Global clinical dementia rating of 0.5 in MCI masks variability related to level of function

Multimodal active subspace analysis for computing assessment oriented subspaces from neuroimaging data

BACKGROUND

For successful biomarker discovery, it is essential to develop computational frameworks that summarize high-dimensional neuroimaging data in terms of involved sub-systems of the brain, while also revealing underlying heterogeneous functional and structural changes covarying with specific cognitive and biological traits. However, unsupervised decompositions do not inculcate clinical assessment information, while supervised approaches extract only individual feature importance, thereby impeding qualitative interpretation at the level of subspaces.

NEW METHOD

We present a novel framework to extract robust multimodal brain subspaces associated with changes in a given cognitive or biological trait. Our approach involves active subspace learning on the gradients of a trained machine learning model followed by clustering to extract and summarize the most salient and consistent subspaces associated with the target variable.

RESULTS

Through a rigorous cross-validation procedure on an Alzheimer's disease (AD) dataset, our framework successfully extracts multimodal subspaces specific to a given clinical assessment (e.g., memory and other cognitive skills), and also retains predictive performance in standard machine learning algorithms. We also show that the salient active subspace directions occur consistently across randomly sub-sampled repetitions of the analysis.

COMPARISON WITH EXISTING METHOD(S)

Compared to existing unsupervised decompositions based on principle component analysis, the subspace components in our framework retain higher predictive information.

CONCLUSIONS

As an important step towards biomarker discovery, our framework not only uncovers AD-related brain regions in the associated brain subspaces, but also enables automated identification of multiple underlying structural and functional sub-systems of the brain that collectively characterize changes in memory and proficiency in cognitive skills related to brain disorders like AD.

An explainable machine learning approach for Alzheimer's disease classification

The early diagnosis of Alzheimer's disease (AD) presents a significant challenge due to the subtle biomarker changes often overlooked. Machine learning (ML) models offer a promising tool for identifying individuals at risk of AD. However, current research tends to prioritize ML accuracy while neglecting the crucial aspect of model explainability. The diverse nature of AD data and the limited dataset size introduce additional challenges, primarily related to high dimensionality. In this study, we leveraged a dataset obtained from the National Alzheimer's Coordinating Center, comprising 169,408 records and 1024 features. After applying various steps to reduce the feature space. Notably, support vector machine (SVM) models trained on the selected features exhibited high performance when tested on an external dataset. SVM achieved a high F1 score of 98.9% for binary classification (distinguishing between NC and AD) and 90.7% for multiclass classification. Furthermore, SVM was able to predict AD progression over a 4-year period, with F1 scores reached 88% for binary task and 72.8% for multiclass task. To enhance model explainability, we employed two rule-extraction approaches: class rule mining and stable and interpretable rule set for classification model. These approaches generated human-understandable rules to assist domain experts in comprehending the key factors involved in AD development. We further validated these rules using SHAP and LIME models, underscoring the significance of factors such as MEMORY, JUDGMENT, COMMUN, and ORIENT in determining AD risk. Our experimental outcomes also shed light on the crucial role of the Clinical Dementia Rating tool in predicting AD.

A characteristic of olfactory function in four types of dementia and non-dementia subjects using smell identification test

BACKGROUND

For those outpatients who were consulted for memory loss, the Japanese version of University of Pennsylvania Smell Identification Test (UPSIT-J) was performed to examine olfactory function. In the same way, the revised version of Hasegawa Dementia Scale, Mini Mental State Examination, Clinical Dementia Rating and brain magnetic resonance imaging were used to investigate the cognitive function. In the present study, we evaluated the olfactory function of elderly subjects, including those with dementia, by means of UPSIT-J and we examined their characteristics.

METHODS

The characteristics of dementia as Alzheimer type group (AD.G), mixed type group (MixD.G), vascular type group (VaD.G), dementia with Lewy bodies group (DLB.G) and the groups which had no dementia as low score group (LS.G), high score group (HS.G), and healthy group (H.G), were examined.

RESULTS

The numbers of olfactory discriminating scores (nODS) were significantly lower in all the dementia groups than in all the LS.G, HS.G and the H.G. No significant difference was observed in nODS between AD.G and DLB.G. The rate of nODS with less than five scores were as follows: AD.G (80.1%), MixD.G (91.5%), VaD.G (63.1%), DLB.G (89.6%), LS.G (50.8%), HS.G (18.6%), H.G (15.6%). A significant positive correlation was found between nODS and Hasegawa Dementia Scale and Mini Mental State Examination scores (r = 0.567, r = 0.532, respectively), which was significant negatively correlated for Clinical Dementia Rating (r = -0.578). A significant negative correlation was observed between nODS and Z score of voxel-based specific regional analysis for Z score of Alzheimer's disease (VSRAD) (r = 0.463).

CONCLUSION

nODS showed a significant correlation between cognitive function tests and brain atrophy level. These results indicate that UPSIT-J is considered a psycho-physiological index useful for the diagnosis and early detection of dementia.

Ultra-Early Screening of Cognitive Decline Due to Alzheimer's Pathology

Alzheimer's pathology can be assessed and defined via Aβ and tau biomarkers. The preclinical period of Alzheimer's disease is long and lasts several decades. Although effective therapies to block pathological processes of Alzheimer's disease are still lacking, downward trends in the incidence and prevalence of dementia have occurred in developed countries. Accumulating findings support that education, cognitive training, physical exercise/activities, and a healthy lifestyle can protect cognitive function and promote healthy aging. Many studies focus on detecting mild cognitive impairment (MCI) and take a variety of interventions in this stage to protect cognitive function. However, when Alzheimer's pathology advances to the stage of MCI, interventions may not be successful in blocking the development of the pathological process. MCI individuals reverting to normal cognitive function exhibited a high probability to progress to dementia. Therefore, it is necessary to take effective measures before the MCI stage. Compared with MCI, an earlier stage, transitional cognitive decline, may be a better time window in which effective interventions are adopted for at-risk individuals. Detecting this stage in large populations relies on rapid screening of cognitive function; given that many cognitive tests focus on MCI detection, new tools need to be developed.

Blood-Derived Progenitor Cells Are Depleted in Older Adults with Cognitive Impairment: A Role for Vascular Resilience?

BACKGROUND

Depletion of blood-derived progenitor cells, including so called "early endothelial progenitor cells", has been observed in individuals with early stage Alzheimer's disease relative to matched older control subjects. These findings could implicate the loss of angiogenic support from hematopoietic progenitors or endothelial progenitors in cognitive dysfunction.

OBJECTIVE

To investigate links between progenitor cell proliferation and mild levels of cognitive dysfunction.

METHODS

We conducted in vitro studies of blood-derived progenitor cells using blood samples from sixty-five older adults who were free of stroke or dementia. Peripheral blood mononuclear cells from venous blood samples were cultured in CFU-Hill media and the number of colony forming units were counted after 5 days in vitro. Neuropsychological testing was administered to all participants.

RESULTS

Fewer colony forming units were observed in samples from older adults with a Clinical Dementia Rating global score of 0.5 versus 0. Older adults whose samples developed fewer colony forming units exhibited worse performance on neuropsychological measures of memory, executive functioning, and language ability.

CONCLUSION

These data suggest blood progenitors may represent a vascular resilience marker related to cognitive dysfunction in older adults.

A Remotely Coached Multimodal Lifestyle Intervention for Alzheimer's Disease Ameliorates Functional and Cognitive Outcomes

BACKGROUND

Comprehensive treatment of Alzheimer's disease and related dementias (ADRD) requires not only pharmacologic treatment but also management of existing medical conditions and lifestyle modifications including diet, cognitive training, and exercise. Personalized, multimodal therapies are needed to best prevent and treat Alzheimer's disease (AD).

OBJECTIVE

The Coaching for Cognition in Alzheimer's (COCOA) trial was a prospective randomized controlled trial to test the hypothesis that a remotely coached multimodal lifestyle intervention would improve early-stage AD.

METHODS

Participants with early-stage AD were randomized into two arms. Arm 1 (N = 24) received standard of care. Arm 2 (N = 31) additionally received telephonic personalized coaching for multiple lifestyle interventions. The primary outcome was a test of the hypothesis that the Memory Performance Index (MPI) change over time would be better in the intervention arm than in the control arm. The Functional Assessment Staging Test was assessed for a secondary outcome. COCOA collected psychometric, clinical, lifestyle, genomic, proteomic, metabolomic, and microbiome data at multiple timepoints (dynamic dense data) across two years for each participant.

RESULTS

The intervention arm ameliorated 2.1 [1.0] MPI points (mean [SD], p = 0.016) compared to the control over the two-year intervention. No important adverse events or side effects were observed.

CONCLUSION

Multimodal lifestyle interventions are effective for ameliorating cognitive decline and have a larger effect size than pharmacological interventions. Dietary changes and exercise are likely to be beneficial components of multimodal interventions in many individuals. Remote coaching is an effective intervention for early stage ADRD. Remote interventions were effective during the COVID pandemic.

Multiple Cognitive and Behavioral Factors Link Association Between Brain Structure and Functional Impairment of Daily Instrumental Activities in Older Adults

OBJECTIVE

Functional impairment in daily activity is a cornerstone in distinguishing the clinical progression of dementia. Multiple indicators based on neuroimaging and neuropsychological instruments are used to assess the levels of impairment and disease severity; however, it remains unclear how multivariate patterns of predictors uniquely predict the functional ability and how the relative importance of various predictors differs.

METHOD

In this study, 881 older adults with subjective cognitive complaints, mild cognitive impairment (MCI), and dementia with Alzheimer's type completed brain structural magnetic resonance imaging (MRI), neuropsychological assessment, and a survey of instrumental activities of daily living (IADL). We utilized the partial least square (PLS) method to identify latent components that are predictive of IADL.

RESULTS

The result showed distinct brain components (gray matter density of cerebellar, medial temporal, subcortical, limbic, and default network regions) and cognitive-behavioral components (general cognitive abilities, processing speed, and executive function, episodic memory, and neuropsychiatric symptoms) were predictive of IADL. Subsequent path analysis showed that the effect of brain structural components on IADL was largely mediated by cognitive and behavioral components. When comparing hierarchical regression models, the brain structural measures minimally added the explanatory power of cognitive and behavioral measures on IADL.

CONCLUSION

Our finding suggests that cerebellar structure and orbitofrontal cortex, alongside with medial temporal lobe, play an important role in the maintenance of functional status in older adults with or without dementia. Moreover, the significance of brain structural volume affects real-life functional activities via disruptions in multiple cognitive and behavioral functions.

SVR-based Multimodal Active Subspace Analysis for the Brain using Neuroimaging Data.. [DOI: 10.1101/2022.07.28.501879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Understanding the patterns of changes in brain function and structure due to various disorders and diseases is of utmost importance. There have been numerous efforts toward successful biomarker discovery for complex brain disorders by evaluating neuroimaging datasets with novel analytical frameworks. However, due to the multi-faceted nature of the disorders involving a wide and overlapping range of symptoms as well as complex changes in structural and functional brain networks, it is increasingly important to devise computational frameworks that can consider the underlying patterns of heterogeneous changes with specific target assessments, at the same time producing a summarizing output from the high-dimensional neuroimaging data. While various machine learning approaches focus on diagnostic prediction, many learning frameworks analyze important features at the level of brain regions involved in prediction using supervised methods. Unsupervised learning methods have also been utilized to break down the neuroimaging features into lower dimensional components. However, most learning frameworks either do not consider the target assessment information while extracting brain subspaces, or can extract only higher dimensional importance associations as an ordered list of involved features, making manual interpretation at the level of subspaces difficult. We present a novel multimodal active subspace learning framework to understand various subspaces within the brain that are associated with changes in particular biological and cognitive traits. For a given cognitive or biological trait, our framework performs a decomposition of the feature importances to extract robust multimodal subspaces that define the most significant change in the given trait. Through a rigorous cross-validation procedure on an Alzheimer’s disease (AD) dataset, we show that our framework can extract subspaces covering both functional and structural modalities, which are specific to a given clinical assessment (like memory and other cognitive skills) and also retain predictive performance in standard machine learning algorithms. We show that our framework not only uncovers AD-related brain regions (e.g., hippocampus, entorhinal cortex) in the associated brain subspaces, but also enables an automated identification of multiple underlying structural and functional sub-systems of the brain that collectively characterize changes in memory and cognitive skill proficiency related to brain disorders like AD.

Validation of T-MoCA in the Screening of Mild Cognitive Impairment in Chinese Patients With Atrial Fibrillation

Background

Atrial fibrillation (AF) is associated with a high risk of mild cognitive impairment (MCI) and dementia. However, feasible and simple instruments that facilitate the regular assessment of cognitive status in patients with AF remain underdeveloped.

Methods

Cognitive function was first evaluated using telephone Montreal cognitive assessment (T-MoCA), and then patients were invited for an in-person interview for cognitive assessment using both Clinical Dementia Rating (CDR) and mini-mental status evaluation (MMSE). Using CDR = 0.5 as a reference standard, the ability of T-MoCA and MMSE to discriminate cognitive dysfunction, stratified by education level, was tested by receiver–operating curve (ROC) analysis. The net reclassification index was calculated for comparison between the performance of T-MoCA and MMSE.

Results

One hundred and one patients completed both telephone and in-person interview. Thirty-five MCI patients were identified as MCI using the criteria of CDR = 0.5. The areas under the ROC curve of T-MoCA were 0.80 (0.71–0.89), 0.83 (0.71–0.95), and 0.85 (0.64–0.92) for all patients, patients with high educational level, and patients with low education level, respectively. The optimal threshold was achieved at 16/17 with a sensitivity of 85.7% and a specificity of 69.7% in overall patients, 15/16 with a sensitivity of 88.2% and a specificity of 64.5% in the low educational level patients, and 16/17 with a sensitivity of 77.8% and a specificity of 87.9% in the high educational level patients. Compared to the criterion MMSE ≤ 27 and MMSE norms for the elderly Chinese community, the stratified T-MoCA threshold improves correct classification by 23.7% (p = 0.033) and 30.3% (p = 0.020), respectively.

Conclusion

T-MoCA is a feasible and effective instrument for MCI screening in patients with AF.

Impact of Sarcopenia on Decline in Quality of Life in Older People with Mild Cognitive Impairment

Quality of life (QOL) was assessed using the EQ-5D twice in 1 year in 57 older community-dwelling people (age 79.1±5.9 years) with mild cognitive impairment in a memory clinic. Screening for sarcopenia at the initial assessment revealed 40.1% of participants (23/57) were sarcopenic. QOL declined in 33.3% of participants (19/57) after around 1 year. Multiple logistic regression analysis showed that sarcopenia was associated with a decline in QOL around 1 year after initial assessment. Sarcopenia may be a risk factor for decline in QOL in older people with mild cognitive impairment.

Reducing misclassification of mild cognitive impairment based on base rate information from the Uniform data set

The current study aimed to define and validate the criteria for characterizing possible and probable cognitive deficits based on the psychometric approach using the Uniform data set Czech version (UDS-CZ 2.0) to reduce the rate of misdiagnosis. We computed the prevalence of low scores on the 14 subtests of UDS-CZ 2.0 in a normative sample of healthy older adults and validated criteria for possible and probable cognitive impairment on the sample of amnestic Mild Cognitive Impairment (MCI) patients. The misclassification rate of the validation sample using psychometrically derived criteria remained low: for classification as possible impairment, we found 66-76% correct classification in the clinical sample and only 2-8% false positives in the healthy control validation sample, similar results were obtained for probable cognitive impairment. Our findings offer a psychometric approach and a computational tool to minimize the misdiagnosis of mild cognitive impairment compared to traditional criteria for MCI.

Identifying Mild Cognitive Impairment by Using Human-Robot Interactions

BACKGROUND

Mild cognitive impairment (MCI), which is common in older adults, is a risk factor for dementia. Rapidly growing health care demand associated with global population aging has spurred the development of new digital tools for the assessment of cognitive performance in older adults.

OBJECTIVE

To overcome methodological drawbacks of previous studies (e.g., use of potentially imprecise screening tools that fail to include patients with MCI), this study investigated the feasibility of assessing multiple cognitive functions in older adults with and without MCI by using a social robot.

METHODS

This study included 33 older adults with or without MCI and 33 healthy young adults. We examined the utility of five robotic cognitive tests focused on language, episodic memory, prospective memory, and aspects of executive function to classify age-associated cognitive changes versus MCI. Standardized neuropsychological tests were collected to validate robotic test performance.

RESULTS

The assessment was well received by all participants. Robotic tests assessing delayed episodic memory, prospective memory, and aspects of executive function were optimal for differentiating between older adults with and without MCI, whereas the global cognitive test (i.e., Mini-Mental State Examination) failed to capture such subtle cognitive differences among older adults. Furthermore, robot-administered tests demonstrated sound ability to predict the results of standardized cognitive tests, even after adjustment for demographic variables and global cognitive status.

CONCLUSION

Overall, our results suggest the human-robot interaction approach is feasible for MCI identification. Incorporating additional cognitive test measures might improve the stability and reliability of such robot-assisted MCI diagnoses.

It Is Time to Study Overlapping Molecular and Circuit Pathophysiologies in Alzheimer's and Lewy Body Disease Spectra

Alzheimer's disease (AD) is the leading cause of dementia due to neurodegeneration and is characterized by extracellular senile plaques composed of amyloid β1 - 42 (Aβ) as well as intracellular neurofibrillary tangles consisting of phosphorylated tau (p-tau). Dementia with Lewy bodies constitutes a continuous spectrum with Parkinson's disease, collectively termed Lewy body disease (LBD). LBD is characterized by intracellular Lewy bodies containing α-synuclein (α-syn). The core clinical features of AD and LBD spectra are distinct, but the two spectra share common cognitive and behavioral symptoms. The accumulation of pathological proteins, which acquire pathogenicity through conformational changes, has long been investigated on a protein-by-protein basis. However, recent evidence suggests that interactions among these molecules may be critical to pathogenesis. For example, Aβ/tau promotes α-syn pathology, and α-syn modulates p-tau pathology. Furthermore, clinical evidence suggests that these interactions may explain the overlapping pathology between AD and LBD in molecular imaging and post-mortem studies. Additionally, a recent hypothesis points to a common mechanism of prion-like progression of these pathological proteins, via neural circuits, in both AD and LBD. This suggests a need for understanding connectomics and their alterations in AD and LBD from both pathological and functional perspectives. In AD, reduced connectivity in the default mode network is considered a hallmark of the disease. In LBD, previous studies have emphasized abnormalities in the basal ganglia and sensorimotor networks; however, these account for movement disorders only. Knowledge about network abnormalities common to AD and LBD is scarce because few previous neuroimaging studies investigated AD and LBD as a comprehensive cohort. In this paper, we review research on the distribution and interactions of pathological proteins in the brain in AD and LBD, after briefly summarizing their clinical and neuropsychological manifestations. We also describe the brain functional and connectivity changes following abnormal protein accumulation in AD and LBD. Finally, we argue for the necessity of neuroimaging studies that examine AD and LBD cases as a continuous spectrum especially from the proteinopathy and neurocircuitopathy viewpoints. The findings from such a unified AD and Parkinson's disease (PD) cohort study should provide a new comprehensive perspective and key data for guiding disease modification therapies targeting the pathological proteins in AD and LBD.

Urban-rural disparities in mild cognitive impairment and its functional subtypes among community-dwelling older residents in central China

BACKGROUND

Substantial variations in the prevalence of mild cognitive impairment (MCI) and its subtypes have been reported, although mostly in geographically defined developed countries and regions. Less is known about MCI and its subtypes in rural areas of less developed central China.

AIMS

The study aimed to compare the prevalence of MCI and its subtypes in residents aged 65 years or older in urban and rural areas of Hubei Province, China.

METHODS

Participants aged 65 years or older were recruited between 2018 and 2019. Inperson structured interviews and clinical and neuropsychological assessments were performed at city health community centres and township hospitals.

RESULTS

Among 2644 participants without dementia, 735 had MCI, resulting in a prevalence of 27.8% for total MCI, 20.9% for amnestic MCI (aMCI) and 6.9% for non-amnestic MCI (naMCI). The prevalence of MCI in urban and rural areas was 20.2% and 44.1%, respectively. After adjusting for demographic factors, the prevalence of total MCI, aMCI and naMCI differed significantly between rural and urban areas (adjusted odds ratio (OR) 2.10, 1.44 and 3.76, respectively). Subgroup analysis revealed an association between rural socioeconomic and lifestyle disadvantage and MCI and its subtypes.

CONCLUSIONS

Our findings suggest that the prevalence of MCI among urban residents in central China is consistent with that in other metropolis areas, such as Shanghai, but the prevalence in rural areas is twice that in urban areas. Prospective studies and dementia prevention in China should focus on rural areas.

Comparison of RCF Scoring System to Clinical Decision for the Rey Complex Figure Using Machine-Learning Algorithm

BACKGROUND AND PURPOSE

Interpreting the Rey complex figure (RCF) requires a standard RCF scoring system and clinical decision by clinicians. The interpretation of RCF using clinical decision by clinicians might not be accurate in the diagnosing of mild cognitive impairment (MCI) or dementia patients in comparison with the RCF scoring system. For this reason, a machine-learning algorithm was used to demonstrate that scoring RCF using clinical decision is not as accurate as of the RCF scoring system in predicting MCI or mild dementia patients from normal subjects.

METHODS

The RCF dataset consisted of 2,232 subjects with formal neuropsychological assessments. The RCF dataset was classified into 2 datasets. The first dataset was to compare normal vs. abnormal and the second dataset was to compare normal vs. MCI vs. mild dementia. Models were trained using a convolutional neural network for machine learning. Receiver operating characteristic curves were used to compare the sensitivity, specificity, and area under the curve (AUC) of models.

RESULTS

The trained model's accuracy for predicting cognitive states was 96% with the first dataset (normal vs. abnormal) and 88% with the second dataset (normal vs. MCI vs. mild dementia). The model had a sensitivity of 85% for detecting abnormal with an AUC of 0.847 with the first dataset. It had a sensitivity of 78% for detecting MCI or mild dementia with an AUC of 0.778 with the second dataset.

CONCLUSIONS

Based on this study, the RCF scoring system has the potential to present more accurate criteria than the clinical decision for distinguishing cognitive impairment among patients.

Clinical and Objective Cognitive Measures for the Diagnosis of Cognitive Frailty Subtypes: A Comparative Study

Background

Cognitive frailty (CF) includes reversible and potentially reversible subtypes; the former is known as concurrent physical frailty (PF) and pre-mild cognitive impairment subjective cognitive decline (pre-MCI SCD), whereas the latter is known as concurrent PF and MCI. The diagnoses of pre-MCI SCD and MCI are based on clinical criteria and various subjective cognitive decline questionnaires. Heterogeneous assessment of cognitive impairment (CI) results in significant variability of CI, CF, and their subtype prevalence in various population-based studies.

Objective

This study aimed to compare the classification differences in CI and CF subtypes from PF and normal cognition by applying clinical and objective cognitive criteria. Clinical criteria comprised Fried PF and clinical MCI criteria combined with the SCD questionnaire, whereas objective criteria comprised Fried PF and objective cognitive criteria based on the norm-adjusted six neuropsychological test scores.

Methods

Of the 335 volunteers (age ≥ 60 years) in this study, 191 were diagnosed with CI based on clinical cognitive diagnosis criteria, and 144 were identified as robust normal based on objective cognitive assessment from the community-dwelling older adult cohort. Individuals with clinical CI, including 94 with MCI and 97 with pre-MCI SCD, were reclassified into different z-score-derived MCI, pre-MCI SCD, and normal subgroups based on objective cognitive criteria. The classification diagnostic accuracy of normal cognition, PF, pre-MCI, MCI, CF, and CF subtypes based on clinical and objective criteria was compared before and after adjusting for age, sex, and education level.

Results

The reclassification of objective assessments indicated better performance than that of clinical assessments in terms of discerning CI severity among different subgroups before adjusting for demographic factors. After covariate adjustment, clinical assessments significantly improved the ability to cognitively discriminate normal individuals from those with pre-MCI SCD and MCI but not the z-score-derived pre-MCI SCD and MCI groups from the robust normal group. Furthermore, the adjustment did not improve the ability to discriminate among individuals with reversible CF from those with potentially reversible CF and pre-MCI only SCD from MCI only SCD.

Conclusions

Objective criteria showed better performance than clinical criteria in the diagnosis of individuals with CI or CF subtypes. Rapid clinical cognitive screening in combination with normative z-scores criteria is cost effective and sustainable in clinical practice.

Demographically Corrected Normative Z Scores on the Neuropsychological Test Battery in Cognitively Normal Older Chinese Adults

BACKGROUND

Subjective questionnaires used for the diagnosis of pre-mild cognitive impairment (pre-MCI) and conventional criteria for MCI might mainly result in false-positive diagnostic errors. The integrated criteria based on demographically adjusted total and process Z scores on neuropsychological tests have been validated to be sensitive for measuring pre-MCI, MCI, and MCI subtypes. However, the underrepresentativity of Chinese populations and the complexity in some tests limit the use of the established Z scores in the elderly Chinese population.

OBJECTIVE

The aim of this study was to develop a useful Z score calculator to assess individual cognitive performance after adjustment of the scores on each of the neuropsychological tests according to sex, age, and education and to establish preliminary norms for the objective assessment of cognition function in elderly Chinese individuals.

METHODS

The neuropsychological test battery consists of measures of performance on different cognitive domains, including episodic memory, language, executive function, processing speed, and attention. Data were obtained from 220 clinically cognitively normal Chinese volunteers aged 60 years or older from the cohort of the Shanghai study of health promotion among frail elderly individuals. Regression models were used to investigate the impact of age, education, and sex on test scores. Z scores were estimated for the different scores by subtracting the predicted mean from the raw score and dividing it by the root mean square error term for any given linear regression model.

RESULTS

Preliminary analyses indicated that age, sex, or level of education significantly affected test scores. A series of linear regression models was constructed for all instruments, i.e.: the Trail-Making Test A and B, to assess executive function or attention; the Boston Naming Test and animal list generation, to assess language; delayed free correct responses and the Hopkins Verbal Learning Test-Revised (HVLT-R) recognition, as well as three process scores, i.e., intrusion errors, learning slope, and retroactive interference, from the HVLT-R, to assess memory, by adjusting for the covariates of age, sex, and level of education concurrently. The Z scores on all neuropsychological tests were estimated based on the corresponding regression coefficients.

CONCLUSIONS

We constructed a multivariable regression-based normative Z score method for the measurement of cognition among older Chinese individuals in the community. The normative score will be useful for the accurate diagnosis of different subtypes of pre-MCI and MCI after preliminary rapid screening in the community.

Associations of Anxiety with Amyloid, Tau, and Neurodegeneration in Older Adults without Dementia: A Longitudinal Study

BACKGROUND

The pathophysiological process of amyloid-β, tau deposition, and neurodegeneration of Alzheimer's disease (AD) begin in a preclinical phase, while anxiety is associated with an increased risk of AD in preclinical phase.

OBJECTIVE

To examine the relationships between anxiety and amyloid-β, tau deposition, and neurodegeneration. To test the hypothesis that anxiety could predict clinical progression in the elderly without dementia.

METHODS

1,400 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database were included in the study and were studied over a median period of 3 years. In multivariable models, the cross-sectional and longitudinal associations between anxiety and amyloid-β PET, tau PET, and FDG PET SUVRs in participants without dementia were explored using Spearman rank correlation, logistic regression model, multiple linear regression model, Kaplan-Meier survival curves, and Cox proportional hazards model. The association between baseline anxiety and clinical progression was also explored.

RESULTS

There was a positive correlation between anxiety and amyloid-β deposition (r = 0.11, p = 0.0017) and a negative correlation between anxiety and neurodegeneration (r = -0.13, p = 0.00022). MCI participants with anxiety showed a faster clinical progression of dementia (HR = 1.56, p = 0.04). Non-anxious participants with more amyloid-β deposition or more severe neurodegeneration displayed accelerated development into anxiety (HR = 2.352, p < 0.0001; HR = 2.254, p < 0.0001).

CONCLUSION

Anxiety was associated with amyloid-β deposition and neurodegeneration in non-dementia elderly. Anxiety in MCI predicted conversion to dementia. Anxiety may play a selective role and prediction of disease progression in the early phase of AD.

Association Between Sarcopenia and Quality of Life in Patients with Early Dementia and Mild Cognitive Impairment

BACKGROUND

Cognitive impairment is linked to decreased quality of life (QOL), but few studies have investigated the impact of comorbid sarcopenia.

OBJECTIVE

The aim of this study was to elucidate the association of sarcopenia with QOL in patients with early dementia and mild cognitive impairment.

METHODS

Individuals with a Clinical Dementia Rating of 0.5 or 1 and a Mini-Mental State Examination score of 20-30 underwent a battery of neuropsychological assessments administered by a group of well-trained clinical psychologists. The EQ-5D was completed by both the patients and their main caregivers. EQ-5D utility and visual analog scale scores were measured. Sarcopenia was defined according to the criteria published in the 2019 consensus update by the Asian Working Group for Sarcopenia.

RESULTS

Patients with sarcopenia had significantly lower scores on the Digit Symbol Substitution Test and Trail Making Test Part A. There was a significant negative association between sarcopenia and both self- and proxy-rated EQ-5D utility scores independent of potential confounding factors. However, there was no association between QOL visual analog scale scores and sarcopenia.

CONCLUSION

Given that sarcopenia is often found in individuals with cognitive impairment, early detection by timely screening and effective intervention may help to maintain or improve QOL in this population. However, this study could not determine whether reduced QOL is a direct consequence of sarcopenia.

Effect of acupuncture treatment on post-stroke cognitive impairment: A randomized controlled trial

INTRODUCTION

Post-stroke cognitive impairment (PSCI), which has a high morbidity, is closely associated with the recurrence and rehabilitation of ischemic stroke. There are 2 different stages of PSCI, including post-stroke cognitive impairment with no dementia (PSCIND) and post-stroke dementia (PSD). The latter has a significantly higher mortality rate than the previous one. Therefore, preventing the onset of PSD is of vital importance. However, there is no unequivocally effective prevention or treatment for PSCI, except intensive secondary prevention of stroke. The primary aim of this protocol is to explore whether acupuncture can improve cognitive function of patients with PSCIND and reduce the chances of developing PSD. On this bias, we also want to explore its possible mechanisms.

METHODS AND ANALYSIS

A prospective, multicenter, large sample, randomized controlled trial will be conducted. A total of 360 eligible patients will be recruited from 5 different hospitals and randomly allocated into the acupuncture group (AG), sham acupuncture group (NAG), and waiting-list group (WLG) in a 1:1:1 ratio. The intervention period of NAG and AG will last 3 months (30 minutes per day, 3 times per week). Primary and secondary outcomes will be measured at baseline, 12 weeks (at the end of the intervention), 24 weeks (after the 12-week follow-up period), and 36 weeks (after the 24-week follow-up period). Resting-state and task-state functional MRI will be conducted at baseline and 12 weeks.

ETHICS AND DISSEMINATION

The ethic committee of First Teaching Hospital of University of Traditional Chinese Medicine approved the study. Study results will be first informed to each participant and later disseminated to researchers, and the general public through courses, presentations and the internet, regardless of the magnitude or direction of effect. The results will also be documented in a published peer-reviewed academic journal.

REGISTRATION

We have registered at ClinicalTrials.gov(ChiCTR2000033801).

The Effectiveness and Safety of Manual Acupuncture Therapy in Patients with Poststroke Cognitive Impairment: A Meta-analysis

Background. Poststroke cognitive impairment (PSCI) is a common cause of disability among patients with stroke. Meanwhile, acupuncture has increasingly been used to improve motor and cognitive function for stroke patients. The aim of the present study was to summarize and evaluate the evidence on the effectiveness of acupuncture in treating PSCI. Methods. Eight databases (PubMed, The Cochrane Library, CNKI, WanFang Data, VIP, CBM, Medline, Embase databases) were searched from January 2010 to January 2020. Meta-analyses were conducted for the eligible randomized controlled trials (RCTs). Assessments were performed using Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Barthel Index (BI), or modified Barthel Index (MBI). Results. A total of 657 relevant RCTs were identified, and 22 RCTs with 1856 patients were eventually included. Meta-analysis showed that acupuncture appeared to be effective for improving cognitive function as assessed by MMSE ( $\text{mean}\text{difference}\left(\text{MD}\right)=1.73$ , 95% confidence interval (CI) (1.39, 2.06), $P<0.00001$ ) and MoCA ( $\text{MD}=2.32$ , 95% CI (1.92, 2.73), $P<0.00001$ ). Furthermore, it also suggested that acupuncture could improve the activities of daily life (ADL) for PSCI patients as assessed by BI or MBI ( $\text{SMD}=0.97$ , 95% CI (0.57, 1.38), $P<0.00001$ ). Conclusions. Compared with nonacupuncture group, acupuncture group showed better effects in improving the scores of MMSE, MoCA, BI, and MBI. This meta-analysis provided positive evidence that acupuncture may be effective in improving cognitive function and activities of daily life for PSCI patients. Meanwhile, long retention time of acupuncture may improve cognitive function and activities of daily life, and twist technique may be an important factor that could influence cognitive function. However, further studies using large samples and a rigorous study design are needed to confirm the role of acupuncture in the treatment of PSCI.

White matter pathways underlying Chinese semantic and phonological fluency in mild cognitive impairment

Neuroimaging evidence has suggested that Chinese-language processing differs from that of its alphabetic-language counterparts. However, the underlying white matter pathway correlations between semantic and phonological fluency in Chinese-language processing remain unknown. Thus, we investigated the differences between two verbal fluency tests on 50 participants with amnestic mild cognitive impairment (aMCI) and 36 healthy controls (HC) with respect to five groups (ventral and dorsal stream fibers, frontal-striatal fibers, hippocampal-related fibers, and the corpus callosum) of white matter microstructural integrity. Diffusion spectrum imaging was used. The results revealed a progressive reduction in advantage in semantic fluency relative to phonological fluency from HC to single-domain aMCI to multidomain aMCI. Common and dissociative white matter correlations between tests of the two types of fluency were identified. Both types of fluency relied on the corpus callosum and ventral stream fibers, semantic fluency relied on the hippocampal-related fibers, and phonological fluency relied on the dorsal stream and frontal-striatal fibers. The involvement of bilateral tracts of interest as well as the association with the corpus callosum indicate the uniqueness of Chinese-language fluency processing. Dynamic associations were noted between white matter tract involvement and performance on the two fluency tests in four time blocks. Overall, our findings suggest the clinical utility of verbal fluency tests in geriatric populations, and they elucidate both task-specific and language-specific brain-behavior associations.

Evidence for the Utility of Actuarial Neuropsychological Criteria Across the Continuum of Normal Aging, Mild Cognitive Impairment, and Dementia

Background:

Research suggests that actuarial neuropsychological criteria improve the accuracy of mild cognitive impairment (MCI) diagnoses relative to conventional diagnostic methods.

Objective:

We sought to examine the utility of actuarial criteria relative to consensus diagnostic methods used in the National Alzheimer’s Coordinating Center (NACC) Uniform Data Set (UDS), and more broadly across the continuum of normal aging, MCI, and dementia.

Methods:

We compared rates of cognitively normal (CN), MCI, and dementia diagnoses at baseline using actuarial versus consensus diagnostic methods in 1524 individuals from the NACC UDS.

Results:

Approximately one-third (33.59%) of individuals diagnosed as CN and more than one-fifth (22.03%) diagnosed with dementia based on consensus methods, met actuarial criteria for MCI. Many participants diagnosed with MCI via consensus methods also appeared to represent possible diagnostic errors. Notably, the CN_a/CN_c group (i.e., participants diagnosed as CN based on both actuarial [_a] and consensus [_c] criteria) had a lower proportion of apolipoprotein E ɛ4 carriers than the MCI_a/MCI_c group, which in turn had a lower proportion of ɛ4 carriers than the dementia (Dem)_a/Dem_c group. Proportions of ɛ4 carriers were comparable between the CN_a/CN_c and CN_a/MCI_c, MCI_a/MCI_c and MCI_a/CN_c, MCI_a/MCI_c and MCI_a/Dem_c, and Dem_a/Dem_c and Dem_a/MCI_c groups. These results were largely consistent with diagnostic agreement/discrepancy group comparisons on neuropsychological performance.

Conclusion:

The present results extend previous findings and suggest that actuarial neuropsychological criteria may enhance diagnostic accuracy relative to consensus methods, and across the wider continuum of normal aging, MCI, and dementia. Findings have implications for both clinical practice and research.

Disentangling Heterogeneity in Alzheimer's Disease: Two Empirically-Derived Subtypes

BACKGROUND

Clinical-pathological Alzheimer's disease (AD) subtypes may help distill heterogeneity in patient presentation. To date, no studies have utilized neuropsychological and biological markers to identify preclinical subtypes with longitudinal stability.

OBJECTIVE

The objective of this study was to empirically derive AD endophenotypes using a combination of cognitive and biological markers.

METHODS

Hierarchical cluster analysis grouped dementia-free older adults using memory, executive and language abilities, and cerebrospinal fluid amyloid-β and phosphorylated tau. Brain volume differences, neuropsychological trajectory, and progression to dementia were compared, controlling for age, gender, education, and apolipoprotein E4 (ApoE4).

RESULTS

Subgroups included asymptomatic-normal (n = 653) with unimpaired cognition and subthreshold biomarkers, typical AD (TAD; n = 191) showing marked memory decline, high ApoE4 rates and abnormal biomarkers, and atypical AD (AAD; n = 132) with widespread cognitive decline, intermediate biomarker levels, older age, less education and more white matter lesions. Cognitive profiles showed longitudinal stability with corresponding patterns of cortical atrophy, despite nearly identical rates of progression to AD dementia.

CONCLUSION

Two clinical-pathological AD subtypes are identified with potential implications for preventative efforts.

On-Road Behavior in Older Drivers With Mild Cognitive Impairment

OBJECTIVES

Dementia increases the risk of unsafe driving, but this is less apparent in preclinical stages such as mild cognitive impairment (MCI). There is, however, limited detailed data on the patterns of driving errors associated with MCI. Here, we examined whether drivers with MCI exhibited different on-road error profiles compared with cognitively normal (CN) older drivers.

DESIGN

Observational.

SETTING AND PARTICIPANTS

A total of 296 licensed older drivers [mean age 75.5 (SD = 6.2) years, 120 (40.5%) women] recruited from the community.

METHOD

Participants completed a health and driving history survey, a neuropsychological test battery, and an on-road driving assessment including driver-instructed and self-navigation components. Driving assessors were blind to participant cognitive status. Participants were categorized as safe or unsafe based on a validated on-road safety scale, and as having MCI based on International Working Group diagnostic criteria. Proportion of errors incurred as a function of error type and traffic context were compared across safe and unsafe MCI and CN drivers.

RESULTS

Compared with safe CN drivers (n = 225), safe MCI drivers (n = 45) showed a similar pattern of errors in different traffic contexts. Compared with safe CN drivers, unsafe CN drivers (n = 17) were more likely to make errors in observation, speed control, lane position, and approach, and at stop/give-way signs, lane changes, and curved driving. Unsafe MCI drivers (n = 9) had additional difficulties at intersections, roundabouts, parking, straight driving, and under self-navigation conditions. A higher proportion of unsafe MCI drivers had multidomain subtype [n = 6 (67%)] than safe MCI drivers [n = 11 (25%)], odds ratio 6.2 (95% confidence interval, 1.4-29.6).

CONCLUSION AND IMPLICATIONS

Among safe drivers, MCI and CN drivers exhibit similar on-road error profiles, suggesting driver restrictions based on MCI status alone are unwarranted. However, formal evaluation is recommended in such cases, as there is evidence drivers with multiple domains of cognitive impairment may require additional interventions to support safe driving.

Function-based dementia severity assessment for vascular cognitive impairment

BACKGROUND/PURPOSES

Unimpaired activities of daily living (ADL) is essential for the diagnosis of normal cognition and mild cognitive impairment. However, diagnosis according to this concept is difficult to apply to patients comorbid with motor dysfunction. We aim to use a novel ADL questionnaire for operationally diagnosing unimpaired ADL in vascular cognitive impairment with no dementia (VCIND).

METHODS AND PARTICIPANTS

This was a retrospective cohort study with both cross-sectional and long-term follow-up analysis. Patients with cerebrovascular disease with normal cognition (CVDNC), VCIND, and vascular dementia (VaD) were analyzed. Cutoff scores for differentiating different stages of cognitive impairment were compared between the new History-based Artificial Intelligent ADL questionnaire (HAI-ADL) and other tools.

RESULTS

A total of 596 individuals were analyzed, including 40 CVDNC, 167 VCIND, 218 mild, 119 moderate, and 52 severe-dementia patients. The cutoff scores for determining unimpaired ADL in VCIND were 8.5, 3.5, 5, 100, and 60 in HAI-ADL, CDR-SB, IADL, BI, and CASI, respectively. HAI-ADL had the highest correlations with CDR-SB and the CDR staging system compared to other tools. Four models of progression rates from CVDNC/VCIND to VaD revealed it was much higher in the group with HAI-ADL > 8.5 compared to those with HAI-ADL≦8.5 with odds ratios of 3.75, 3.66, 3.31, and 2.77, respectively.

CONCLUSION

Our study showed that HAI-ADL provides an operational determinates unimpaired ADL which is necessary for the diagnosis of VCIND. The predictive value for progression to dementia was proved by a long-term follow-up analysis of the research cohort.

Cognitive and neuropsychological examination of the elderly

Neuropsychological assessment plays a prominent role in the evaluation and care of patients with neurodegenerative diseases throughout the dynamic course of disease. As a biomarker of disease, neuropsychological measurement can distinguish normal from pathologic aging processes. Further, neuropsychological data can help distinguish and classify underlying pathologies in dementing diseases, augmenting imaging and biofluid markers in this area. Neuropsychological data can predict increased or reduced risk for dementia conferred by multiple factors, and describe disease trajectory in affected individuals. Cognitive evaluation can also estimate and address functional outcomes that are most important to patients and their loved ones and that are clinically relevant to diagnostic staging. In informing intervention and patient care needs, areas of cognitive weakness highlight targets for support/intervention, while areas of cognitive strength can be capitalized upon to modify the clinical course of disease. These functions can be accomplished through the complementary use of brief screening tools and comprehensive test batteries. However, for neuropsychological data to serve these functions, it is critical to understand neuropsychological test properties and nondisease factors that can account for variance in test performance. This chapter concludes with directions for future research.

The effect of severity of white matter hyperintensities on loss of functional independency in patients with mild cognitive impairment: A CREDOS-LTCI (clinical research center for dementia of South Korea-long term card insurance) study

OBJECTIVE

By combining data from the Clinical Research Center for Dementia of South Korea(CREDOS) study and long-term care insurance(LTCI), we aimed to assess whether the severity of white matter hyperintensity(WMH) predicted functional decline in cases of amnestic mild cognitive impairment(MCI).

METHODS

WMH was evaluated in 3,569 patients with amnestic MCI using the visual rating scale developed for the CREDOS study. The participants were classified as having amnestic MCI with minimal WMH change(aMCI), with moderate WMH change(maMCI) and with severe WMH change(saMCI) according to the severity of the WMH measurements. A Kaplan-Meier survival probability estimate was used to compute median time from the diagnosis of MCI to LTCI enrollment for the three MCI groups. The effect of various risk factors of LTCI enrollment was evaluated using Cox's proportional hazards model, adjusted for covariates.

RESULTS

As compared with aMCI cases, maMCI and saMCI patients required help with daily activities of living at a younger age. The saMCI and maMCI patients had higher risk of LTCI enrollment as compared with that of the aMCI patients. Younger patients(≤ 65y) with MCI had a 3.201 times higher risk of early LTCI enrollment than older patients(> 65y) did. High clinical dementia rating score and female sex were also risk factors of early LTCI enrollment.

CONCLUSIONS

WMH predicted the rate of global functional decline and loss of independence in patients with MCI. The findings support the use of neuroimaging of WMH, in conjunction with biomarkers, as a tool in predicting functional decline in patients with MCI.

Global Clinical Dementia Rating Score of 0.5 May Not Be an Accurate Criterion to Identify Individuals with Mild Cognitive Impairment

Many studies use the global clinical dementia rating (CDR) of 0.5 as a criterion for mild cognitive impairment, but past studies have not fully discussed its validity. The authors developed the ABC Dementia Scale (ABC-DS) to accurately monitor the changes in activities for daily living, behavioral and psychological symptoms of dementia, and cognitive function. When we carried out a cluster analysis of ABC-DS scores of 110 individuals for whom global CDR was 0.5, there were three groups with different levels of activities for daily living and cognitive function. O’Bryant et al. proposed a new guideline to stage dementia using the CDR sum of boxes scores (CDR-SOB). We used their proposal and ABC-DS scores to evaluate the validity of CDR 0.5 as a definition of mild cognitive impairment (MCI). We concluded that the CDR-SOB scores and ABC-DS score are more accurate than global CDR of 0.5 for specifying individuals with MCI.

Psychometric validation of Fuld Object Memory Evaluation in older adults with cognitive impairments

OBJECTIVES

Mild cognitive impairment (MCI) refers to an early but abnormal state of cognitive impairment with minimal functional impairment. The present study aimed to evaluate the validity of Fuld Object Memory Evaluation (FOME) as a measure of episodic memory function.

METHOD

The study sample included 204 Chinese older adults with cognitive impairments. The participants completed five recall trials and a delayed trial in FOME, neurocognitive measures on digit spans and trail making, and daily functioning. Discriminative power of FOME to differentiate between MCI and dementia was inspected via receiver operating characteristic curve analysis.

RESULTS

FOME showed good test-retest reliability and convergent validity with digit spans and trail making. Controlling for gender, age, and education, lower levels of FOME total retrieval, verbal fluency, and daily functioning significantly predicted a higher likelihood of dementia compared to MCI. The optimal cut-off scores for total retrieval, verbal fluency, and daily functioning to differentiate dementia were 37/38 (77% sensitivity and 83% specificity), 28/29 (85% sensitivity and 72% specificity), and 14/15 (92% sensitivity and 78% specificity), respectively, in the younger subgroup. The corresponding figures were 34/35 (69% sensitivity and 76% specificity) and 27/28 (92% sensitivity and 62% specificity), and 11/12 (74% sensitivity and 80% specificity), respectively, in the older subgroup.

CONCLUSION

The findings support the FOME as a valid assessment tool of episodic memory function in older Chinese adults. The combined use of FOME and daily functioning is recommended to distinguish persons with dementia from MCI.

The Uniform Data Set, Czech Version: Normative Data in Older Adults from an International Perspective

BACKGROUND

Outside of the United States, international perspectives on normative data for neuropsychological test performance, within diverse populations, have been scarce. The neuropsychological test battery from the Uniform Data Set (UDS) of the Alzheimer's Disease Centers (ADC) program of the United States National Institute on Aging (NIA) is one of the most sensitive batteries for the evaluation of both normal cognitive aging and pathological cognitive decline.

OBJECTIVE

This study aimed to determine the feasibility of the Czech Neuropsychological Test Battery from the Uniform Data Set (UDS-Cz 2.0), while also evaluating the results obtained from an international perspective.

METHODS

This paper describes data from 520 cognitively normal participants. Regression analyses were used to describe the influence of demographic variables on UDS-Cz test performance.

RESULTS

Cognitive performance on all measures declined with age, with patient education level serving as a protective factor. Therefore, the present study provides normative data for the UDS-Cz, adjusted for the demographic variables of age and education.

CONCLUSION

The present study determines the psychometric properties of the UDS-Cz and establishes normative values in the aging Czech population, which can be used in clinical settings.

Mild Cognitive Impairment in Clinical Practice: A Review Article

The spectrum of cognitive decline in the elderly ranges from what can be classified as normal cognitive decline with aging to subjective cognitive impairment to mild cognitive impairment (MCI) to dementia. This article reviewed the up-to-date evidence of MCI including the diagnostic criteria of MCI due to Alzheimer's disease, vascular cognitive impairment and MCI due to Parkinson disease, management and preventive intervention of MCI. There are various etiologies of MCI, and a large number of studies have been conducted to ascertain the practical modalities of preserving cognition in predementia stages. Lifestyle modification, such as aerobic exercise, is an approved modality to preserve cognitive ability and decrease the rate of progression to dementia, as well as being recommended for frailty prevention.

Association Between Functional Performance and Alzheimer's Disease Biomarkers in Individuals Without Dementia

OBJECTIVES

To examine the cross-sectional association between functional performance and Alzheimer's disease (AD) neuroimaging biomarkers in individuals without dementia (cognitively unimpaired (CU), and those with mild cognitive impairment (MCI)).

DESIGN

Cross-sectional.

SETTING

Olmsted County, Minnesota.

PARTICIPANTS

Population-based Mayo Clinic Study of Aging (MCSA) participants (aged ≥ 50, mean age 71.3 ± 10.2; 53.4% male; 28.3% apolipoprotein (APO)E ε4 allele carriers, 1,578 CU, 204 MCI) who underwent ¹¹ C-Pittsburgh compound B (¹¹ C-PiB) positron emission tomography (PET) (N=1,782).

MEASUREMENTS

We defined an abnormal (high) ¹¹ C-PiB-PET retention ratio as a standardized uptake value ratio greater than 1.42 (high amyloid; A+), abnormal (reduced) AD signature cortical thickness (neurodegeneration; N+) as less than 2.67 mm (MRI measurement), and biomarker groups according to the combination of abnormality (or not) for amyloid accumulation (A+/A-) and neurodegeneration (N+/N-). Functional performance was assessed using the Clinical Dementia Rating (CDR) Sum of Boxes (SOB) for functional domains and the Functional Activities Questionnaire (FAQ).

RESULTS

Participants with a CDR-SOB (functional) score greater than 0 were almost 4 times as likely to have N + (odds ratio (OR)=3.92, 95% confidence interval (CI)=1.77-8.67, adjusting for age, sex, education, global cognitive z-score, and APOE ε4 allele status; p<.001) and those with a FAQ score greater than 0 were 1.5 times as likely to have A + (OR=1.48, 95% CI=1.04-2.11, p=.03). Higher FAQ scores were associated with greater odds of A+N + and A-N + in CU participants.

CONCLUSION

The findings of this cross-sectional study supplement limited available information that supports an association between functional performance and AD neuroimaging biomarkers very early in the dementia pathophysiology. The associations should be validated in longitudinal studies. J Am Geriatr Soc 66:2274-2281, 2018.

Maximum gait speed is associated with a wide range of cognitive functions in Japanese older adults with a Clinical Dementia Rating of 0.5

AIM

Physical and cognitive functions are mutually associated. However, it is unknown which markers of physical functions or body composition are most strongly associated with cognition. Here, we explored the association between body composition/physical performance and comprehensive neuropsychological assessments in an effort to identify reliable markers of cognition among factors in body composition/physical performance, including both usual and maximum gait speeds.

METHODS

We examined a total of 161 Japanese individuals (71 men, 90 women; aged 76.3 ± 7.2 years) with a Clinical Dementia Rating of 0.5 and a Mini-Mental State Examination score >24. A battery of neuropsychological assessments, physical functional assessments and measurements of body composition was carried out. We conducted a multiple regression analysis to investigate the associations between cognitive performance and the factors in body composition and physical performance with adjustments for age, sex, and number of school years.

RESULTS

Maximum gait speed was the factor most widely associated with cognitive performance among the factors of body composition and physical performance.

CONCLUSION

Maximum gait speed might be the best marker for cognition in this population of older individuals. Geriatr Gerontol Int 2018; 18: 1323-1329.

Triple test, a diagnostic observation, can detect cognitive impairment in older adults

BACKGROUND

A simple, quick, and efficient screening tool for detecting mild cognitive impairment (MCI) and Alzheimer's disease (AD) is essential, especially in the primary care setting. In this study, we examined the neuropsychological profiles of elderly patients and aimed to assess the diagnostic value of the triple test, comprised of the attended alone sign (AAS), head-turning sign, and applause sign (AS), for detecting MCI and AD.

METHOD

Comprehensive geriatric assessment was performed in 354 elderly outpatients, and the presence or absence of AS, AAS and HTS was investigated.

RESULTS

Of the 354 patients, 93 patients were considered to be cognitively impaired (MCI: 30; AD: 63); the remaining 261 were cognitively healthy. Relative to those without AS, patients with AS had significantly lower scores on the Mini-Mental State Examination, the clock-drawing test, Instrumental Activities of Daily Living Scale, and Basic Activities of Daily Living Scale (P < 0.001, for each). Similar significant differences were found between patients who were positive and negative for the HTS (P < 0.001) and between those who attended the clinic alone and those who were accompanied (P < 0.001). The sensitivity of the triple test for identifying cognitively impairment (CI), MCI, and AD was 0.61, 0.30, and 0.72, respectively; the specificity was 0.85, 0.68, and 0.83, respectively; and the positive and negative predictive values were 0.69, 0.09, and 0.59, respectively, and 0.79, 0.90, and 0.89, respectively.

CONCLUSIONS

The present study suggests that the triple test is a simple, quick, and efficient screening tool for detecting cognitive impairment, and the results may reflect deterioration in patients' activities of daily living. Additionally, it could be advantageous in clinical practice because educational level does not affect the test outcome. Therefore, it may be an appropriate test to screen for cognitive impairment in the elderly, both as a bedside diagnostic test and in daily clinical practice, especially in the primary care setting.

Automated tests for diagnosing and monitoring cognitive impairment: a diagnostic accuracy review

BACKGROUND

Cognitive impairment is a growing public health concern, and is one of the most distinctive characteristics of all dementias. The timely recognition of dementia syndromes can be beneficial, as some causes of dementia are treatable and are fully or partially reversible. Several automated cognitive assessment tools for assessing mild cognitive impairment (MCI) and early dementia are now available. Proponents of these tests cite as benefits the tests' repeatability and robustness and the saving of clinicians' time. However, the use of these tools to diagnose and/or monitor progressive cognitive impairment or response to treatment has not yet been evaluated.

OBJECTIVES

The aim of this review was to determine whether or not automated computerised tests could accurately identify patients with progressive cognitive impairment in MCI and dementia and, if so, to investigate their role in monitoring disease progression and/or response to treatment.

DATA SOURCES

Five electronic databases (MEDLINE, EMBASE, The Cochrane Library, ISI Web of Science and PsycINFO), plus ProQuest, were searched from 2005 to August 2015. The bibliographies of retrieved citations were also examined. Trial and research registers were searched for ongoing studies and reviews. A second search was run to identify individual test costs and acquisition costs for the various tools identified in the review.

REVIEW METHODS

Two reviewers independently screened all titles and abstracts to identify potentially relevant studies for inclusion in the review. Full-text copies were assessed independently by two reviewers. Data were extracted and assessed for risk of bias by one reviewer and independently checked for accuracy by a second. The results of the data extraction and quality assessment for each study are presented in structured tables and as a narrative summary.

RESULTS

The electronic searching of databases, including ProQuest, resulted in 13,542 unique citations. The titles and abstracts of these were screened and 399 articles were shortlisted for full-text assessment. Sixteen studies were included in the diagnostic accuracy review. No studies were eligible for inclusion in the review of tools for monitoring progressive disease. Eleven automated computerised tests were assessed in the 16 included studies. The overall quality of the studies was good; however, the wide range of tests assessed and the non-standardised reporting of diagnostic accuracy outcomes meant that meaningful synthesis or statistical analysis was not possible.

LIMITATIONS

The main limitation of this review is the substantial heterogeneity of the tests assessed in the included studies. As a result, no meta-analyses could be undertaken.

CONCLUSION

The quantity of information available is insufficient to be able to make recommendations on the clinical use of the computerised tests for diagnosing and monitoring MCI and early dementia progression. The value of these tests also depends on the costs of acquisition, training, administration and scoring.

FUTURE WORK

Research is required to establish stable cut-off points for automated computerised tests that are used to diagnose patients with MCI or early dementia. Additionally, the costs associated with acquiring and using these tests in clinical practice should be estimated.

STUDY REGISTRATION

The study is registered as PROSPERO CRD42015025410.

FUNDING

The National Institute for Health Research Health Technology Assessment programme.

Prevalence of mild cognitive impairment and its subtypes in community-dwelling residents aged 65 years or older in Guangzhou, China

BACKGROUND

Prevalence of mild cognitive impairment (MCI) has been reported substantial variations, and mostly in Western countries. Less is known about MCI in the south of China. The study is to estimate the prevalence of MCI and its subtypes in residents aged 65year or older in community-dwelling residents of Guangzhou, China.

METHODS

The study was a community-based, cross-sectional study conducted in rural and urban areas of Guangzhou between April and October 2009. Eight communities were randomly selected using a cluster sampling method. Each elderly was interviewed with Montreal Cognitive Assessment, the Mini-Mental state examination, Auditory Verbal Learning Test, the Clinical Dementia Rating scale et al. MCI was classified as amnestic MCI (a-MCI) or nonamnestic MCI (na-MCI).

RESULTS

2427 individuals were contacted, but in-person interviews were conducted with 2111 participants. 299 participants with MCI were identified. The prevalence of MCI, a-MCI and na-MCI was 14.2%, 12.2%, 2.0% respectively. The prevalence of MCI and a-MCI increased with age, decreased with education level, and was higher in rural areas than in urban areas. The difference of prevalence of MCI and a-MCI between women with men wasn't statistically significant(MCIχ2=1.0, OR 0.9, 95%CI=0.6-1.2; a-MCIχ2=1.0, OR 0.9, 95%CI=0.6-1.2), when controlling for education by logistic regression analysis.

CONCLUSIONS

The results suggest that 14.2% of elderly individuals are affected by MCI in Guangzhou, China. And MCI was dominated by a-MCI. The prevalence of MCI and a-MCI increased with age, decreased with education level, and was higher in the rural population compared to the urban population.

Validation of the Telephone Interview of Cognitive Status and Telephone Montreal Cognitive Assessment Against Detailed Cognitive Testing and Clinical Diagnosis of Mild Cognitive Impairment After Stroke

BACKGROUND AND PURPOSE

Assessment of cognitive status poststroke is recommended by guidelines but follow-up can often not be done in person. The Telephone Interview of Cognitive Status (TICS) and the Telephone Montreal Cognitive Assessment (T-MoCA) are considered useful screening instruments. Yet, evidence to define optimal cut-offs for mild cognitive impairment (MCI) after stroke is limited.

METHODS

We studied 105 patients enrolled in the prospective DEDEMAS study (Determinants of Dementia After Stroke; NCT01334749). Follow-up visits at 6, 12, 36, and 60 months included comprehensive neuropsychological testing and the Clinical Dementia Rating scale, both of which served as reference standards. The original TICS and T-MoCA were obtained in 2 separate telephone interviews each separated from the personal visits by 1 week (1 before and 1 after the visit) with the order of interviews (TICS versus T-MoCA) alternating between subjects. Area under the receiver-operating characteristic curves was determined.

RESULTS

Ninety-six patients completed both the face-to-face visits and the 2 interviews. Area under the receiver-operating characteristic curves ranged between 0.76 and 0.83 for TICS and between 0.73 and 0.94 for T-MoCA depending on MCI definition. For multidomain MCI defined by multiple-tests definition derived from comprehensive neuropsychological testing optimal sensitivities and specificities were achieved at cut-offs <36 (TICS) and <18 (T-MoCA). Validity was lower using single-test definition, and cut-offs were higher compared with multiple-test definitions. Using Clinical Dementia Rating as the reference, optimal cut-offs for MCI were <36 (TICS) and approximately 19 (T-MoCA).

CONCLUSIONS

Both the TICS and T-MoCA are valid screening tools poststroke, particularly for multidomain MCI using multiple-test definition.

Effects of cognitive reserve depend on executive and semantic demands of the task

BACKGROUND

Cognitive reserve (CR) is one factor that helps to maintain cognitive function in patients with Alzheimer's disease (AD). Whether the effects of CR depend on the semantic/executive components of the task remains unknown.

METHODS

470 patients (138 with AD, 332 with mild cognitive impairment (MCI)) were selected from the Alzheimer's Disease Neuroimaging Initiative database. Linear regression models were used to determine the effects of CR (years of education) on cognitive performance after controlling for demographic factors and regional cortical atrophy. First, we assessed memory tasks with low (Auditory Verbal Learning Test (AVLT) discriminability), moderate (AVLT delayed recall) and high (Logical Memory Test (LMT) delayed recall) executive/semantic components. Next, we assessed tasks with lower (digit span forward, Trails A) or higher (digit span backwards, Trails B) executive demands, and lower (figure copying) or higher (naming, semantic fluency) semantic demands.

RESULTS

High CR was significantly associated with performance on the LMT delayed recall, approached significance in the AVLT delayed recall and was not significantly associated with performance on AVLT discriminability. High CR was significantly associated with performance on the Trails B and digit span backwards, mildly associated with Trails A performance and was not associated with performance on digit span forwards. High CR was associated with performance on semantic but not visuospatial tasks. High CR was associated with semantic tasks in patients with both MCI and AD, but was only associated with executive functions in patients with MCI.

CONCLUSION

CR may relate to executive functioning and semantic knowledge, leading to preserved cognitive performance in patients with AD pathology.

Heterogeneous cortical atrophy patterns in MCI not captured by conventional diagnostic criteria

OBJECTIVE

We investigated differences in regional cortical thickness between previously identified empirically derived mild cognitive impairment (MCI) subtypes (amnestic MCI, dysnomic MCI, dysexecutive/mixed MCI, and cluster-derived normal) in order to determine whether these cognitive subtypes would show different patterns of cortical atrophy.

METHODS

Participants were 485 individuals diagnosed with MCI and 178 cognitively normal individuals from the Alzheimer's Disease Neuroimaging Initiative. Cortical thickness estimates were computed for 32 regions of interest per hemisphere. Statistical group maps compared each MCI subtype to cognitively normal participants and to one another.

RESULTS

The pattern of cortical thinning observed in each MCI subtype corresponded to their cognitive profile. No differences in cortical thickness were found between the cluster-derived normal MCI subtype and the cognitively normal group. Direct comparison between MCI subtypes suggested that the cortical thickness patterns reflect increasing disease severity.

CONCLUSIONS

There is an ordered pattern of cortical atrophy among patients with MCI that coincides with their profiles of increasing cognitive dysfunction. This heterogeneity is not captured when patients are grouped by conventional diagnostic criteria. Results in the cluster-derived normal group further support the premise that the conventional MCI diagnostic criteria are highly susceptible to false-positive diagnostic errors. Findings suggest a need to (1) improve the diagnostic criteria by reducing reliance on conventional screening measures, rating scales, and a single memory measure in order to avoid false-positive errors; and (2) divide MCI samples into meaningful subgroups based on cognitive and biomarkers profiles-a method that may provide better staging of MCI and inform prognosis.

Mild Cognitive Impairment in Late Middle Age in the Wisconsin Registry for Alzheimer's Prevention Study: Prevalence and Characteristics Using Robust and Standard Neuropsychological Normative Data

OBJECTIVE

Detecting cognitive decline in presymptomatic Alzheimer's disease (AD) and early mild cognitive impairment (MCI) is challenging, but important for treatments targeting AD-related neurodegeneration. The current study aimed to investigate the utility and performance of internally developed robust norms and standard norms in identifying cognitive impairment in late middle-age (baseline age range = 36-68; M = 54).

METHOD

Robust norms were developed for neuropsychological measures based on longitudinally confirmed cognitively normal (CN) participants (n= 476). Seven hundred and seventy-nine participants enriched for AD risk were classified as psychometric MCI (pMCI) or CN based on standard and robust norms and "single-test" versus "multi-test" criteria.

RESULTS

Prevalence of pMCI ranged from 3% to 49% depending on the classification scheme used. Those classified as pMCI using robust norms exhibited greater subjective cognitive complaints, diagnostic stability, and mild clinical symptoms at follow-up.

CONCLUSIONS

Results suggest that identifying early clinically relevant cognitive decline in late middle-age is feasible using robust norms and multi-test criteria.

Application and Revision of Montreal Cognitive Assessment in China's Military Retirees with Mild Cognitive Impairment

Objective

In an effort to accommodate MOCA to better fit for the Chinese context, this study was designed to employ the MOCA criteria to screen mild cognitive impairment (MCI) and analyze associated risk factors in military retirees.

Methods

Three hundred and four retired military cadres were recruited using a random cluster sampling technique with information collected including personal, prevalence, MOCA scale, and related neuropsychiatry scale. Thirty retirees were randomly chosen to be further analyzed one month later using the revised MOCA scale.

Results

①Our data indicated an incidence rate of 64.8% for mild cognitive impairment in retired military cadres. The incidence rate for MCI was significantly higher in those aged 80 or above compared with those 80 years of age or younger (P<0.05). The incidence rate of MCI was significantly higher in those with fewer than 6 years of education compared with those with over 7 years of education (P<0.05). The MCI incidence was higher for those with little exercise than those taking regular exercise (P<0.01). Moreover, the MCI incidence was higher in stroke patients than those who never had a stroke episode (P<0.05). ②There was a significant correlation between MOCA and MMSE scale scores (r = 0.81). MOCA scale scores were negatively correlated with ADL and CES-D scores (although not PSQI scores). ③ MOCA recension Cronbach’s alpha value was 0.862. The related coefficient of MOCA and MOCA recension was 0.878(P<0.01). When the Score of cut-off -point of the MOCA recension was 28, the area in ROC curve analyses was 0.859, as well as the largest area.

Conclusion

Retired cadres exhibited a greater incidence of MCI (than general population), which was closely associated with age, level of education and physical exercise and cerebral apoplexy. Revised MOCA scale displays a better validity and reaction degree of reliability and is more suitable for screening and diagnosis of MCI in the elderly in China.

Clinical Dementia Rating Scale Detects White Matter Changes in Older Adults at Risk for Alzheimer's Disease

This study investigated the putative changes in regional gray matter and cingulum bundle segments in mild cognitive impairment (MCI) by using two diagnostic criteria. Participants comprised 50 older adults with MCI and 22 healthy older controls (HC). The older adults with MCI were further divided into two groups defined by a global Clinical Dementia Rating (CDR) score of 0.5 and with (the CDR/NPT MCI group) or without (the CDR MCI group) objective cognitive impairments determined using neuropsychological tests (NPTs). Comparable regional gray matter integrity was observed among the three groups. However, the integrity of the right inferior segment of the cingulum bundle in the two MCI groups was more reduced than that in the HC group, and the CDR/NPT MCI group exhibited additional disruption in the left inferior cingulum bundle. The results also demonstrated that neuropsychological measures have greater predictive value for changes in white matter beyond the contribution of an informant-based instrument alone. Overall, the findings confirm the utility of informant-based assessment in detecting microstructural brain changes in high-risk older adults, even before objective cognitive impairment is evident. The findings also suggest that combining the neuropsychological measures with the informant-based assessment provided the greatest predictive value in assessing white matter disruption. The essential role of the white matter measurement as a biomarker for detecting individuals at a high risk of developing dementia was highlighted.

Instrumental activities of daily living performance and role satisfaction in people with and without mild cognitive impairment: a pilot project

OBJECTIVE

We investigated differences in observed performance of instrumental activities of daily living (IADLs) and self-reported satisfaction with social role performance between people with amnestic mild cognitive impairment (a-MCI) and age- and gender-matched control participants.

METHOD

We measured observed performance of 14 IADLs using the Independence, Safety, and Adequacy domains of the Performance Assessment of Self-Care Skills (PASS) and the Patient-Reported Outcomes Measurement Information Systems (PROMIS) to examine satisfaction with social role performance.

RESULTS

Total PASS scores were significantly lower in participants with a-MCI (median=40.6) than in control participants (median=44.2; p=.006). Adequacy scores were also significantly lower. No significant differences were found between groups on the PROMIS measures.

CONCLUSION

IADL differences between groups were related more to errors in adequacy than to safety and independence. Occupational therapy practitioners can play a key role in the diagnosis and treatment of subtle IADL deficits in people with MCI.

Susceptibility of the conventional criteria for mild cognitive impairment to false-positive diagnostic errors

BACKGROUND

We assessed whether mild cognitive impairment (MCI) subtypes could be empirically derived within the Alzheimer's Disease Neuroimaging Initiative (ADNI) MCI cohort and examined associated biomarkers and clinical outcomes.

METHODS

Cluster analysis was performed on neuropsychological data from 825 MCI ADNI participants.

RESULTS

Four subtypes emerged: (1) dysnomic (n = 153), (2) dysexecutive (n = 102), (3) amnestic (n = 288), and (4) cluster-derived normal (n = 282) who performed within normal limits on cognitive testing. The cluster-derived normal group had significantly fewer APOE ε4 carriers and fewer who progressed to dementia compared with the other subtypes; they also evidenced cerebrospinal fluid Alzheimer's disease biomarker profiles that did not differ from the normative reference group.

CONCLUSIONS

Identification of empirically derived MCI subtypes demonstrates heterogeneity in MCI cognitive profiles that is not captured by conventional criteria. The large cluster-derived normal group suggests that conventional diagnostic criteria are susceptible to false-positive errors, with the result that prior MCI studies may be diluting important biomarker relationships.

The most frequently used tests for assessing executive functions in aging

There are numerous neuropsychological tests for assessing executive functions in aging, which vary according to the different domains assessed.

OBJECTIVE

To present a systematic review of the most frequently used instruments for assessing executive functions in older adults with different educational levels in clinical and experimental research.

METHODS

We searched for articles published in the last five years, using the PubMed database with the following terms: "neuropsychological tests", "executive functions", and "mild cognitive impairment". There was no language restriction.

RESULTS

25 articles fulfilled all the inclusion criteria. The seven neuropsychological tests most frequently used to evaluate executive functions in aging were:[1] Trail Making Test (TMT) Form B;[2] Verbal Fluency Test (VFT) - F, A and S;[3] VFT Animals category;[4] Clock Drawing Test (CDT);[5] Digits Forward and Backward subtests (WAIS-R or WAIS-III);[6] Stroop Test; and[7] Wisconsin Card Sorting Test (WCST) and its variants. The domains of executive functions most frequently assessed were: mental flexibility, verbal fluency, planning, working memory, and inhibitory control.

CONCLUSION

The study identified the tests and domains of executive functions most frequently used in the last five years by research groups worldwide to evaluate older adults. These results can direct future research and help build evaluation protocols for assessing executive functions, taking into account the different educational levels and socio-demographic profiles of older adults in Brazil.

Development of a new assessment scale for measuring interaction during staff-assisted transfer of residents in dementia special care units

Background

Mobility problems and cognitive deficits related to transferring or moving persons suffering from dementia are associated with dependency. Physical assistance provided by staff is an important component of residents’ maintenance of mobility in dementia care facilities. Unfortunately, hands-on assistance during transfers is also a source of confusion in persons with dementia, as well as a source of strain in the caregiver. The bidirectional effect of actions in a dementia care dyad involved in transfer is complicated to evaluate. This study aimed to develop an assessment scale for measuring actions related to transferring persons with dementia by dementia care dyads.

Methods

This study was performed in four phases and guided by the framework of the biopsychosocial model and the approach presented by Social Cognitive Theory. These frameworks provided a starting point for understanding reciprocal effects in dyadic interaction. The four phases were 1) a literature review identifying existing assessment scales; 2) analyses of video-recorded transfer of persons with dementia for further generation of items, 3) computing the item content validity index of the 93 proposed items by 15 experts; and 4) expert opinion on the response scale and feasibility testing of the new assessment scale by video observation of the transfer situations.

Results

The development process resulted in a 17-item scale with a seven-point response scale. The scale consists of two sections. One section is related to transfer-related actions (e.g., capability of communication, motor skills performance, and cognitive functioning) of the person with dementia. The other section addresses the caregivers’ facilitative actions (e.g., preparedness of transfer aids, interactional skills, and means of communication and interaction). The literature review and video recordings provided ideas for the item pool. Expert opinion decreased the number of items by relevance ratings and qualitative feedback. No further development of items was performed after feasibility testing of the scale.

Conclusions

To enable assessment of transfer-related actions in dementia care dyads, our new scale shows potential for bridging the gap in this area. Results from this study could provide health care professionals working in dementia care facilities with a useful tool for assessing transfer-related actions.

Electronic supplementary material

The online version of this article (doi:10.1186/s12877-015-0003-6) contains supplementary material, which is available to authorized users.