Cognitive Impairment Group Research Articles

A multimodal learning machine framework for Alzheimer’s disease diagnosis based on neuropsychological and neuroimaging data

Alzheimer’s disease (AD) is the most prevalent form of dementia, with no current cure. Early screening and intervention are vital. In multimodal AD data, besides neuroimaging dimensions, neuropsychological tests based on cognitive domains also provide the clinical information for diagnosing AD. However, previous multimodal methods often fuse these neuropsychological test scores with other data, losing the rich clinical details inherent in each test, including videos, speech, images, and text. To address this, we propose a novel framework with an entropy-based polynomial dimension expansion function that restores this critical information by accurately calculating the optimal polynomial degree. Additionally, the proposed framework offers a series of cognitive-based Extreme Learning Machine (ELM) models to better utilize the detailed clinical insights from neuropsychological tests, reducing diagnostic redundancy and noise. Finally, we design a boosting ensemble strategy that combines diagnostic models from various dimensions and cognitive domains, automatically optimizing weights to enhance diagnostic accuracy. Tested on the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset, our approach achieves over 98% accuracy and F1 scores, with no observed bias between mild cognitive impairment (MCI) and AD groups. Therefore, our framework can offer clinicians more logical recommendations for diagnosing and managing the disease.

Disparities in the diagnostic efficacy of radiomics models in predicting various degrees of cognitive impairment in patients with cerebral small vessel disease

BackgroundAim to validate the diagnostic efficacy of radiomics models for predicting various degrees of cognitive impairment in patients with cerebral small vessel disease (CSVD).MethodsParticipants were divided into mild cognitive impairment group (mild-CSVD group) and sever cognitive impairment group (sever-CSVD group) according to Montreal Cognitive Assessment (MoCA) performance, 98 gender-age-education matched subjects served as normal controls. Radiomic features were extracted from the segmented hippocampus using PyRadiomics. The feature preprocessing involved replacing missing values with the mean, applying stratified random sampling to allocate subjects into training (80%) and testing (20%) sets, ensuring balance among the three classes (normal controls, mild-CSVD group, and sever-CSVD group). A feature selection method was applied to identify discriminative radiomic features, with the optimal texture feature chosen for developing diagnostic models. Performance was evaluated in both the training and testing sets using receiver operating characteristic (ROC) curve analysis.ResultsThe radiomics model achieved an accuracy of 0.625, an AUC of 0.593, a sensitivity of 0.828, and a specificity of 0.316 in distinguishing mild-CSVD group from normal controls. When distinguishing mild-CSVD group from sever-CSVD group, the radiomics model reached an accuracy of 0.683, an AUC of 0.660, a sensitivity of 0.167, and a specificity of 0.897. Similarly, in distinguishing sever-CSVD group from normal controls, the radiomics model exhibited an accuracy of 0.781, an AUC of 0.818, a sensitivity of 0.538, and a specificity of 0.947.ConclusionRadiomics model based on hippocampal texture had disparities in the diagnostic efficacy of radiomics models in predicting various degrees of cognitive impairment in patients with CSVD.

Prediction and validation of mild cognitive impairment in occupational dust exposure population based on machine learning

ObjectiveWorkers exposed to dust for extended periods may experience varying degrees of cognitive impairment. However, limited research exists on the associated risk factors. This study aims to identify key variables using machine learning algorithms (ML) and develop a model to predict the occurrence of mild cognitive impairment in miners. Methods: A total of 1938 miners were included in the study. Univariate analysis and multivariable logistic regression were employed to identify independent risk factors for cognitive impairment among miners. The dataset was randomly divided into a training set and a validation set in an 8:2 ratio of 1550 and 388 individuals, respectively. An additional group of 351 miners was collected as a test set for cognitive impairment assessment. Seven machine learning algorithms, including XGBoost, Logistic Regression, Random Forest, Complement Naive Bayes, Multi-layer Perceptron, Support Vector Machine, and K-Nearest Neighbors, were used to establish a predictive model for mild cognitive impairment in the dust-exposed population, based on baseline characteristics of the workers. The predictive performance of the models was evaluated using the Area Under the Receiver Operating Characteristic Curve (AUC), and the XGBoost model was further explained using the Shapley Additive exPlanations (SHAP) package. Cognitive function assessments using rank sum tests were conducted to compare differences in cognitive domains between the mild cognitive impairment group and the normal group. Results: Univariate and multivariable logistic regression analyses revealed that education level, Age, Work years, SSRS (Self-Rating Scale for Stress), and HAMA (Hamilton Anxiety Rating Scale) were independent risk factors for cognitive impairment among dust-exposed workers. Comparative analysis of the performance of the seven machine learning algorithms demonstrated that XGBoost (training set: AUC=0.959, validation set: AUC=0.795) and Logistic Regression (training set: AUC=0.818, validation set: AUC=0.816) models exhibited superior predictive performance. Results from the test set showed that the AUC of the XGBoost model (AUC=0.913) outperformed the Logistic Regression model (AUC=0.778). Miners with mild cognitive impairment exhibited significant impairments (p<0.05) in visual-spatial abilities, attention, abstract thinking, and memory areas. Conclusion: Machine learning algorithms can predict the risk of cognitive impairment in this population, with the XGBoost algorithm showing the best performance. The developed model can guide the implementation of appropriate preventive measures for dust-exposed workers.

Comorbidities, medications, depression, and physical performance measures associated with severe cognitive impairments in community-dwelling adults

Cognitive impairment negatively impacts health, psychological, social, and economic domains. Cognitive impairment commonly affects physical functions in older adults, whereas these are deteriorated. However, the prevalence and associated factors of cognitive impairment among community-dwelling adults in Saudi Arabia have not been investigated yet. This study aimed to examine the prevalence of severe cognitive impairment and its associated factors in community-dwelling older adults in Saudi Arabia. This cross-sectional study involved adults aged ≥50 years. Demographic data and clinical data, including number of medications and body mass index (BMI), were collected. Cognitive impairment and depressive symptoms were measured using Arabic versions of the Montreal Cognitive Assessment (MoCA) and Patient Health Questionnaire-9 (PHQ-9), respectively. The participants were divided into severe cognitive impairment and mild cognitive impairment or normal cognitive function groups based on a score of &lt;20 or ≥20, respectively, using the MoCA. Physical measures included dynamic gait index (DGI) scores, timed up-and-go (TUG), 5 times sit-to-stand (5XSST), functional reach test, and 6-minute walk test. A total of 206 participants (female: n = 96) were included. The prevalence of severe cognitive impairment in the community-dwelling older adults was 12.6%. The number of chronic conditions (odds ratio [OR]: 2.31, p&lt;0.001), number of medications (OR: 1.36, p = 0.003), and depressive symptoms using PHQ-9 (OR: 1.11, p = 0.009) were significantly associated with severe cognitive impairment after adjustment for other covariates, including age, sex, and BMI. Based on the physical function measures, only the scores for DGI (OR: 0.86, p = 0.003), TUG (OR: 1.16, p = 0.035) and 5XSST (OR: 1.25, p &lt;0.001) were significantly associated with severe cognitive impairment. This study revealed a high prevalence of severe cognitive impairment among community-dwelling adults in Saudi Arabia. Its major risk factors include depressive symptoms, number of chronic conditions and medications, and physical measures, including DGI, TUG, and 5XSST.

A new test for evaluation of marginal cognitive function deficits in idiopathic normal pressure hydrocephalus through expressing texture recognition by sound symbolic words.

The number of dementia patients is increasing with population aging. Preclinical detection of dementia in patients is essential for access to adequate treatment. In previous studies, dementia patients showed texture recognition difficulties. Onomatopoeia or sound symbolic words (SSW) are intuitively associated with texture impressions and are less likely to be affected by aphasia and description of material perception can be easily obtained. In this study, we aimed to create a test of texture recognition ability expressed by SSW to detect the presence of mild cognitive disorders. The sound symbolic words texture recognition test (SSWTRT) is constructed from 12 close-up photos of various materials and participants were to choose the best SSW out of 8 choices to describe surface texture in the images in Japanese. All 102 participants seen in Juntendo University Hospital from January to August 2023 had a diagnosis of possible iNPH (age mean 77.9, SD 6.7). The answers were scored on a comprehensive scale of 0 to 1. Neuropsychological assessments included MMSE, FAB, and the Rey Auditory Verbal Learning Test (RAVLT), Pegboard Test, and Stroop Test from the EU-iNPH Grading Scale (GS). In study 1 the correlation between SSWTRT and the neuropsychological tests were analyzed. In study 2, participants were divided into two groups: the Normal Cognition group (Group A, n = 37) with MMSE scores of 28 points or above, and the Mild Cognitive Impairment group (Group B, n = 50) with scores ranging from 22 to 27 points, and its predictability were analyzed. In study 1, the total SSWTRT score had a moderate correlation with the neuropsychological test results. In study 2, there were significant differences in the SSWTRT scores between groups A and B. ROC analysis results showed that the SSWTR test was able to predict the difference between the normal and mildly impaired cognition groups. The developed SSWTRT reflects the assessment results of neuropsychological tests in cognitive deterioration and was able to detect early cognitive deficits. This test not only relates to visual perception but is likely to have an association with verbal fluency and memory ability, which are frontal lobe functions.

B - 91 Characterizing Memory Profiles of Movement Disorders: the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) Recognition Subtests

Abstract Objective This study explores the utility of novel recognition memory composites integrating recently developed recognition subtests from the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS; Duff et al., 2021) in characterizing memory profiles across Mild Cognitive Impairment (MCI) and Normal Cognitive Study (NCS) groups in patients with movement disorders. Methods Twenty patients with movement disorders (M = 69.4 years, SD = 6.3) were administered the RBANS including additional Story and Figure Recognition subtests as part of a comprehensive neuropsychological evaluation at an academic medical center. Samples were stratified by MCI (n = 15) and NCS (n = 5) groups based on clinician diagnoses. Z-score based composites were created for individual recognition measures (total, hits, false positives, and discriminability indices, d’) and “Total Delayed Recall” memory composites across list, story, and figure subtests. Results Mann–Whitney U test analyses revealed significant differences between MCI and NCS groups on Story recognition d’ performance, U = 9.50, p = &amp;lt;0.05. Within the MCI group, a paired samples t-test revealed significantly worse performance on recognition d’ compared to “Total Delayed Recall” (M = 1.63, SD = 2.22); t(14) = 2.84, p = &amp;lt;0.05. Conclusions Greater impairment in recognition discriminability compared to delayed recall suggests the involvement of memory processes that extend beyond retrieval deficits typically observed in movement disorders characterized by subcortical/frontosubcortical profiles. Further investigations are warranted in establishing implications of recognition memory composites in differentiating among MCI subtypes and neurodegenerative disease progression within movement disorder populations, as findings may have been influenced by unequal variances between groups.

B - 83 Associations between Memory Aid Use, Memory Complaints, and Meta-Prospective Memory Accuracy

Abstract Objective This study examined differences in associations between memory aid usage, memory complaints, and meta-prospective memory (PM) accuracy between healthy and mild cognitive impairment (MCI) groups. Method Participants aged 60–90 were recruited from a rural community and neuropsychology clinic and separated into healthy (n = 50) and MCI (n = 31) groups using the MMSE and historical diagnoses. Measures included memory complaints, pre−/postdictions of PM performance, PM performance, and memory aid usage. Results There was no significant difference in memory aid usage between groups (t(79) = −0.79, p = 0.43, d = 0.18), nor was aid use correlated with PM performance (r = −0.04, p = 0.71). There was a significant difference in groups’ correlations between total aids used and overall memory complaints (Fisher’s Z = −2.13, p = 0.03*); the same pattern emerged for PM-only complaints (Fisher’s Z = −2.18, p = 0.03*). There was a significant difference in groups’ correlations between internal aid use and overall memory complaints (Fisher’s Z = −2.40, p = 0.02*). Internal aid use was significantly negatively correlated with PM-only complaints in the MCI group (r = −0.41, p = 0.02*), revealing a significant difference between groups (Fisher’s Z = −2.79, p = 0.005*). Conclusions Memory aid usage was not related to meta-PM accuracy or PM performance. Groups’ correlations significantly differed between total and internal memory aid usage and overall and PM-only complaints. Overall and internal memory aid usage was associated with fewer memory complaints for MCI groups but greater complaints in controls, suggesting that aid usage may improve or worsen perceptions of memory depending on neurocognitive status.

A - 99 Examining the Relationship between Adverse Childhood Experiences, Neuropsychological Functioning, and Neurocognitive Status among Older Adults

Abstract Objective Adverse childhood experiences (ACEs) are associated with poorer cognitive and mental health outcomes in adulthood. However, there is limited research elucidating the relationship between ACE severity and specific neuropsychological outcomes among examinees with cognitive impairment. This study assessed the relationship between ACE exposure and cognitive and psychiatric outcomes among older adults with and without cognitive impairment. Method This cross-sectional study included 75 patients (64% female; MAge = 67, SD = 8.6; MEducation = 12.8, SD = 3.2) undergoing neuropsychological evaluation at an academic medical center. Analyses of variance (ANOVAs) compared high versus low ACE groups on specific tests of verbal fluency, processing speed, working memory, executive functions, and on depression and anxiety measures. Groups were formed based on neurocognitive status (i.e., no diagnosis, mild cognitive impairment, dementia) and ANOVAs were re-run for each diagnosis. Results No significant differences were detected on neurocognitive measures among the overall group or when groups were subdivided by diagnosis. Among the overall sample, significant group differences were detected for depression and anxiety symptoms, F(1,73) = 16.696, p &amp;lt; 0.001 and F(1,73) = 12.268, p = 0.001 respectively, such that higher ACE groups endorsed significantly more psychiatric symptoms. Among the no-diagnosis group, depressive symptoms were bordering insignificance, p = 0.048, and no differences were detected for anxiety. By contrast, higher ACEs were associated with greater anxiety among the mild cognitive impairment group and greater depression among the dementia group. Conclusions Findings reinforce the impact of ACEs on psychiatric symptoms among older adults. Although there were no significant cognitive differences, further research is necessary to better understand the relationship between ACEs, neurocognitive impairment, and psychiatric functioning.

Exploration of a comprehensive index for predicting cognitive impairment in patients with cerebral small vessel disease and white matter lesions

Background &amp; Objective: The objective of this study was to explore the risk factors for cognitive impairment in patients with cerebral small vessel disease (CSVD), and to construct a predictive model for cognitive impairment in CSVD patients, providing personalized diagnostic and treatment strategies for patients. Methods: Clinical data and blood indicators of CSVD patients admitted to the Department of Neurology at the Second Affiliated Hospital of Shandong First Medical University from February 2022 to February 2023 were collected. Additionally, these patients underwent cranial MRI examinations and completed neurological and psychological assessments, including the Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE). Based on the MoCA and MMSE results, the patients were divided into the cognitive impairment group and the normal cognitive group. Clinical data, blood indicators, and white matter lesion (WML) grades were compared between the two groups. Univariate logistic regression analysis was performed to identify the risk factors for cognitive impairment in CSVD patients. Using MoCA assessment results as the gold standard and several clinical indicators as independent variables, a logistic regression model was constructed. Predicted values were calculated based on this model, and a receiver operating characteristic (ROC) curve for the comprehensive diagnosis of multiple variables was plotted to evaluate the model’s accuracy. Results: A total of 134 CSVD patients were included, and cognitive impairment occurred in 98 cases, with an incidence rate of 73.13%, while 36 patients did not have cognitive impairment. Univariate logistic regression analysis of the collected variables identified eight factors: age, education level, hypertension, diabetes, cerebral hemorrhage, low-density lipoprotein cholesterol (LDL-C), hyperhomocysteine (HHCY), and WML grading. Multivariate logistic regression analysis identified age, LDL-C, and WML grading as the final predictive factors, establishing a combined diagnostic model to predict the probability of cognitive impairment in patients. The constructed ROC curve for the comprehensive diagnosis of multiple variables yielded an area under the curve of 0.870, indicating good accuracy. To facilitate clinical diagnosis, the combined diagnostic model was simplified into an L score calculation formula, with the optimal cutoff value of 5.223. When the L score is &lt;5.223, the patient can be considered not having cognitive impairment, while an L score &gt;5.223 indicates cognitive impairment, allowing for the prediction of the risk of cognitive impairment in patients. Conclusion: Age, education level, hypertension, diabetes, cerebral hemorrhage, LDL-C, HHCY, and WML grading are related risk factors for cognitive impairment in CSVD patients. Age, LDL-C, and WML grading are independent risk factors for cognitive impairment in CSVD patients. The clinical predictive model for cognitive impairment in cerebral small vessel disease, constructed using the final predictive factors, showed good performance and clinical utility. It facilitates individualized risk assessment for cognitive impairment in CSVD patients and allows for targeted follow-up observation for high-risk individuals.

Characterizing Gut Microbiota in Older Chinese Adults with Cognitive Impairment: A Cross-Sectional Study.

Cognitive impairment is a clinical manifestation that occurs in the course of dementia like Alzheimer's disease. The association between cognitive impairment and gut microbiota is unclear. We aimed to identify gut microbiota characteristics and key gut microbiota biomarkers associated with cognitive impairment in a relatively large cohort of older adults in China. A total of 229 adults aged ≥60 years from Shenzhen, China were recruited into this cross-sectional study. Participants were divided into cognitive impairment (CI) and no cognitive impairment (NCI) groups according to the results of the Mini-Mental State Examination. Diversity analysis and network analysis were used to characterize the gut microbiota between the two groups. The linear discriminant analysis effect size method and machine learning approaches were sequentially performed to identify gut microbiota biomarkers. The relationship between biomarkers and lifestyle factors was explored using Transformation-based redundancy analysis (tb-RDA). A total of 74 CI participants and 131 NCI participants were included in the analysis. The CI group demonstrated lower α-diversity compared to the NCI group (Shannon: 2.798 versus 3.152, p < 0.001). The density of the gut microbiota interaction network was lower in the CI group (0.074) compared to the NCI group (0.081). Megamonas, Blautia, Pseudomonas, Stenotrophomonas, and Veillonella were key biomarkers for CI. The tb-RDA revealed that increased fruit intake and exercise contribute to a higher abundance of Megamonas, Blautia, and Veillonella. We identified a significantly reduced abundance of certain beneficial gut microbiota in older Chinese adults with cognitive impairment.

Physical activity modifies cognitive impairment-associated mortality risks among chronic kidney disease

BackgroundOlder chronic kidney disease (CKD) patients frequently face unrecognized cognitive impairment and excess mortality. Physical activity (PA) reduces cognitive decline but whether PA modifies cognitive impairment-associated mortality remains unknown. MethodsFrom 2005 to 2011, 30,561 older Taiwanese CKD patients were enrolled. Patients were divided into intact cognition (≥8 scores), mild (6–7 scores), and severe (≤5 scores) cognitive impairment groups by the Short Portable Mental Status Questionnaire (SPMSQ), and were also categorized into high-PA (≥60 min/week of moderate-intensity PA), low-PA (20–60 min/week) or inactive (<20 min/week) groups. Cox regression was conducted to evaluate the individual and joint associations of cognitive impairment and PA on all-cause and cardiovascular mortality. ResultsAfter a median follow-up of 4.52 years, the all-cause mortality were higher in CKD patients with severe (multivariable-adjusted hazard ratio [aHR] 2.31; 95% confidence interval [CI] 2.05–2.60) and mild (aHR 1.74; CI 1.51–1.99) cognitive impairment than cognitively intact ones. Remarkably, decreased PA amount interacted and amplified the cognitive impairment-associated mortality risks. Notably, the high-PA status linked to lower overall mortality risks both in mild (aHR 0.65; CI 0.45–0.93) and severe (aHR 0.73; CI 0.54–0.99) cognitively-impaired patients as compared to inactivity. Survival tree analysis indicated the least mortality in those with high PA and >8 SPMSQ scores. Similar associations were found in the cardiovascular mortality. LimitationsResidual confounding and single ethnicity. ConclusionsCognitive impairment defined by SPMSQ was progressively associated with higher mortality among elderly CKD. Higher PA linked to lower cognitive impairment-associated death risks, and could be promoted for longevity benefits.

Effect of infarct location and volume on cognitive dysfunction in elderly patients with acute insular cerebral infarction

BACKGROUND The aging of the population has become increasingly obvious in recent years, and the incidence of cerebral infarction has shown an increasing trend annually, with high death and disability rates. AIM To analyze the effects of infarct location and volume on cognitive dysfunction in elderly patients with acute insular cerebral infarction. METHODS Between January 2020 and December 2023, we treated 98 cases of elderly acute insula, patients with cerebral infarction in the cerebral infarction acute phase (3-4 weeks) and for the course of 6 months in Montreal Cognitive Assessment Scale (MoCA) for screening of cognition. Notably, 58 and 40 patients were placed in the cognitive impairment group and without-cognitive impairment group, respectively. In patients with cerebral infarction, magnetic resonance imaging was used to screen and clearly analyze the MoCA scores of two groups of patients with different infarctions, the relationship between the parts of the infarction volume, and analysis of acute insula cognitive disorder in elderly patients with cerebral infarction and the relationship between the two. RESULTS The number of patients with cognitive impairment in the basal ganglia and thalamus was significantly higher than that without cognitive impairment (P &lt; 0.05). The total infarct volume in the cognitive impairment group was higher than that in the non-cognitive impairment group, and the difference was statistically significant (P &lt; 0.05). The infarct volumes at different sites in the cognitive impairment group was higher than in the non-cognitive impairment group (P &lt; 0.05). In the cognitive impairment group, the infarct volumes in the basal ganglia, thalamus, and mixed lesions were negatively correlated with the total MoCA score, with correlation coefficients of -0.67, -0.73, and -0.77, respectively. CONCLUSION In elderly patients with acute insular infarction, infarction in the basal ganglia, thalamus, and mixed lesions were more likely to lead to cognitive dysfunction than in other areas, and patients with large infarct volumes were more likely to develop cognitive dysfunction. The infarct volume in the basal ganglia, thalamus, and mixed lesions was significantly negatively correlated with the MoCA score.

Brain structural–functional coupling mechanism in mild subcortical stroke and its relationship with cognition

ObjectivesStroke can lead to significant restructuring of brain structure and function. However, the precise changes in the coordination between brain structure and function in subcortical stroke patients remain unclear. We investigated alterations in brain structural–functional coupling (SC-FC coupling) and their impact on cognitive function in subcortical basal ganglia infarction patients. MethodsThe study comprised 40 patients with mild stroke with basal ganglia region infarcts and 29 healthy controls (HC) who underwent multidimensional neuroimaging examination and neuropsychological testing. The subcortical stroke patients were divided into post-stroke cognitive impairment (PSCI) and stroke with no cognitive impairment (NPSCI) groups based on cognitive performance, with 22 individuals undergoing follow-up examination after three months. We investigated differences in brain structural–functional coupling across three groups, and their associations with cognitive functions. ResultsCompared to both HC participants and NPSCI, PSCI exhibited significantly reduced structural–functional coupling strength in specific brain regions. After a three-month period, there was observed an increase in structural–functional coupling strength within the frontal lobe (precentral gyrus and paracentral lobule). The strength of SC-FC coupling within the precentral gyrus, precuneus, and paracentral lobule regions demonstrated a decline correlating with the deterioration of cognitive function (MoCA, memory and visual motor speed functions). ConclusionsAfter subcortical basal ganglia stroke, PSCI patients demonstrated decreased SC-FC coupling in the frontal lobe region, correlating with multidimensional cognitive impairment. Three months later, there was an increase in SC-FC coupling in the frontal lobe, suggesting a compensatory mechanism during the recovery phase of cognitive impairment following stroke.

Enhancing cognitive performance and mitigating dyslipidemia: the impact of moderate aerobic training on sedentary older adults

BackgroundThe present study aimed to evaluate the effects of 24 weeks of moderate aerobic exercise on lipids and lipoprotein levels; Lipo (a) markers, and their association with cognitive performance in healthy older adults.MethodsA total of 150 healthy subjects (100 males and 50 females; age range: 65–95 years) were recruited for this study. Based on the LOTCA test score, subjects were classified into two groups: the control group (n = 50) and the cognitive impairment group (n = 100). Cognitive functioning, leisure-time physical activity (LTPA), lipid profile, total cholesterol, TG, HDL-c, LDL-C, and lipo(a) were assessed at baseline and post-24-week aerobic exercise interventions using LOTCA battery, pre-validated Global Physical Activity Questionnaire (GPAQ) version II, colorimetric, and immunoassay techniques, respectively.ResultsSignificant improvements in cognitive function and modulation in lipid profile and lipoprotein (a) markers were reported in all older subjects following 24 weeks of moderate exercise. LOTCA-7-sets scores significantly correlated with physical activity status and the regulation of lipids and Lipo (a) markers. Physically active persons showed higher cognitive performance along with a reduction in the levels of T-Cholest., TG, LDL-C, Lipo (a), and an increase in the levels of HDL-C and aerobic fitness VO2max compared with sedentary participants. Cognitive performance correlated positively with increased aerobic fitness, HDL-C, and negatively with T-Cholest., TG, LDL-C, and Lipo (a). However, a significant increase in the improvement of motor praxis, vasomotor organization, thinking operations, attention, and concentration were reported among older adults.ConclusionsThe study findings revealed that supervised moderate aerobic training for 24 weeks significantly enhances cognitive functions via mitigating older adults’ lipid profiles and lipoprotein (a). Cognitive performance is positively correlated with aerobic fitness and HDL-C level and negatively with T-Cholest., TH, LDL-C, and Lipo (a).

Brain activation patterns in patients with post-stroke cognitive impairment during working memory task: a functional near-infrared spectroscopy study.

To explore the activation patterns in the frontal cortex of patients with post-stroke cognitive impairment during the execution of working memory tasks. 15 patients with post-stroke cognitive impairment, 17 patients without cognitive impairment, and 15 healthy controls of similar age and sex were included. All participants under-went immediate recall task testing and near-infrared spectroscopy imaging to measure frontal cortex activation during the task. The healthy control group performed the best in the immediate recall task, followed by the post-stroke non-cognitive impairment group. The post-stroke cognitive impairment group had the poorest performance. The near-infrared spectroscopy results revealed that during the immediate recall task, the healthy control group primarily activated the left frontal lobe region. In contrast, post-stroke patients exhibited reduced activation in the left frontal lobe and increased activation in the right frontal cortex, particularly in the right frontopolar and orbitofrontal regions, with the post-stroke cognitive impairment group displaying the most pronounced changes. Patients with post-stroke cognitive impairment exhibit reduced activation in the left prefrontal cortex during the working memory tasks. They rely on compensatory activation in the right prefrontal cortex, particularly in the frontopolar and orbitofrontal cortex, to successfully complete the task.

Fractional Anisotropy is a More Sensitive Diagnostic Biomarker Than Mean Kurtosis for Patients with Parkinson Disease with Cognitive Dysfunction: A Diffusional Kurtosis Map Tract-Based Spatial Statistics Study.

There is heterogeneity of white matter damage in Parkinson's disease patients with different cognitive states. Our aim was to find sensitive diffusional kurtosis imaging biomarkers to differentiate the white matter damage pattern of mild cognitive impairment and dementia. Nineteen patients with Parkinson disease with mild cognitive impairment and 18 patients with Parkinson disease with dementia were prospectively enrolled. All participants underwent MR examination with 3D-T1-weighted image and diffusional kurtosis imaging sequences. Demographic data were compared between the 2 groups. Voxelwise statistical analyses of diffusional kurtosis imaging parameters were performed using tract-based spatial statistics. The receiver operator characteristic curve of significantly different metrics was graphed. The correlation of significantly different metrics with global cognitive status was analyzed. Compared with the Parkinson disease with mild cognitive impairment group, the fractional anisotropy and mean kurtosis values decreased in 4 independent clusters in the forceps minor, forceps major, inferior fronto-occipital fasciculus, and the inferior and superior longitudinal fasciculus in patients with Parkinson disease with dementia; the mean diffusivity decreased in 1 cluster in the forceps minor. The fractional anisotropy value in the inferior fronto-occipital fasciculus and inferior longitudinal fasciculus would be the diffusional kurtosis imaging marker for the differential diagnosis of Parkinson disease with mild cognitive impairment and patients with Parkinson disease with dementia, with the best diagnostic efficiency of 0.853. The fractional anisotropy values in the forceps minor (β = 84.20, P < .001) and years of education (β = 0.38, P = .014) were positively correlated with the Montreal Cognitive Assessment. The diffusional kurtosis imaging-derived fractional anisotropy and mean kurtosis can detect the different white matter damage patterns of Parkinson disease with mild cognitive impairment and Parkinson disease with dementia. Fractional anisotropy is more sensitive than mean kurtosis in the differential diagnosis; fractional anisotropy derived from diffusional kurtosis imaging could become a promising imaging marker for the differential diagnosis of Parkinson disease with mild cognitive impairment and Parkinson disease with dementia.

Correlation between GLCM-based texture features of the lateral pterygoid muscle and cognitive function in patients with idiopathic normal pressure hydrocephalus: a preliminary report.

The potential relationship between mastication ability and cognitive function in idiopathic normal pressure hydrocephalus (iNPH) patients is unclear. This report investigated the association between mastication and cognitive function in iNPH patients using the gray level of the co-occurrence matrix on the lateral pterygoid muscle. We analyzed data from 96 unoperated iNPH patients who underwent magnetic resonance imaging (MRI) between December 2016 and February 2023. Radiomic features were extracted from T2 MRI scans of the lateral pterygoid muscle, and muscle texture parameters were correlated with the iNPH grading scale. Subgroup analysis compared the texture parameters of patients with normal cognitive function with those of patients with cognitive impairment. The mini-mental state examination score correlated positively with the angular second moment (P < 0.05) and negatively with entropy (P < 0.05). The dementia scale (Eide's classification) correlated negatively with gray values (P < 0.05). Gray values were higher in the cognitive impairment group (64.7 ± 16.6) when compared with the non-cognitive impairment group (57.4 ± 13.3) (P = 0.005). Entropy was higher in the cognitive impairment group (8.2 ± 0.3) than in the non-cognitive impairment group (8.0 ± 0.3) (P < 0.001). The area under the receiver operating characteristic curve was 0.681 (P = 0.003) and 0.701 (P < 0.001) for gray value and entropy, respectively. Our findings suggest an association between heterogeneity of mastication and impaired cognitive function in iNPH patients and highlight muscle texture analysis as a potential tool for predicting cognitive impairment in these patients.

Establishment and evaluation of a clinical prediction model for cognitive impairment in patients with cerebral small vessel disease

BackgroundThere are currently no effective prediction methods for evaluating the occurrence of cognitive impairment in patients with cerebral small vessel disease (CSVD).AimsTo investigate the risk factors for cognitive dysfunction in patients with CSVD and to construct a risk prediction model.MethodsA retrospective study was conducted on 227 patients with CSVD. All patients were assessed by brain magnetic resonance imaging (MRI), and the Montreal Cognitive Assessment (MoCA) was used to assess cognitive status. In addition, the patient’s medical records were also recorded. The clinical data were divided into a normal cognitive function group and a cognitive impairment group. A MoCA score < 26 (an additional 1 point for education < 12 years) is defined as cognitive dysfunction.ResultsA total of 227 patients (mean age 66.7 ± 6.99 years) with CSVD were included in this study, of whom 68.7% were male and 100 patients (44.1%) developed cognitive impairment. Age (OR = 1.070; 95% CI = 1.015 ~ 1.128, p < 0.05), hypertension (OR = 2.863; 95% CI = 1.438 ~ 5.699, p < 0.05), homocysteine(HCY) (OR = 1.065; 95% CI = 1.005 ~ 1.127, p < 0.05), lacunar infarct score(Lac_score) (OR = 2.732; 95% CI = 1.094 ~ 6.825, P < 0.05), and CSVD total burden (CSVD_score) (OR = 3.823; 95% CI = 1.496 ~ 9.768, P < 0.05) were found to be independent risk factors for cognitive decline in the present study. The above 5 variables were used to construct a nomogram, and the model was internally validated by using bootstrapping with a C-index of 0.839. The external model validation C-index was 0.867.ConclusionsThe nomogram model based on brain MR images and clinical data helps in individualizing the probability of cognitive impairment progression in patients with CSVD.

Frontal pole iron deposition is associated with cognitive decline in patients with carotid atherosclerosis stenosis: a quantitative susceptibility mapping study

Objective: To investigate the correlation between brain iron deposition and cognitive function in patients with carotid atherosclerosis stenosis (CAS) based on quantitative susceptibility mapping (QSM). Methods: This single-center prospective study was performed at the Department of Vascular Surgery, Nanjing Drum Tower Hospital from January 2022 to June 2022. Patients who met the ataxation criteria were divided into the CAS group (n=16) and the CAS with mild cognitive impairment (CAS-MCI) group (n=17) according to the Montreal Cognitive Assessment (MoCA) scores. All patients completed QSM imaging and whole-brain analyses were performed for absolute susceptibility values in cortical regions. Age, sex, education years, hypertension, and diabetes mellitus were included as covariates in all analyses. Partial correlation analyses were used to determine the correlation between bilateral CAS degrees and cortical susceptibility values. Further, mediation analyses were performed to determine whether and how cortical susceptibility values affect cognition in CAS patients. Receiver operating characteristic (ROC) curve analysis was also performed to evaluate the predictive worth of differential brain region susceptibility values for cognitive decline. Independent sample t test and Mann-Whitney U test was used to compare quantitative variables. The comparison of categorical variables was conducted using χ2 test, Fisher's exact test or Wilcoxon rank sum test. Results: A total of 33 patients were included in the study, including 16 in the CAS group and 17 in the CAS-MCI group. There were 23 males and 10 females, aged (62.8±9.0) years (range: 48 to 88 years). CAS-MCI group showed higher right CAS grades (Z=-2.037, P=0.042). Whole-brain cortical QSM analyses showed higher susceptibility values in the frontal pole ((-0.210±0.080)×10-8 vs.(-0.130±0.120)×10-8;t=-2.187, P=0.037), superior frontal gyrus ((-0.604±0.243)×10-8 vs. (-0.428±0.203)×10-8;t=-2.223,P=0.034), and temporal pole ((-0.081±0.115)×10-8 vs. (0.054±0.190)×10-8;t=-2.417, P=0.022) in CAS-MCI group compared to CAS group. The susceptibility value of the frontal pole showed a positive correlation with the right CAS grade (r=0.424, P=0.009),while a quasi-significant positive correlation with the left CAS (r=0.313, P=0.070). The susceptibility values of the frontal and temporal poles were negatively correlated with the MoCA score (frontal pole: r=-0.391, P=0.027; temporal pole: r=-0.410, P=0.020). Mediation analysis showed the effect of right CAS on cognition was fully mediated by the susceptibility value of the frontal pole. The ROC curve revealed that the area under the curve of using hypertension combined with the susceptibility value of the frontal pole to predict cognitive decline was 0.882 (95% CI:0.763 to 0.989) with 82% of sensitivity and 83% of specificity. Conclusions: Multiple cortical regions show iron deposition in CAS-MCI patients. Right CAS plays an important role in cognitive decline, frontal pole iron deposition mediates the effect of right CAS on cognitive function. Quantified frontal pole susceptibility is useful for the diagnosis of cognitive decline in patients with CAS.

Association of Cognitive Frailty With Subsequent All-Cause Mortality Among Middle-Aged and Older Adults in 17 Countries

ObjectivesCognitive frailty refers to the co-occurrence of cognitive impairment and frailty without concurrent Alzheimer's disease or dementia. Studies of cognitive frailty and mortality have been limited to single country or older people. However, frailty and cognitive decline may occur much earlier. We aimed to examine the association between different cognitive frailty status and subsequent all-cause mortality among middle-aged and older people in 17 countries. MethodsParticipants aged 50 and over were drawn from six prospective cohorts of aging. We classified participants according to their cognitive impairment and frailty status into the following groups: none, only cognitive impairment, only frailty and cognitive frailty. Competing-risks regression models were used to evaluate the association of different cognitive frailty status at baseline with subsequent all-cause mortality. ResultsThe cognitive frailty group had a higher mortality risk compared to those without cognitive impairment and frailty groups. Meta-analysis results showed participants with cognitive frailty (pooled subhazard ratio [SHR] = 2.34, 95% confidence interval [CI]: 2.01–2.72, I2 = 68.0%) had a higher mortality risk compared with those with only cognitive impairment status (pooled SHR = 1.36, 95% CI: 1.25–1.48, I2 = 3.0%) or only frailty status (pooled SHR = 1.83, 95% CI: 1.72–1.95, I2 = 31.0%). The association between cognitive frailty and mortality were stronger among those who were aged 70 years and older, males, single and nonconsumers of alcohol. ConclusionsCognitive frailty, frailty or cognitive impairment alone, is associated with an increased risk of all-cause mortality in Asian, European and American countries. Physical and cognitive function screening should be conducted as early as possible in middle-aged and older people, and targeted intervention approaches should be developed to reduce the incidence of adverse health outcomes.