Clinical Cognitive Assessment Research Articles

Feasibility and psychometric quality of smartphone administered cognitive ecological momentary assessments in women with metastatic breast cancer.

Metastatic breast cancer (MBC) is associated with burdensome side effects, including cognitive changes that require ongoing monitoring. Cognitive ecological momentary assessments (EMAs) allow for assessment of individual cognitive functioning in natural environments and can be administered via smartphones. Accordingly, we sought to establish the feasibility, reliability, and validity of a commercially available cognitive EMA platform. Using a prospective design, clinical cognitive and psychosocial assessments (cognitive batteries; patient reported outcomes) were collected at baseline, followed by a 28-day daily EMA protocol that included self-ratings for symptoms and mobile cognitive tests (memory, executive functioning, working memory, processing speed). Satisfaction and feedback questions were included in follow-up data collection. Feasibility data were analyzed using mixed descriptive methods. Test-retest reliability was examined using intraclass correlation coefficients (ICCs) for each EMA, and Pearson's correlation were used to evaluate convergent validity between cognitive EMAs and baseline clinical cognitive and psychosocial variables. Fifty-one women with MBC (n = 51) completed this EMA study. High satisfaction (median 90%), low burden (median 19%), high adherence rates (mean 94%), and 100% retention rate were observed. ICCs for cognitive tests of working memory, executive function, and processing speed were robust (>0.90) and ICC for memory tests acceptable (>0.66). Other correlational findings indicated strong convergent validity for all cognitive and psychosocial EMAs. Cognitive EMA monitoring for 28 days is feasible and acceptable in women with MBC, with specific cognitive EMAs (mobile cognitive tests; cognitive function self-ratings) demonstrating strong reliability and validity.

Neural divergence between individuals with and without minor depression during dynamic emotion processing: a movie-fMRI Study.

Research on the neuropathological mechanisms underlying minor depression (MD), particularly in individuals with a history of recurrent minor depressive episodes, is very limited. This study focuses on the abnormality in processing real-life emotional stimuli among individuals with MD. Thirty-two individuals with MD and 31 normal controls (NC) were recruited and underwent comprehensive clinical interview, cognitive assessment, and magnetic resonance imaging (MRI) scans. During functional MRI scanning, subjects watched positive, negative, and neutral emotional movie clips. We used the inter-subject correlation and inter-subject functional connectivity analysis to investigate the neural differentiation between MD and NC during film viewing. The relationships between neural differentiation, symptom severity, and psychological resilience were analysed. We found that neural differentiations between individuals with MD and NC in the post cingulate cortex (PCC) and precuneus (PCUN) were consistent across three emotional conditions. Notably, the similarity of neural responses in the PCC and PCUN with NC but not MD was negatively correlated with depressive symptoms. Furthermore, this neural similarity mediated the relationship between psychological resilience and depression severity. Our findings support that the PCC and PCUN, two core areas of the default mode network, play a critical role in MD's emotion processing deficit.

Utility of Tau PET in the diagnostic work up of neurodegenerative dementia among Indian patients

Background and objectivesTau PET is being increasingly appraised as a novel diagnostic modality for dementia work up. Given limited data among South Asians, we assessed the frequency, patterns, phenotypic associations and incremental value of positive Tau PET scans in clinically diagnosed neurodegenerative dementia. MethodsThis cross-sectional study recruited consecutive patients of Alzheimer's disease (AD) and non-AD syndromes (September 2021 to October 2022, India). Participants underwent clinical interview, cognitive assessment, MRI brain and tau PET scan ([F-18]ML-104). Visual read in a priori regions of interest was used to identify patterns of tau deposition in the brain. ResultsWe recruited 54 participants (mean age: 63.2 ± 9.2 years, 64.8 % men, 77.8 % dementia, 70.4 % early onset cases, 37.8 % APOE4+). The analysis identified abnormal tau uptake in 40/54 (74.1 %) participants; with uptake in AD signature areas in 27/40 (67.5 %) cases [cortical subtype (74.1 %), limbic (14.8 %), combined cortical/limbic (11.1 %)], and patterns not conforming to AD in 13/40 (32.5 %) cases. Tau PET substantiated the diagnosis of AD among 17/19 (89.5 %) cases with clinically diagnosed AD dementia, 8/23 (34.8 %) cases with suspected non-AD cause, and 2/12 (16.7 %) cases with mild cognitive impairment. A trend for increasing proportion of early onset cases, and worsening cognition, behavior and functional ability was seen, from ‘limbic’ to ‘combined cortical/limbic’ to ‘cortical’ subgroups. ConclusionTau PET is a useful modality to differentiate AD dementia from other neurodegenerative causes in the Indian setting where amyloid biomarkers are not widely available. Biological subtypes of AD map well onto clinical phenotypes and need study in larger cohorts.

Comparing machine learning and deep learning models to predict cognition progression in Parkinson's disease.

Cognitive decline in Parkinson's disease (PD) varies widely. While models to predict cognitive progression exist, comparing traditional probabilistic models to deep learning methods remains understudied. This study compares sequential modeling techniques to identify cognitive progression in individuals with and without PD. Using data from the Parkinson's Progression Marker Initiative, shallow Markov, deep recurrent (long short-term memory [LSTM]), and nonrecurrent (temporal fusion transformer [TFT]) models were compared to predict cognitive status over time. Cognitive status was categorized into normal cognition (NC), mild cognitive impairment (MCI), and dementia. Predictions were made annually for up to 3 years using clinical data, including demographics, cognitive assessments, PD severity, and medical history. Each approach was evaluated using inverse probability weighted (IPW-) F1 scores. An ensemble method combined outputs from the Markov, LSTM, and TFT models. The dataset included 917 individuals (53% PD; 30% at risk for PD; 17% Healthy Controls). The TFT model outperformed others across all annual periods (IPW-F1 = 0.468) compared to the Markov (IPW-F1 = 0.349) and LSTM (IPW-F1 = 0.414) models, with improved performance using an ensemble approach (IPW-F1 = 0.502). For MCI and dementia predictions, which were rarer occurrences compared to NC status (ratios: 50:8:1), the TFT model consistently outperformed competing models, achieving IPW-F1 scores of 0.496 and 0.533 for MCI and dementia, respectively. In conclusion, sequential deep learning models like TFT, which mitigate long-term memory loss and can interpret complex, high-dimensional data, perform best overall in predicting clinically important cognitive transitions. These methods should be further explored for predicting degenerative conditions.

Investigating DTI-ALPS index and its association with cognitive impairments in patients with alcohol use disorder: A diffusion tensor imaging study

BackgroundThe glymphatic system, a physiological pathway recently identified, has attracted considerable attention for its potential role in the pathophysiology of neurological disorders. Despite significant research efforts, the exact contribution of the glymphatic system to alcohol use disorder (AUD) remains largely elusive. This study was a secondary analysis by analyzing a subset of the original data to examine changes in the ALPS index and determine its association with cognitive abilities in individuals with AUD. MethodsWe recruited 40 individuals with AUD and 40 healthy controls (HC). All subjects underwent MRI scans and clinical cognitive scale assessments. Diffusion tensor imaging along the perivascular space (DTI-ALPS) index was used to estimate the differences in glymphatic activity between both groups, and linear regression analysis was used to examine the association between ALPS index and cognitive performance measures. ResultsA statistically significant difference in the ALPS index was observed between both groups (p < 0.001), with the AUD group showing statistically lower ALPS index compared with the HC group (p < 0.001). Additionally, a positive correlation was identified between the ALPS index and MoCA/MMSE scores, indicating that higher ALPS index is indicative of better cognitive performance in individuals with AUD. ConclusionsThe findings of this study provide evidence of ALPS index in individuals with AUD and establish a link between the ALPS index and the cognitive impairments observed in AUD patients. These findings might suggest the importance of glymphatic activity in the emergence of cognitive deficits among those impacted by AUD, but a stronger link between ALPS index and glymphatic system is needed to better understand the relationship between glymphatic function and healthy outcomes.

Association between Multi-Domain Lifestyle and Objective Cognitive Impairment in Elderly People with SCD and MCI in Chinese Communities.

Controlling the lifestyle associated with dementia risk can delay the process of cognitive decline. Subjective cognitive decline (SCD) and mild cognitive impairment (MCI) are early states in the development of dementia and are also the window period for early intervention in dementia. The purpose of this study was to explore the association between multi-domain lifestyle and objective cognitive impairment in elderly people with SCD and MCI in Chinese communities and to provide reference for effective implementation of precise health management measures to reduce the risk of dementia. A total of 265 middle-aged and elderly volunteers recruited from the community were divided into SCD group (107 cases), MCI group (80 cases), and healthy control (HC) group (78 cases). All participants received clinical interview, examination, and cognitive assessments. The total Dementia Risk Reduction Lifestyle Scale (DRRLS) scores in the HC, SCD, and MCI groups [110.00 (11.25) vs. 101.00 (10.00) vs. 79.50 (20.75)] exhibited statistically significant differences among them. The total score of the DRRLS showed a significant negative correlation with the Trail-Making Test (TMT), and significant positive correlations with both the Verbal Fluency Test (VFT) and Auditory Verbal Learning Test (AVLT) scores (p < 0.05). After adjusting for confounding factors, such as age and years of education, multiple linear regression analysis revealed several points. In the SCD group, brain-strengthening exercise and interpersonal relationship scores were negatively correlated with TMT scores (β = -11.257, -15.077; all p < 0.05), while health responsibility, smoking control behavior, and interpersonal relationship scores were positively correlated with AVLT scores (β = 0.485, 0.344, and 0.406; all p < 0.05). In the MCI Group, brain-strengthening exercise, brain-healthy diet, and interpersonal relationship were negatively correlated with TMT (β = -22.011, -16.206, -11.696; all p < 0.01), whereas health responsibility, mental activity, smoking control behavior, interpersonal relationship, and stress management were positively correlated with AVLT (β = 0.450, 0.435, 0.308, 0.256, 0.607; all p < 0.05). In Chinese communities, the unhealthy lifestyle of elderly individuals with SCD and MCI is significantly associated with cognitive function impairment. The greater their unhealthy lifestyle habits, the more pronounced the scope and severity of cognitive function impairment becomes. Furthermore, different dimensions of lifestyle have varying impacts on cognitive domains.

Alzheimer's Disease and Vascular Dementia, Connecting and Differentiating Features.

Alzheimer's disease (AD) and vascular dementia (VD) are the leading causes of dementia, presenting a significant challenge in differential diagnosis. While their clinical presentations can overlap, their underlying pathologies are distinct. AD is characterized by the accumulation of amyloid plaques and neurofibrillary tangles, leading to progressive neurodegeneration. VD, on the other hand, arises from cerebrovascular insults that disrupt blood flow to the brain, causing neuronal injury and cognitive decline. Despite distinct etiologies, AD and VD share common risk factors such as hypertension, diabetes, and hyperlipidemia. Recent research suggests a potential role for oral microbiota in both diseases, warranting further investigation. The diagnostic dilemma lies in the significant overlap of symptoms including memory loss, executive dysfunction, and personality changes. The absence of definitive biomarkers and limitations of current neuroimaging techniques necessitate a multi-modal approach integrating clinical history, cognitive assessment, and neuroimaging findings. Promising avenues for improved diagnosis include the exploration of novel biomarkers like inflammatory markers, MMPs, and circulating microRNAs. Additionally, advanced neuroimaging techniques hold promise in differentiating AD and VD by revealing characteristic cerebrovascular disease patterns and brain atrophy specific to each condition. By elucidating the complexities underlying AD and VD, we can refine diagnostic accuracy and optimize treatment strategies for this ever-growing patient population. Future research efforts should focus on identifying disease-specific biomarkers and developing more effective neuroimaging methods to achieve a definitive diagnosis and guide the development of targeted therapies.

Methods for assessment of rey auditory verbal learning test performance in memory clinic patients and healthy adults - at the cross-roads of learning theory and clinical utility

Background: Knowledge is still lacking regarding the preferred method for evaluation of learning in the Rey Auditory Verbal Learning Test (RAVLT). Validity of different methods was examined by the effect size in differentiating diagnostic stages in memory clinic patients versus healthy adults and the strength of association between RAVLT performance and brain atrophy. Method: The study included individuals with dementia (n = 247), Mild Cognitive Impairment (MCI, n = 709), Subjective Cognitive Impairment (SCI, n = 175) and cognitively unimpaired adults serving as healthy controls (HC, n = 102). All patients went through a comprehensive clinical examination and neuropsychological assessment of cognition including episodic memory gauged with RAVLT and brain imaging of medial temporal atrophy, cortical atrophy, and white matter hyperintensity. Results: The standard method for evaluation of learning in RAVLT (summed score over five trials) together with the late learning method (mean of trials 4 and 5) were the two most powerful methods according to group differentiation (discriminant validity). Both methods also showed considerable association with medial temporal atrophy (construct validity). The initial RAVLT performance represented by results on trial 1 and the constant in regression analysis with the power function provided information regarding attention that was important for the separation of SCI and HC. Conclusions: The most favorable clinical utility was indicated by discriminant and construct validity by total learning (standard method) including both attention- and learning-related parts and late learning of RAVLT performance, while theoretical understanding of mental processes involved in RAVLT performance was provided by the distinction between initial versus the subsequent learning performance.

Unearthing Subtle Cognitive Variations: A Digital Screening Tool for Detecting and Monitoring Mild Cognitive Impairment

Early diagnosis of mild cognitive impairment (MCI) is pivotal in mitigating the risk of cognitive impairment and the onset of dementia. However, prevailing clinical cognitive screening tests and biomarker assessment approaches often suffer from drawbacks such as high cost, invasiveness, time consumption, or subjectivity. In China, existing digital cognitive assessment tools face multiple challenges due to their distinctive cultural, language, and healthcare landscape. Therefore, we embarked on a study to develop a digital cognitive assessment tool, evaluate its efficacy in distinguishing between healthy individuals and MCI patients, and examine its acceptability among Chinese older adults. Through a series of symposiums, programming, and interviews with stakeholders, we iteratively designed the "BrainNursing" mobile application. The system consists of eleven single tasks and three dual tasks, each taking only 1–3 minutes. Subsequently, we conducted statistical comparisons of movement kinetics and physiological signals recorded during cognitive testing in 181 older adults to investigate which parameters could serve as effective digital biomarkers for MCI screening. Leveraging machine learning classifiers and a majority voting principle, we evaluated the classification performance of the BrainNursing system in detecting MCI, yielding an accuracy rate of 90.3%. Furthermore, our analysis of movement kinetics revealed that time, score, and sequence features are crucial in cognitive assessment. Contrasting with their healthy counterparts, MCI patients exhibited decreased heart rate variability, increased sympathetic nervous system activity, and weakened autonomic nervous system regulation in response to stimuli during cognitive testing. Finally, user experience feedback indicated that participants universally perceived BrainNursing as a convenient and user-friendly cognitive screening tool and provided valuable insights for further improvement.

Hereditary spastic paraparesis type 46 (SPG46): new GBA2 variants in a large Italian case series and review of the literature.

Hereditary spastic paraparesis (HSP) is a group of central nervous system diseases primarily affecting the spinal upper motor neurons, with different inheritance patterns and phenotypes. SPG46 is a rare, early-onset and autosomal recessive HSP, linked to biallelic GBA2 mutations. About thirty families have been described worldwide, with different phenotypes like complicated HSP, recessive cerebellar ataxia or Marinesco-Sjögren Syndrome. Herein, we report five SPG46 patients harbouring five novel GBA2 mutations, the largest series described in Italy so far. Probands were enrolled in five different centres and underwent neurological examination, clinical cognitive assessment, column imaging for scoliosis assessment, ophthalmologic examination, brain imaging, GBA2 activity in peripheral blood cells and genetic testing. Their phenotype was consistent with HSP, with notable features like upper gaze palsy and movement disorders. We review demographic, genetic, biochemical and clinical information from all documented cases in the existing literature, focusing on the global distribution of cases, the features of the syndrome, its variable presentation, new potential identifying features and the significance of measuring GBA2 enzyme activity.

Altered dynamic amplitude of low-frequency fluctuation in individuals at high risk for Alzheimer's disease.

The brain's dynamic spontaneous neural activity is significant in supporting cognition; however, how brain dynamics go awry in subjective cognitive decline (SCD) and mild cognitive impairment (MCI) remains unclear. Thus, the current study aimed to investigate the dynamic amplitude of low-frequency fluctuation (dALFF) alterations in patients at high risk for Alzheimer's disease and to explore its correlation with clinical cognitive assessment scales, to identify an early imaging sign for these special populations. A total of 152 participants, including 72 SCD patients, 44 MCI patients and 36 healthy controls (HCs), underwent a resting-state functional magnetic resonance imaging and were assessed with various neuropsychological tests. The dALFF was measured using sliding-window analysis. We employed canonical correlation analysis (CCA) to examine the bi-multivariate correlations between neuropsychological scales and altered dALFF among multiple regions in SCD and MCI patients. Compared to those in the HC group, both the MCI and SCD groups showed higher dALFF values in the right opercular inferior frontal gyrus (voxel P < .001, cluster P < .05, correction). Moreover, the CCA models revealed that behavioural tests relevant to inattention correlated with the dALFF of the right middle frontal gyrus and right opercular inferior frontal gyrus, which are involved in frontoparietal networks (R = .43, P = .024). In conclusion, the brain dynamics of neural activity in frontal areas provide insights into the shared neural basis underlying SCD and MCI.

Naturalistic assessment of reaction time variability in older adults at risk for Alzheimer's disease.

Maintaining attention underlies many aspects of cognition and becomes compromised early in neurodegenerative diseases like Alzheimer's disease (AD). The consistency of maintaining attention can be measured with reaction time (RT) variability. Previous work has focused on measuring such fluctuations during in-clinic testing, but recent developments in remote, smartphone-based cognitive assessments can allow one to test if these fluctuations in attention are evident in naturalistic settings and if they are sensitive to traditional clinical and cognitive markers of AD. Three hundred and seventy older adults (aged 75.8 +/- 5.8 years) completed a week of remote daily testing on the Ambulatory Research in Cognition (ARC) smartphone platform and also completed clinical, genetic, and conventional in-clinic cognitive assessments. RT variability was assessed in a brief (20-40 seconds) processing speed task using two different measures of variability, the Coefficient of Variation (CoV) and the Root Mean Squared Successive Difference (RMSSD) of RTs on correct trials. Symptomatic participants showed greater variability compared to cognitively normal participants. When restricted to cognitively normal participants, APOE ε4 carriers exhibited greater variability than noncarriers. Both CoV and RMSSD showed significant, and similar, correlations with several in-clinic cognitive composites. Finally, both RT variability measures significantly mediated the relationship between APOE ε4 status and several in-clinic cognition composites. Attentional fluctuations over 20-40 seconds assessed in daily life, are sensitive to clinical status and genetic risk for AD. RT variability appears to be an important predictor of cognitive deficits during the preclinical disease stage.

Correlation between the changes of brain amplitude of low-frequency fluctuation and cognitive impairment in patients with neuropsychiatric lupus.

To explore the relationship between brain function changes and clinical serological indicators and behavioral cognitive assessment in patients with neuropsychiatric systemic lupus erythematosus (NPSLE), and understand the pathogenesis of NPSLE from the perspective of imaging. The resting-state functional imaging data, clinical serological, and behavioral cognitive assessment scores of 28 patients with NPSLE and 22 healthy controls (HC) were prospectively collected. The resting-state amplitude of low-frequency fluctuation (ALFF) values obtained from the analysis and processing were correlated with the serological data and behavioral cognitive assessment scores to determine the relationship between these data. The average age of the patients of the NPSLE group was older than that of the HC group; significant differences in education level, Auditory Verbal Learning Test Hua Shan Version (AVLT-H), and Trail Making Test scores were observed between the two groups. The NPSLE group demonstrated increased brain activity in the insula, precentral gyrus, and superior temporal gyrus, and decreased brain activity in the superior parietal gyrus. The ALFF value of the insula positively correlated with the Anti-β2gp1 antibody and negatively correlated with the anti-nucleosome antibody and the AVL-recall (RC) score. The ALFF of the precentral gyrus negatively correlated with the AVL-immediate recall (I). The ALFF value of the superior temporal gyrus negatively correlated with the AVL-RC score. The left superior parietal gyrus positively correlated with the c-reactive protein. The right superior parietal gyrus positively correlated with the System Lupus Erythematosus Disease Activity Index and negatively correlated with the AVL-I score. Patients with NPSLE show different brain activity changes in different brain regions, and the abnormal brain regions are correlated with certain lupus antibodies, inflammatory factors, and cognitive assessment, thereby suggesting that the correlation between the three could provide novel insights into the pathogenesis of NPSLE.

Altered Iron and Microstructure in Huntington's Disease Subcortical Nuclei: Insight From 7T MRI.

Pathophysiological changes of Huntington's disease (HD) can precede symptom onset by decades. Robust imaging biomarkers are needed to monitor HD progression, especially before the clinical onset. To investigate iron dysregulation and microstructure alterations in subcortical regions as HD imaging biomarkers, and to associate such alterations with motor and cognitive impairments. Prospective. Fourteen individuals with premanifest HD (38.0 ± 11.0 years, 9 females; far-from-onset N = 6, near-onset N = 8), 21 manifest HD patients (49.1 ± 12.1 years, 11 females), and 33 age-matched healthy controls (43.9 ± 12.2 years, 17 females). 7 T, T1-weighted imaging, quantitative susceptibility mapping, and diffusion tensor imaging. Volume, susceptibility, fractional anisotropy (FA), and mean diffusivity (MD) within subcortical brain structures were compared across groups, used to establish HD classification models, and correlated to clinical measures and cognitive assessments. Generalized linear model, multivariate logistic regression, receiver operating characteristics with the area under the curve (AUC), and likelihood ratio test comparing a volumetric model to one that also includes susceptibility and diffusion metrics, Wilcoxon paired signed-rank test, and Pearson's correlation. A P-value <0.05 after Benjamini-Hochberg correction was considered statistically significant. Significantly higher striatal susceptibility and FA were found in premanifest and manifest HD preceding atrophy, even in far-from-onset premanifest HD compared to controls (putamen susceptibility: 0.027 ± 0.022 vs. 0.018 ± 0.013 ppm; FA: 0.358 ± 0.048 vs. 0.313 ± 0.039). The model with additional susceptibility, FA, and MD features showed higher AUC compared to volume features alone when differentiating premanifest HD from HC (0.83 vs. 0.66), and manifest from premanifest HD (0.94 vs. 0.83). Higher striatal susceptibility significantly correlated with cognitive deterioration in HD (executive function: r = -0.600; socioemotional function: r = -0.486). 7 T MRI revealed iron dysregulation and microstructure alterations with HD progression, which could precede volume loss, provide added value to HD differentiation, and might be associated with cognitive changes. 2 TECHNICAL EFFICACY: Stage 2.

Resting-state fMRI is associated with trauma experiences, mood and psychosis in Afro-descendants with bipolar disorder and schizophrenia

BackgroundBipolar disorder (BD) and schizophrenia (SCZ) may exhibit functional abnormalities in several brain areas, including the medial temporal and prefrontal cortex and hippocampus; however, a less explored topic is how brain connectivity is linked to premorbid trauma experiences and clinical features in non-Caucasian samples of SCZ and BD. Methods: Sixty-two individuals with SCZ (n = 20), BD (n = 21), and healthy controls (HC, n = 21) from indigenous and African ethnicity were submitted to clinical screening (Di-PAD), traumata experiences (ETISR-SF), cognitive and functional MRI assessment. The item psychosis/hallucinations in SCZ patients showed a negative correlation with the global efficiency (GE) in the right dorsal attention network. The items mania, irritable mood, and racing thoughts in the Di-PAD scale had a significant negative correlation with the GE in the parietal right default mode network. Conclusions: Differences in the activation of specific networks were associated with earlier disease onset, history of physical abuse, and more severe psychotic and mood symptoms in SCZ and BD subjects of indigenous and black ethnicity. Findings provide further evidence on SZ and BD's brain connectivity disturbances, and their clinical significance, in non-Caucasian samples.

Radiomics models based on cortical damages for identification of multiple sclerosis with cognitive impairment

BackgroundCognitive impairment (CI) is a common symptom in multiple sclerosis (MS) patients. Cortical damages can be closely associated with cognitive network dysfunction and clinically significant CI in MS. So, in this study, We aimed to develop a radiomics model to efficiently identify the MS patients with CI based on clinical data and cortical damages. MethodsOne hundred and eighteen patients with MS were divided into CI and normal cognitive (NC) cohorts (62/56) as defined by the Montreal Cognitive Assessment (MoCA). All participants were randomly divided into train and test sets with a ratio of 7:3. The radiomic features were selected by using the least absolute shrinkage and selection operator (LASSO) method. The discrimination models were built with the support vector machines (SVM) by the clinical data, radiomic features, and merge data, respectively. And the patients were further divided according to each cognitive domain including memory, visuospatial, language, attention and executive, and each domain model was applied by the most suitable classifier. ResultsA total of 2298 features were extracted, of which 36 were finally selected. The merge model showed the greatest performance with the area under the curve (AUC) of 0.86 (95 % confidence interval: 0.81–0.91), accuracy (ACC) of 0.78, sensitivity of 0.79 and specificity of 0.77 in test cohort. However, although the visuospatial domain model showed the highest AUC of 0.71 (95 % confidence interval: 0.61–0.81) among five domain models, other domain models did not meet satisfactory results with a relatively low AUC, ACC, sensitivity and specificity. ConclusionsThe radiomics model based on clinical data and cortical damages had a great potential to identify the MS patients with CI for clinical cognitive assessment.

Associations between neuropsychiatric symptoms and ADRD serum biomarkers in Mexican American and non‐Hispanic white adults with mild cognitive impairment

AbstractBackgroundMild cognitive impairment (MCI) is a heterogenous diagnostic category with trajectories ranging from reversion to unimpaired cognition to progression to dementia. Neuropsychiatric symptoms such as depression and irritability are common and influence quality of life of patients and caregivers. The role of neuropsychiatric symptoms on disease biology, presentation, and course remains poorly understood. The goal of this study was to evaluate the associations between neuropsychiatric symptoms and serum ADRD biomarkers in Mexican American and non‐Hispanic white participants diagnosed with MCI.MethodParticipants from the Texas Alzheimer’s Research and Care Consortium underwent a blood draw and clinical evaluation, including psychopathological and cognitive assessments. Diagnoses of MCI were adjudicated in consensus reviews. The presence and severity of neuropsychiatric symptoms were assessed by informant report using the Neuropsychiatric Inventory (NPI). Serum levels of total tau, neurofilament light (NfL), and glial fibrillary acidic protein (GFAP) were assessed using Simoa HD‐X Analyzer. Associations between NPI total score and individual items with serum biomarker levels were assessed using linear regression adjusted for age and sex.ResultA total of 425 participants (mean age: 71 ± 9 years, 62% female, 74% Mexican American) had a diagnosis of MCI and serum ADRD biomarkers (Table 1). Total NPI score was not associated with total tau (ß = 0.002, p = 0.609), NfL (ß = 0.001, p = 0.658), or GFAP (ß = 0.001, p = 0.777). However, endorsement of appetite changes was associated with higher NfL (ß = 0.077, p = 0.006) and GFAP (ß = 0.088, p = 0.002) levels. Stratified analyses indicated associations of appetite changes with serum NfL (ß = 0.108, p = 0.002) and GFAP (ß = 0.095, p = 0.003) in Mexican Americans, but not in non‐Hispanic whites (NfL: ß = 0.022, p = 0.633, GFAP: ß = 0.102, p = 0.066).There were no other significant associations between individual items on the NPI with serum biomarkers (p&gt;0.05, Bonferroni adjustment p±0.003).ConclusionWithin Mexican American adults with MCI, changes in appetite were associated with higher serum NFL and GFAP levels. As elevations in circulating NfL and GFAP levels are associated with ADRD pathology and accelerated disease progression, appetite changes, a non‐invasive and easily discernible behavioral phenotype, may predict higher likelihood of worsening cognitive course. Future longitudinal studies will be necessary to confirm predictive utility of appetite changes for disease progression.

Design and development of the intelligent voice recognition‐based cognitive assessment WeChat mini‐program

AbstractBackgroundEarly screening of mild cognitive impairment (MCI) is crucial for the elderly to access formal diagnosis and intervention of Alzheimer’s Disease (AD) and related dementias (ADRD) at early stages. Owing to the rapid development of artificial intelligence (AI) and voice recognition technology, the detection method using speech patterns as digital biomarkers collected by digital consumer devices can accommodate a huge demand for early and large‐scale detection. We here reported the design and development of the Shanghai Cognitive Screening (SCS) mini‐program, the first intelligent voice recognition‐based cognitive assessment WeChat mini‐program in China.MethodThe SCS mini‐program was developed based on the cognitive paradigm and classic pencil‐and‐paper neuropsychological assessments (e.g. Montreal cognitive assessment basic [MoCA‐B]). Through Automatic Speech Recognition (ASR), users speak to complete tasks including Naming, Immediate Recall, Delayed Recall, Symbol Digit Modalities Test (SDMT), Delayed RecallII, and Recognition (Figure 1). The acoustic, phonetics, and linguistic speech pattern variables would also be extracted and processed as digital biomarkers. The SCS intelligent prediction model enrolls speech pattern digital biomarkers, individual task scores, and time use variables with age, gender, and education level as linking variables, which enables to grade the user’s global cognitive function and individual cognitive domains (Figure 2).ResultAfter completing all tasks in the SCS, users can immediately read the comprehensive results which are divided into 4 categories corresponding to 4 grading intervals: “healthy” (cognitively normal), “low risk” (suspected SCD), “medium‐high risk” (suspected MCI), and “high risk” (suspected AD). We also use a radar chart with scores of cognitive domains (i.e., memory, attention, visual perception, language, and executive functions), a memory trend graph (i.e., immediate and delayed recalls), an attention persistence graph, and related advice in the automatically generated report (Figure 3).ConclusionThe SCS mini‐program is more efficient and economical compared to traditional paper‐based cognitive assessments. It is suitable for clinical cognitive assessment, remote self‐rating, and community screening for MCI and dementias among Chinese older adults and other ADRD high‐risk groups. Clinical trials are yet to be conducted to validate the accuracy and diagnostic value of the SCS WeChat mini‐program.

51 Feasibility of Remote Administration of a Modified UDSv3 Cognitive Battery

Objective:Face-to-face administration is the “gold standard” for both research and clinical cognitive assessments. However, many factors may impede or prevent face-to-face assessments, including distance to clinic, limited mobility, eyesight, or transportation. The COVID19 pandemic further widened gaps in access to care and clinical research participation. Alternatives to face-to-face assessments may provide an opportunity to alleviate the burden caused by both the COVID-19 pandemic and longer standing social inequities. The objectives of this study were to develop and assess the feasibility of a telephone- and video-administered version of the Uniform Data Set (UDS) v3 cognitive batteries for use by NIH-funded Alzheimer’s Disease Research Centers (ADRCs) and other research programs.Participants and Methods:Ninety-three individuals (M age: 72.8 years; education: 15.6 years; 72% female; 84% White) enrolled in our ADRC were included. Their most recent adjudicated cognitive status was normal cognition (N=44), MCI (N=35), mild dementia (N=11) or other (N=3). They completed portions of the UDSv3 cognitive battery, plus the RAVLT, either by telephone or video-format within approximately 6 months (M:151 days) of their annual in-person visit, where they completed the same in-person cognitive assessments. Some measures were substituted (Oral Trails for TMT; Blind MoCA for MoCA) to allow for phone administration. Participants also answered questions about the pleasantness, difficulty level, and preference for administration mode. Cognitive testers provided ratings of perceived validity of the assessment. Participants’ cognitive status was adjudicated by a group of cognitive experts blinded to most recent inperson cognitive status.Results:When results from video and phone modalities were combined, the remote assessments were rated as pleasant as the inperson assessment by 74% of participants. 75% rated the level of difficulty completing the remote cognitive assessment the same as the in-person testing. Overall perceived validity of the testing session, determined by cognitive assessors (video = 92%; phone = 87.5%), was good. There was generally good concordance between test scores obtained remotely and in-person (r = .3 -.8; p &lt; .05), regardless of whether they were administered by phone or video, though individual test correlations differed slightly by mode. Substituted measures also generally correlated well, with the exception of TMT-A and OTMT-A (p &gt; .05). Agreement between adjudicated cognitive status obtained remotely and cognitive status based on in-person data was generally high (78%), with slightly better concordance between video/in-person (82%) vs phone/in-person (76%).Conclusions:This pilot study provided support for the use of telephone- and video-administered cognitive assessments using the UDSv3 among individuals with normal cognitive function and some degree of cognitive impairment. Participants found the experience similarly pleasant and no more difficult than inperson assessment. Test scores obtained remotely correlated well with those obtained in person, with some variability across individual tests. Adjudication of cognitive status did not differ significantly whether it was based on data obtained remotely or in-person. The study was limited by its’ small sample size, large test-retest window, and lack of randomization to test-modality order. Current efforts are underway to more fully validate this battery of tests for remote assessment. Funded by: P30 AG072947 &amp; P30 AG049638-05S1

Employment loss and financial hardship among women with breast cancer receiving chemotherapy.

505 Background: A breast cancer diagnosis and subsequent treatment an have both physical and emotional toxicities. Many who are employed have to reduce hours or take leave, often resulting in loss of income. The effect of this loss of income is potentially compounded by the cost of medical care and can result in significant financial hardship. However, the association between employment income loss and financial hardship is not well studied. Methods: This is an analysis of the Genetics, Molecular Mechanisms, and Symptom Science (GEMMS) longitudinal study of people with newly diagnosed breast cancer undergoing curative intent chemotherapy and surgery. The study collects clinical data, patient-reported outcomes, cognitive assessments, and biospecimens for correlative studies. Participants completed assessments at baseline (prior to chemotherapy initiation), mid-way, and chemotherapy completion, as well as 3 and 6 month post chemotherapy and annually thereafter for up to 5 years. This analysis was restricted to data collected within 1 year of completing chemotherapy. Multivariable logistic regression models were constructed to determine which features were associated with employment loss and financial hardship. Financial hardship was assessed using a single question, “In the past week, has your physical condition or medical treatment caused you financial difficulties?”. Results: 149 participants are included in GEMMS, of which 111 (75%) were employed at diagnosis. Within the 1 year following completion of chemotherapy, 48% of working women reported at least one 4 week period of where they did not work. This was most common 3 months following completion, where 30% reported being out of work for the prior 4 weeks. None of the variables tested (age, race, marital status, education level, stage of cancer, etc.) predicted employment loss. Overall, 61% of women reported financial hardship within the year following commencement of treatment. Neither being employed at diagnosis nor suffering employment loss were associated with experiencing financial hardship. Of the other variables tested, only marital status was associated with financial hardship. Married women were 70% ( p = 0.02) less likely to report financial hardship than unmarried women. Conclusions: Nearly half of women receiving curative intent chemotherapy for breast cancer report job loss of 4 weeks or more and nearly two-thirds report financial hardship during the year following commencement of chemotherapy. These negative consequences of breast cancer and its treatment seem to effect women of different backgrounds similarly.