs, worse accuracy as well as smaller ERP P3 amplitudes for the memory-switching condition. Importantly, cardiorespiratory fitness levels were significantly correlated with accuracy for most task-switching conditions, and levels of BDNF, Aß1-40, and Aß1-42 collapsed across the two groups even when controlling for the age co-variable, while the ApoE-4 group revealed similar pattern of results. CONCLUSIONS: These data suggest that individuals with ADFH that were carriers of the ApoE-4 variant performed worse on the task-switching paradigm and that this could be due to compromised task-set and memory updating processes. Physical exercise interventions aimed to enhance cardiorespiratory fitness levels could be a potential AD prevention strategy for ameliorating cognitive function and reducing the accumulation of the Aß peptides in this high risk group.

Circulating levels of Irisin in obese individuals at genetic risk for Alzheimer's disease: Correlations with amyloid-ß, metabolic, and neurocognitive indices.

Irisin is involved in various metabolic pathways and is suggested to be a potential agent capable of preventing onset of Alzheimer's disease (AD) and ameliorating AD neuropathology and cognitive deficits. In the present study, the serum levels of Irisin and Amyloid-ß (Aß) peptides and the neurocognitive performance among obese individuals at genetic risk for AD were investigated. The correlations between Irisin and AD-related neuropathological and neurocognitive indices were also explored. Thirty-two individuals with a family history of AD (ADFH) and obesity (ADFH-obesity group) and 32 controls (ADFH-non-obesity group) were recruited. Circulating levels of Irisin, Aß peptides, and metabolic biomarkers, as well as neurocognitive performance [e.g., behavior and brain even-related potentials (ERP)] were measured during a visuospatial working memory task. Although the ADFH-obesity group exhibited comparable reaction times, ERP N2 latency and amplitudes, and P3 latency as compared to the ADFH-non-obesity group when performing the cognitive task, they exhibited significantly lower rates of accuracy and smaller P3 amplitudes in the higher memory-load condition, even when controlling for the blood pressure and cardiorespiratory fitness co-variables. The serum levels of leptin, insulin, and glucose, and HOMA-IR were significantly higher in the ADFH-obesity group relative to the ADFH-non-obesity group, but this was not the case for the levels of Aß1-40 and Aß1-42. The Irisin levels approached between-group significance. Partial correlations adjusting for cardiorespiratory fitness and blood pressure showed that Irisin levels were positively associated with neurophysiological (i.e., P3 amplitude) performance in the ADFH-obesity group. The Irisin levels were not significantly correlated with the levels of Aß1-40 and Aß1-42. The present findings suggest that ADFH individuals with obesity exhibited neurocognitive deficits when performing the visuospatial working memory task, and serum Irisin levels could be one of the influencing factors. However, the relationship between the circulating levels of Irisin and Aß peptides needs more evidence to support this assumption.

Have I Been Here? Sense of Location in People With Alzheimer's Disease.

Background: When navigating in a particular space, a sense of being at a current location is of great help for the navigators in reaching their destination or getting back to the start. To accomplish this work, interwoven neural structures and neurons are called into play. This system is called the heading direction cell-place cell-grid cell circuit. Evidence from various neuroscience studies has revealed that the regions responsible for this circuit are damaged in the early stages of Alzheimer's disease (AD). This may explain why wayfinding difficulty is one of the most frequent symptoms in persons with AD. The aim of this study was to examine the sense of location (SoL) in persons with mild AD, persons with prodromal AD (prAD), and those who were cognitively unimpaired (CU). Methods: We invited people with mild AD, prAD, and CU to participate in this study. The venue of the core experiment to assess SoL was a 660-m path located on the university campus. The participants were instructed to take a walk on the path and press a device to indicate their arrival at each of the five carefully chosen targets. The linear deviations from the target site were compared among the groups. Results: A total of 20 AD, 28 prAD, and 29 CU persons completed the study. Their Mini-Mental State Examination scores were on average 20 (SD 3), 24 (SD 3), and 28 (SD 2). The groups were well differentiated regarding several measurements for cognitive ability and spatial navigation. As for the SoL, the hit rates of exact location with linear deviation of 16 m or less were 0.05, 0.54, and 0.86 for AD, prAD, and CU persons, respectively. The hit rates were well correlated with the presence of getting lost. Also, SoL differentiated well among CU, PrAD, and AD in terms of average linear deviation. Conclusions: Our employing linear deviation by utilizing a grid-cell function device as an assessment for SoL showed distinct features among the three groups. This model can be used to develop more delicate devices or instruments to detect, monitor, and aid spatial navigation in persons with prAD and AD.

Tackling challenges in care of Alzheimer's disease and other dementias amid the COVID-19 pandemic, now and in the future.

We have provided an overview on the profound impact of COVID-19 upon older people with Alzheimer's disease and other dementias and the challenges encountered in our management of dementia in different health-care settings, including hospital, out-patient, care homes, and the community during the COVID-19 pandemic. We have also proposed a conceptual framework and practical suggestions for health-care providers in tackling these challenges, which can also apply to the care of older people in general, with or without other neurological diseases, such as stroke or parkinsonism. We believe this review will provide strategic directions and set standards for health-care leaders in dementia, including governmental bodies around the world in coordinating emergency response plans for protecting and caring for older people with dementia amid the COIVD-19 outbreak, which is likely to continue at varying severity in different regions around the world in the medium term.

[Development and Psychometric Validation of a Tool for Assessing the Care Needs of Families of Patients With Dementia].

BACKGROUND: The rapid aging of the global population has sharply increased the prevalence of dementia. Most people with dementia (PwD) live at home and are cared for by family caregivers. The complicated care needs of PwD and family caregivers necessitate the provision of comprehensive and transdisciplinary assessment and service support. PURPOSE: The purpose of this study was to construct the contents of the "Assessment Tool for Family Care Needs of People with Dementia" using a transdisciplinary perspective and to establish the reliability and validity of this tool. METHODS: Based on a literature review and clinical experience, the preliminary items of the assessment tool were drawn up and pilot tests of the case were conducted in the Clinic for Dementia Care. The transdisciplinary research team discussed the pilot tests and verified the preliminary items, and then experts were invited to assess the content validity of the assessment tool. Next, quota sampling was conducted in accordance with the national proportion of the severity of dementia and the questionnaire surveys were administered in an outpatient department of neurology at a medical center in southern Taiwan. Two hundred dyads of PwD and their family caregivers participated in the survey. Reliability and validity analysis of the data were completed. RESULTS: The assessment tool contains 21 items of demographic data and 31 items in the eight subscales of "language and communication", "activities of daily living", "sleep", "activity arrangements", "nutrition and diet", "behavioral and psychological symptoms of dementia", "care stress", and "obtaining resources". The overall content validity of the assessment tool was .99 and the Cronbach's alpha of each subscale ranged between .625 and .905. The concurrent validities of the "activities of daily living" subscale and the "behavioral and psychological symptoms of dementia" subscale were, respectively, correlated with the Barthel Index (r = -.889, p < .001) and the Neuropsychiatric Inventory Questionnaire (r = .750, p < .001). CONCLUSIONS / IMPLICATIONS FOR PRACTICE: The assessment tool was assessed as having satisfactory validity and reliability. Moreover, the tool was clear and concise, and was able to be completed quickly by the caregivers. Transdisciplinary professionals involved in dementia care may use this assessment tool in outpatient departments, centers for integrated dementia care, and discharge preparation services to acquire information related to family care needs. The results of the assessment tool may be used as a reference in developing appropriate transdisciplinary care plans to improve the quality of care and quality of life of families of patients with dementia.

Freezing of Speech Single Questionnaire as a Screening Tool for Cognitive Dysfunction in Patients With Dementia With Lewy Bodies.

INTRODUCTION: Freezing phenomenon is a striking feature of Parkinson's disease. However, it has never been studied in people with dementia with Lewy bodies (DLB). We designed a freezing of speech single questionnaire (FOSSQ) and investigated the frequency and association of freezing of speech (FOS) in patients with DLB and other types of dementia. METHODS: This is a retrospective analysis of data from the project of history-based artificial intelligent computerized dementia diagnostic system. We compared the frequencies of FOS among non-demented (ND) participants, patients with Alzheimer's disease (AD), vascular dementia (VaD), and DLB. Further, we explored the association factors of FOS in all the participants. RESULTS: We enrolled 666 individuals with the following disease distribution: 190, ND; 230, AD; 183, VaD; and 63, DLB. Compared to individuals with ND (2.1%), patients with AD (6.1%), or VaD (18.0%), DLB (54.0%) showed a significantly higher frequency of positive FOS (all p < 0.001). The association factors of FOS were older age, more severe dementia, more severe motor dysfunction, fluctuating cognition, visual hallucinations, parkinsonism, rapid eye movement sleep behavior disorder, attention, mental manipulation, and language. CONCLUSION: Our study showed that the informant-based FOSSQ may be a practical screening tool for discriminating DLB from individuals with ND or other forms of dementia. The FOSSQ can be applied in clinical practice as well as on the artificial intelligent platform.

Effects of walking on sundown syndrome in community-dwelling people with Alzheimer's disease.

BACKGROUND: Sundown syndrome is an important care issue for people with dementia (PwD) and for family caregivers. Walking is a safe and simple physical activity for most PwD, yet no research has explored the effects of different long-term walking periods on sundown syndrome. OBJECTIVES: This study aimed to determine the effects of walking on sundown syndrome, and to identify whether different walking time periods would show different effects on sundown syndrome in community-dwelling people with Alzheimer's disease. METHODS: A quasi-experimental designed study with repeated measurements was conducted. Sixty PwD were recruited and assigned to either the control group or the morning or afternoon walking group according to their caregiver's preference. The participants in the two walking groups completed an average of 120-min walking per week, accompanied by their caregivers. Forty-six achieved the 6-month intervention. Four measurements were taken, one at the pretest and one at weeks 8, 16 and 24. The Chinese version of the Cohen-Mansfield Agitation Inventory, community form (C-CMAI) was used to assess the severity of the sundown syndrome. The generalised estimating equation (GEE) was applied for the longitudinal data analysis. RESULTS: There was a significant change across the study period (p = .048) in the morning walking group, indicating that the score for sundown syndrome decreased when PwD walked in the morning. Considering group effects, compared to the control group, the C-CMAI scores significantly decreased after 16 weeks of walking in the afternoon walking group (p = .001) and after 24 weeks in both the morning and afternoon walking groups (p = .001), indicating that after PwD had walked for 16 weeks, sundown syndrome ameliorated in the afternoon group and continually decreased after 24 weeks in both the morning and afternoon groups. However, there was no significant group difference between the morning and afternoon walking groups during the 24-week walking intervention. CONCLUSIONS: The results indicated that both morning walking and afternoon walking are beneficial for ameliorating the symptoms of sundown syndrome; however, walking in the afternoon may have a faster effect on the symptoms than walking in the morning. Walking is a safe, simple, feasible and effective intervention to benefit individuals with sundown syndrome. IMPLICATIONS FOR PRACTICE: Regularly walking for 30 min a day, four times a week, is beneficial to alleviate sundown syndrome among PwD living in the community. Either morning or afternoon walking is effective for decreasing sundown syndrome, and the longer the walking time, the greater the impact on sundown syndrome.