Education attainment and nutritional status in the prevention of cognitive impairment in the hospitalized Chinese elderly.

BACKGROUND: Effect of education attainment and nutritional status on the development of cognitive impairment in Chinese elderly has not been reported. OBJECTIVE: To investigate the role of education and nutrition in preventing cognitive impairment in the hospitalized Chinese elderly. METHODS: Cognitive function was examined using the scoring system of Mini-Mental State Examination (MMSE) domains performed under instruction of Physicians of Geriatrics. Generalized linear mixed-effect regression was used for analyzing the association of demographic factors (age and gender), socioeconomic factors (education attainment and monthly income), as well as health-related factors (nutritional status, comorbidity, anxiety, and depression) and MMSE scores. RESULTS: Total 246 hospitalized Chinese elders were enrolled into this study. Of them, 96 participants were 60-70 years old, 65 participants were 71-80 years old, and 85 of them were 81 years or older. Of the examined factors, we found that age, education attainment, and nutritional status were significantly associated with the outcome of MMSE scores, while monthly income and health condition (comorbidity, anxiety, and depression) were not significantly associated with MMSE score. Furthermore, education attainment was significantly associated with majority of the MMSE domains, including orientation, registration, attention and calculation, recall, and most of language sub-domains. CONCLUSION: Education attainment and nutritional status were significantly associated with MMSE scores in the hospitalized Chinese elderly. Higher education and better nutritional status are protective factors for the development of cognitive impairment in the hospitalized elderly Chinese population.

The association between oral health and mild cognitive impairment in community-dwelling older adults.

Background: Older adults with cognitive impairment can experience poor oral health due to reduced self-care ability, yet the impact of various oral health indicators on the cognitive ability remains unclear. We investigated the relationship between oral health indicators and mild cognitive impairment (MCI) in older adults. Methods: A cross-sectional study of 234 older adults aged 65 years or over was performed form January to March 2023 at health screening departments of hospitals. This study used the Mini-mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Activities of Daily Living (ADL), Clinical Dementia Rating (CDR), and Hachinski Ischemic Score (HIS) to measure MCI. Two qualified dentists performed clinical oral examinations (number of teeth lost, dental caries, removable dentures, periodontitis). The other oral health status was measured by subjective assessment questionnaires, and the oral health-related quality of life (OHRQoL) was assessed by Geriatric Oral Health Assessment Index (GOHAI). Results: Of the 234 older adults, 166 had MCI and 68 had normal cognitive ability. The univariate analyses revealed that older adults with poor oral health indicators of dental caries, mastication ability, oral and maxillofacial pain, self-perceived oral health status and OHRQoL had lower cognitive levels. The stepwise logistic regression analysis observed that higher education level (OR = 0.06, 95%CI = 0.007, 0.567) and OHRQoL score (OR = 0.92, 95%CI = 0.878, 0.963) were negatively associated with the presence of MCI. The area under the ROC curve (AUC) of MCI was 0.675 (95% CI: 0.600, 0.749) with a low sensitivity of 41.6% and a moderate specificity of 86.8%. Conclusion: OHRQoL was found to be associated with MCI, implying that OHRQoL may be important in cognitive decline. The GOHAI scale can be used to more easily assess the oral health of older adults, which is important for the timely detection of poor oral status to delay cognitive decline.

Reliable change indices for the Italian version of the Montreal Cognitive Assessment (MoCA) in non-demented Parkinson's disease patients.

BACKGROUND: . The present study aimed at deriving regression-based reliable change indices (RCIs) for the Montreal Cognitive Assessment (MoCA) in an Italian cohort of non-demented Parkinson's disease (PD) patients. METHODS: N = 33 consecutive, non-demented PD patients were followed-up at a 5-to-8-month interval (M = 6.6; SD = 0.6) with the MoCA. Practice effects and test-retest reliability were assessed via dependent-sample t-tests and intra-class correlation (ICC) coefficients, respectively. RCIs were derived separately for raw and demographically adjusted MoCA scores according to a standardized regression-based approach by accounting for both baseline confounders (i.e., demographics, disease duration and Unified Parkinson's Disease Rating Scale scores) and retest interval. RESULTS: No practice effects were found (t(32) = 0.29; p = .778), with acceptable test-retest reliability being detected (ICC = 0.67). MoCA scores at T0 proved to be the only significant predictor of T1 MoCA performances within both the model addressing raw scores and that addressing adjusted scores (ps < 0.001). CONCLUSIONS: The present study provides Italian practitioners and researchers with regression-based RCIs for the MoCA in non-demented PD patients, which can be reliably adopted for retest interval ≥ 5 and ≤ 8 months without encountering any practice effect.

Later-Life Cognitive Trajectories and Risk of Death: Results from a 6-Year Longitudinal Study of 7082 Chinese.

BACKGROUND AND OBJECTIVES: To identify cognitive decline trajectories in a Chinese elderly population, explore the associations between these trajectories and mortality, and further identify risk factors related to certain trajectories of cognitive decline. DESIGN: Prospective cohort study. SETTING: The group-based trajectory modeling and Cox proportional hazards models were conducted to explore the association between cognitive trajectory groups and mortality, while multinomial logistic regression models were constructed to estimate potential risk factors. PARTICIPANTS: We included 7082 participants aged 65 years or above in three consecutive but non-overlapping cohorts of the Chinese Longitudinal Healthy Longevity Survey with the Chinese version of the Mini-Mental State Examination up to 6 years. Participants were subsequently followed for a median (IQR) of 2.89 (1.38-3.12) years to obtain their survival status and date of death. MEASUREMENTS: Chinese version of the Mini-Mental State Examination was used to measure participants' cognitive function. RESULTS: Through use of group-based trajectory modeling, we determined three cognitive trajectory groups. Then, after adjusting for confounding factors, we found a monotonic and positive association between cognitive decline and mortality risk. Meanwhile, the association varied among elderly populations in different age groups and BMI categories, but did not differ by sex, smoking, drinking and exercising. Older seniors, females and those with poorer baseline cognitive function and less social participation tended to be more likely to be in the unfavorable trajectory groups. CONCLUSION: We found that the faster the cognitive decline, the higher the mortality, especially among those aged 65-79 years and those overweight. Our findings suggested the importance of implement better monitoring of the cognitive function of the elderly population.

The Effect of Segmentation Method on Medial Temporal Lobe Subregion Volumes in Aging.

Early stages of Alzheimer's disease (AD) are associated with volume reductions in specific subregions of the medial temporal lobe (MTL). Using a manual segmentation method-the Olsen-Amaral-Palombo (OAP) protocol-previous work in healthy older adults showed that reductions in grey matter volumes in MTL subregions were associated with lower scores on the Montreal Cognitive Assessment (MoCA), suggesting atrophy may occur prior to diagnosis of mild cognitive impairment, a condition that often progresses to AD. However, current "gold standard" manual segmentation methods are labour intensive and time consuming. Here, we examined the utility of Automatic Segmentation of Hippocampal Subfields (ASHS) to detect volumetric differences in MTL subregions of healthy older adults who varied in cognitive status as determined by the MoCA. We trained ASHS on the OAP protocol to create the ASHS-OAP atlas and then examined how well automated segmentation replicated manual segmentation. Volumetric measures obtained from the ASHS-OAP atlas were also contrasted against those from the ASHS-PMC atlas, a widely used atlas provided by the ASHS team. The pattern of volumetric results was similar between the ASHS-OAP atlas and manual segmentation for anterolateral entorhinal cortex and perirhinal cortex, suggesting that ASHS-OAP is a viable alternative to current manual segmentation methods for detecting group differences based on cognitive status. Although ASHS-OAP and ASHS-PMC produced varying volumes for most regions of interest, they both identified early signs of neurodegeneration in CA2/CA3/DG and identified marginal differences in entorhinal cortex. Our findings highlight the utility of automated segmentation methods but still underscore the need for a unified and harmonized MTL segmentation atlas.

Validation and comparison of virtual reality and 3D mobile games for cognitive assessment against ACE-III in 82 young participants.

Current medical and clinical ecosystem for dementia detection is inadequate for its early detection. Traditional cognitive assessments are introduced after cognitive impairment has begun to disrupt the real-world functioning of the person. Moreover, these tools are paper-pen based and fail to replicate the real-world situations wherein the person ultimately lives, acts and grows. The lack of tools for early detection of dementia, combined with absence of reliable pharmacological cure compound the problems associated with dementia diagnosis and care. Advancement of technology has facilitated early prediction of disease like cancer, diabetes, heart disease, but hardly any such translation has been observed for dementia or cognitive impairment. Given this background, we examine the potential of Virtual Reality (VR) and 3D Mobile-based goal-oriented games for cognitive assessment. We evaluate three games (2 in VR, one in mobile) among 82 young participants (aged 18-28 years) and compare and contrast the game-based results with their Addenbrooke Cognitive Examination (ACE-III) scores. Three main analysis methods are used: Correlative, Z-score and Regression analysis. Positive correlation was observed for ACE-III and game-based scores. Z-scores analysis revealed no difference between the two scores, and stronger statistical significance was found between game scores and cognitive health factors like age, smoking compared to ACE-III. Specific game performances also revealed about real-world traits of participants, like hand-use confusion and direction confusion. Results establish the plausibility of using goal-oriented games for more granular, time-based, and functional cognitive assessment.

The role of vagal nerve stimulation on psychosocial associated disorders in refractory epilepsy patients.

OBJECTIVE: To determine the effects of vagal nerve stimulation on cognition and epilepsy-associated psychosocial problems in patients with intractable epilepsy, and to assess their relation to seizure decline. METHODS: The longitudinal study was conducted at Saad Al-Witry Neurosciences Hospital, Baghdad, Iraq, from December 2015 to December 2020, and comprised refractory epilepsy cases with implanted vagal nerve stimulation devices. They were subjected to pre- and post-implantation epilepsy protocol assessment with added neuropsychological evaluation using the Mini-Mental State Examination system. Each case was followed up for 2 years post-implantation. Descriptive data regarding patient records of age, seizure nature, mental functioning level, and vagal nerve stimulation insertion was noted. Data was analysed using SPSS 21. RESULTS: Of the 150 patients, 75(50%) each were males and females, with 70(46.7%) aged <10 years at the time of surgery. Overall, 80(53.3%) patients had partial seizures with secondary generalisation, 70(46.7%) had refractory seizure attacks for <5 years, 78(52%) had attack frequency of 2-5 per day. All 150(100%) patients had had vagal nerve stimulation for >2 years. Post-intervention, 80(53.3%) patients had <2 attacks per day. Mini-Mental State Examination score was >25 in 35(23.3%) patients which post-intervention rose to 64(42.7%). CONCLUSIONS: There was evidence of improvement with respect to patient characteristics predictive of vagal nerve stimulation-related cognition and neuropsychological responsiveness in refractory epilepsy.

Improving analysis of cognitive outcomes in cardiovascular trials using different statistical approaches.

BACKGROUND: The Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) questionnaires are commonly used to measure global cognition in clinical trials. Because these scales are discrete and bounded with ceiling and floor effects and highly skewed, their analysis as continuous outcomes presents challenges. Normality assumptions of linear regression models are usually violated, which may result in failure to detect associations with variables of interest. METHODS: Alternative approaches to analyzing the results of these cognitive batteries include transformations (standardization, square root, or log transformation) of the scores in the multivariate linear regression (MLR) model, the use of nonlinear beta-binomial regression (which is not dependent on the assumption of normality), or Tobit regression, which adds a latent variable to account for bounded data. We aim to empirically compare the model performance of all proposed approaches using four large randomized controlled trials (ORIGIN, TRANSCEND, COMPASS, and NAVIGATE-ESUS), and using as metrics the Akaike information criterion (AIC). We also compared the treatment effects for the methods that have the same unit of measure (i.e., untransformed MLR, beta-binomial, and Tobit). RESULTS: The beta-binomial consistently demonstrated superior model performance, with the lowest AIC values among nearly all the approaches considered, followed by the MLR with square root and log transformations across all four studies. Notably, in ORIGIN, a substantial AIC reduction was observed when comparing the untransformed MLR to the beta-binomial, whereas other studies had relatively small AIC reductions. The beta-binomial model also resulted in a significant treatment effect in ORIGIN, while the untransformed MLR and Tobit regression showed no significance. The other three studies had similar and insignificant treatment effects among the three approaches. CONCLUSION: When analyzing discrete and bounded outcomes, such as cognitive scores, as continuous variables, a beta-binomial regression model improves model performance, avoids spurious significance, and allows for a direct interpretation of the actual cognitive measure. TRIALS REGISTRATION: ORIGIN (NCT00069784). Registered on October 1, 2003; TRANSCEND (NCT00153101). Registered on September 9, 2005; COMPASS (NCT01776424). Registered on January 24, 2013; NAVIGATE-ESUS (NCT02313909). Registered on December 8, 2014.

Effects of traditional Chinese medicine on outcomes and costs of dementia care: results from a retrospective real-world study.

OBJECTIVES: This study aims to assess the impact of Traditional Chinese Medicine (TCM) on dementia patients, utilizing real-world data. Specifically, it seeks to evaluate how TCM influences clinical outcomes by examining changes in the Clinical Dementia Rating (CDR) and Mini-Mental State Examination (MMSE) scores, as well as its effect on medical expenses over a two-year period. Data from a multi-center research database spanning from 2004 to 2021 will be used to achieve these objectives, addressing the current gap in empirical data concerning intuitive outcomes and cognitive function assessments. METHODS: Propensity score matching was adopted to improve comparability among the intervention and control groups. Due to repeated dependent variable measurements, the generalized estimating equation was used to control for socio-demographic characteristics, regional characteristics, and Western medicine treatments for dementia. RESULTS: After propensity score matching, a total of 441 research subjects were included: 90 in the TCM intervention group and 351 in the non-TCM intervention group. The results of multivariate regression analysis showed that compared with the non-TCM intervention group, the MMSE scores in the TCM intervention group increased by 0.608 points each year. The annual change in CDR scores in the TCM intervention group was 0.702 times that of the non-TCM utilization group. After TCM intervention, annual outpatient expenses increased by US$492.2, hospitalization expenses increased by US$324.3, and total medical expenses increased by US$815.9, compared with the non-intervention group. CONCLUSIONS: TCM interventions significantly decelerate cognitive decline in dementia patients, evidenced by slower reductions in MMSE scores and mitigated increases in CDR scores. However, these benefits are accompanied by increased medical expenses, particularly for outpatient care. Future healthcare strategies should balance the cognitive benefits of TCM with its economic impact, advocating for its inclusion in dementia care protocols.

Predicting cognitive function changes from oral health status: a longitudinal cohort study.

Recent studies indicate a potential link between oral health and cognitive function; however, long-term associations remain unclear. This study aimed to identify oral health factors that predict changes in cognitive function among older adults over time. The study included 583 independent older adults (201 male, 382 female) with a mean age of 72.7 years. Cognitive function was assessed using Mini-Mental State Examination (MMSE) at baseline and follow-up over two years, with relative change in MMSE (rMMSE) calculated. Baseline oral health variables included number of remaining teeth, masticatory performance, occlusal force, oral diadochokinesis and tongue pressure. Physical performance and confounding factors were also considered. The relationship between rMMSE and the variables was analyzed using Pearson's correlation, Mann-Whitney U test, and multiple linear regression analysis. Cognitive function declined in 196 subjects, with rMMSE significantly correlated with oral diadochokinesis. Regression analysis revealed significant associations between cognitive changes and oral diadochokinesis (p = 0.020) and knee extension strength as a physical performance (p = 0.047). Our findings suggest that cognitive decline may be indicated by declines in both physical and oral motor performance. Incorporating oral diadochokinesis testing into health screenings could aid early detection of cognitive decline, improving outcomes and reducing healthcare burdens.

Influence of intergenerational social mobility on brain structure and global cognition: findings from the Whitehall II study across 20 years.

BACKGROUND: Whether changes in socioeconomic position (SEP) across generations, i.e. intergenerational social mobility, influence brain degeneration and cognition in later life is unclear. OBJECTIVE: To examine the association of social mobility, brain grey matter structure and global cognition. METHODS: We analysed T1 brain MRI data of 771 old adults (69.8 ± 5.2 years) from the Whitehall II MRI substudy, with MRI data collected between 2012 and 2016. Social mobility was defined by SEP changes from their fathers' generation to mid-life status. Brain structural outcomes include grey matter (GM) volume and cortical thickness (CT) covering whole brain. Global cognition was measured by the Mini Mental State Examination. We firstly conducted analysis of covariance to identify regional difference of GM volume and cortical thickness across stable high/low and upward/downward mobility groups, followed with diagonal reference models studying the relationship between mobility and brain cognitive outcomes, apart from SEP origin and destination. We additionally conducted linear mixed models to check mobility interaction over time, where global cognition was derived from three phases across 2002 to 2017. RESULTS: Social mobility related to 48 out of the 136 GM volume regions and 4 out of the 68 CT regions. Declined volume was particularly seen in response to downward mobility, whereas no independent association of mobility with global cognition was observed. CONCLUSION: Despite no strong evidence supporting direct influence of mobility on global cognition in later life, imaging findings warranted a severe level of neurodegeneration due to downward mobility from their father's generation.

Association Between Enlarged Perivascular Spaces and Early Acute Ischemic Stroke with Cognitive Impairment: A Cross-Sectional Study.

BACKGROUND: Enlarged perivascular spaces (EPVSs) are commonly detected via magnetic resonance imaging. It is unclear whether EPVSs are associated with cognitive impairment within one month after an acute ischemic stroke (AIS) (i.e., early AIS with cognitive impairment (EAIS-CI)). This study explored the severity and location of EPVSs and their association with EAIS-CI severity and provides clinicians with early warning indicators before the onset of typical clinical symptoms in the Chinese population. METHODS: The clinical data of 208 patients (176 AIS patients and 32 controls) were prospectively analyzed using the Montreal Cognitive Assessment Beijing version (MoCA-BJ) score as the primary group criterion and the Mini-Mental State Examination (MMSE) score as a supplementary criterion. When EPVS I as the main EPVS type detected by imaging, the basal ganglia (BG) is the area most severely affected. Statistical analysis was conducted on the relevant clinical data. RESULTS: AIS patients were grouped based on MoCA-BJ scores. Age (p < 0.01), education level (p = 0.02), EPVS I as the main EPVS type (p < 0.01), the number of right-sided BG-EPVSs (p = 0.04), white matter hyperintensities (WMHs) (Fazekas scores: p = 0.02), brain atrophy (global cortical atrophy scores: p < 0.01, Koedam posterior atrophy visual scale scores: p = 0.01, medial temporal lobe atrophy scores: p < 0.01) and AIS lesion volume (p = 0.01) were significantly greater in the EAIS-CI group than in the EAIS without cognitive impairment group. The cognitive domains of attention (p = 0.04) and orientation (p < 0.01) were more closely associated with EPVS I as the main EPVS type. However, multivariate regression analysis did not identify EPVS I as the main EPVS type as the main risk factor for EAIS-CI (p = 0.098). Grouping by MMSE scores revealed that EPVS I as the main EPVS type was linked to low education level (p < 0.01) and was significantly associated with EAIS in individuals with cognitive dementia (p < 0.01). CONCLUSIONS: As a result of multiple factors, EAIS-CI is significantly associated with a low education level, BG-EPVS, WMHs, and worsening brain atrophy severity. Imaging markers, such as the severity of BG-EPVS, can assist in the early diagnosis and assessment of EAIS-CI. CLINICAL TRIAL REGISTRATION: The study was registered with the China Clinical Trial Registry (https://www.chictr.org.cn/), registration number: ChiCTR2000038819.

[Mild cognitive impairment: how to find your way around as general practitioners?] / Trouble neurocognitif mineur : comment s'y retrouver dans la pratique au cabinet ?

This article explores the diagnosis of Mild Cognitive Impairment (MCI) in general practice. It examines the subtypes of MCI and their specific diagnostic criteria for different neurodegenerative conditions such as Alzheimer's disease, Parkinson's disease, fronto-temporal dementia and cerebrovascular disorders. It highlights the preferential use of the Montreal Cognitive Assessment (MoCA) over the Mini-Mental State Examination (MMSE) for detecting MCI. A MoCA score below the norm (< 26 points) warrants a more thorough diagnostic work-up, including a full neuropsychological assessment and possibly brain imaging.

Cet article explore le diagnostic du trouble neurocognitif mineur (Mild Cognitive Impairment, MCI) dans le cadre d'une pratique médicale générale. Il examine les sous-types de MCI, leurs critères diagnostiques spécifiques pour différentes conditions neurodégénératives telles que la maladie d'Alzheimer, la maladie de Parkinson, les dégénérescences frontotemporales et les troubles vasculaires cérébraux. Il met en avant l'utilisation préférentielle du Montreal Cognitive Assessment (MoCA) par rapport au Mini-Mental State Examination (MMSE) pour dépister le MCI. Un score MoCA inférieur à la norme (< 26 points) motive un bilan diagnostique plus approfondi, incluant une évaluation neuropsychologique complète et éventuellement une imagerie cérébrale.

Augmenting Blood Test and Periodontal Examination Data with Generative Adversarial Networks for Enhanced Dementia Risk Prediction.

This study investigates the effectiveness of data augmentation to improve dementia risk prediction using deep neural networks (DNNs). Previous research has shown that basic blood test data were cost-effective and crucial in predicting cognitive function, as indicated by mini-mental state examination (MMSE) scores. However, creating models that can accommodate various conditions is a significant challenge due to constraints related to blood test and MMSE results, such as high costs, limited sample size, and missing data from specific tests not conducted in certain facilities. Periodontal examinations have also emerged as a cost-effective tool for mass screening. To address these issues, this study explores the use of generative adversarial networks (GANs) for generating synthesised data from blood test and periodontal examination results. We used DNNs with four hidden layers to compare prediction accuracy between real and GAN-synthesised data from 108 participants at Nihon University Itabashi Hospital. The GAN-synthesised DNNs achieved a mean absolute error (MAE) of 1.91 ± 0.30 compared to 2.04 ± 0.37 for real data, indicating improved accuracy with synthesised data. Importantly, synthesised data showcased enhanced robustness against missing important variables including age information, and better managed data imbalances. Considering the difficulties in amassing extensive medical data, the augmentation approach is promising in refining dementia risk prediction.

Importance of Serum Albumin in Deep Learning-Based Prediction of Cognitive Function Data in the Aged Using a Basic Blood Test.

BACKGROUND: Recently, a method using deep learning has been developed to estimate the risk of developing dementia. This method uses general blood test data from routine health examinations that reveal lifestyle-related diseases, which can lead to vascular cognitive impairment via arteriosclerosis, as well as systemic metabolic disorders that are unrelated to lifestyle, such as nutritional disorders. In this study, we investigated the differences in the accuracy of estimating the risk of dementia based on the presence or the absence of blood test parameters reflecting nutritional disorders while focusing on the association between malnutrition and the risk of dementia in frail, elderly individuals. OBJECTIVES: The objective of this study was to evaluate the impact of including or excluding serum albumin, which reflects nutritional status, on the accuracy of predicting cognitive function in older adults using blood test data. METHODS: We estimated cognitive function, as measured by the Mini-Mental State Examination (MMSE), using the deep learning model (DLM). The estimation was performed based on general blood test data, including complete blood tests and basic metabolic panels, obtained from a selection of 1287 patients admitted to Osaka Medical and Pharmaceutical University Hospital. The data were divided into two groups: individuals aged 65 and above and those aged below 65. The impact of including or excluding serum albumin on the predictive performance of MMSE was examined within each group. RESULTS: In those aged below 65, the mean squared error (MSE) of the DLM was 5.33 without albumin and 4.62 with albumin, showing a -0.71 improvement with albumin. In those aged 65 and above, the MSE of the DLM was 6.38 without albumin and 6.28 with albumin, showing a -0.1 improvement with albumin. DISCUSSION: The present study demonstrated that including serum albumin in the input data resulted in lower estimation errors for MMSE across all applied algorithms in the group aged 65 and above. This is consistent with previously reported studies that have shown the adverse effects of malnutrition on cognitive function in older adults. CONCLUSIONS: This study highlighted the significance of serum albumin, which reflects nutritional status, as an important assessment variable for estimating MMSE from blood test data, particularly in individuals aged 65 and above.

Relationship Between Dementia and Systemic Metabolic Disorders.

Recent research has linked systemic metabolic disorders to cognitive decline and dementia risk, including Alzheimer's. This is suspected to be due to lifestyle-related vascular impairments from atherosclerosis and other factors, such as malnutrition and anaemia. Applying deep learning using 2897 cases from a rehabilitation hospital and health screenings, we trained a model to predict cognitive function [mini-mental state examination (MMSE) scores] and brain atrophy [Brain Healthcare Quotient (BHQ) scores] from basic blood tests and age. The deep learning model accurately estimated MMSE and BHQ from these inputs, with age, nutritional information, and organ function indicators being top predictors. These findings highlight the relationship of dementia with systemic metabolic disorders and suggest the potential of using routine blood tests for dementia risk assessment. Furthermore, personalised dietary interventions could be tailored based on blood test anomalies. This holistic view mirrors traditional Chinese medicine, which considers brain disorders systemic, that is related to vital organs but not the brain itself.

Pain and cognitive function in Korean older adults aged 60 years or more: A retrospective longitudinal study.

To elucidate the relationship between pain and cognitive decline in adults aged ≥60 years using data from the Korean Longitudinal Study of Aging survey. We included 3,287 older adults aged ≥60 years with a Korean Mini-Mental State Examination score ≥24. We assessed the presence of pain and pain interference using self-administered questionnaires. Pain interference was determined based on whether the pain limited the participants' activities of daily living. According to this assessment, participants were categorized as no pain, low-impact pain, and high-impact pain. Cognitive function was assessed using the Mini-Mental State Examination and classified into 3 groups: normal, cognitive impairment, and suspected dementia. Potential confounding factors, including pain × survey year, were adjusted in the analyses. We also performed subgroup analyses of participants experiencing pain to elucidate the association between pain interference, suspected dementia, and cognitive impairment. A significant difference in the Mini-Mental State Examination scores was observed between individuals with and without pain (P < .001). Pain remained negatively associated with the Mini-Mental State Examination score through the first to the eighth wave even after adjusting for confounding factors (ß = -1.170, 95 % confidence interval (CI): -0.243, -0.097). Compared to the absence of pain, the presence of pain increased the odds of suspected dementia and cognitive impairment by approximately 1.6 and 1.4 times, respectively (odds ratio [OR] = 1.56, 95% CI: 1.26, 1.93; OR = 1.36, 95% CI: 1.20, 1.54). Compared to low-impact pain, high-impact pain increased the odds of suspected dementia and cognitive impairment by approximately 2.1and 1.5 times, respectively (OR = 2.12, 95% CI: 1.76, 2.56; OR = 1.47, 95% CI: 1.31, 1.65). Pain was negatively associated with Mini-Mental State Examination scores in Korean older adults aged ≥60 years and increased the odds of suspected dementia and cognitive impairment. Furthermore, individuals with high-impact pain exhibited higher risks of both suspected dementia and cognitive impairment than those with low-impact pain.

Small Vessel Disease Burden Predicts Incident Dementia and Poor Functional Outcome in Independent Outpatients.

Background: Total small vessel disease (SVD) score is used to measure the burden of SVD. Objective: This study aimed to clarify the predictive value of total SVD score for incident dementia and functional outcomes in independent outpatients with vascular risk factors. Methods: We derived data from a Japanese cohort in which patients underwent magnetic resonance imaging and cognitive examinations. They were followed up until March 2023. The primary outcomes was dementia. Secondary outcome was functional outcomes. We measured a modified Rankin scale (mRS) score at the last visit and defined poor functional outcomes as mRS score ≥3. Results: After excluding those with a mRS score ≥2, Mini-Mental State Examination score in Japanese version < 24, and missing T2* images, 692 patients were included. During a median follow-up period of 4.6 years, dementia occurred in 31 patients. In multivariate analysis, the score 4 group showed a significantly higher risk of incident dementia than the score 0-3 groups (adjusted hazard ratio, 6.25; 95% CI, 1.83-21.40, p = 0.003). The total SVD score was also independently related to poor functional outcome. Conclusions: The total SVD score of 4, and ≥1 could predict dementia and poor functional outcomes, respectively. Our results suggest intensive management of patients with SVD to prevent dementia and to maintain independent activities of daily living.

Association between type of menopause and mild cognitive impairment: The REDLINC XII study.

OBJECTIVE: To evaluate the association between type of menopause (spontaneous or surgical) and mild cognitive impairment (MCI). STUDY DESIGN: This study was a cross-sectional, observational, and sub-analytical investigation conducted within gynecological consultations across nine Latin American countries. METHOD: We assessed sociodemographic, clinical, and anthropometric data, family history of dementia, and the presence of MCI using the Montreal Cognitive Assessment (MoCA) tool. RESULTS: The study involved 1185 postmenopausal women with a mean age of 55.3 years and a body mass index of 26.4 kg/m2. They had an average of 13.3 years of education, and 37 % were homemakers. Three hundred ninety-nine experienced menopause before 40, including 136 with surgical menopause (bilateral oophorectomy). Out of the 786 women who experienced menopause at 40 or more years, 110 did so due to bilateral oophorectomy. There were no differences in MoCA scores among women who experienced menopause before or after the age of 40. However, lower MoCA scores were observed in women with surgical menopause than in those with spontaneous menopause (23.8 ± 4.9 vs. 25.0 ± 4.3 points, respectively, p < 0.001). Our logistic regression model with clustering of patients within countries found a significant association between MCI and surgical menopause (OR 1.47, 95 % CI: 1.01-2.16), use (ever) of menopausal hormone therapy (OR 0.33, 95 % CI: 0.21-0.50), and having >12 years of education (OR 0.21, 95 % CI: 0.14-0.30). CONCLUSION: When comparing women who experience spontaneous menopause over the age of 40 with those who undergo it before this age, there was no observed increased risk of developing MCI, while those with surgical menopause, independent of age, are more prone to cognitive decline. Women who have ever used menopausal hormone therapy have a lower MCI risk. Further research is warranted to delve deeper into this topic.

Reliability of the assessment of the clinical dementia rating scale from the analysis of medical records in comparison with the reference method.

BACKGROUND: The Clinical Dementia Rating (CDR) scale allows to detect the presence of dementia and to assess its severity, however its evaluation requires a significant time (45 min). We evaluated the agreement between two methods of collection of the CDR: face-to-face interview or based on the information available in the patient's medical record. METHODS: The CLIMER study was conducted among patients attending a memory center. The CDR scale was evaluated during face-to-face interviews between neuropsychologists and patients and their caregivers and based on blind analysis of the information of the patients' medical record by neuropsychologists. The agreement of the CDR sum of boxes (CDR-SB), the 5-point scale CDR and the different domains of the CDR evaluated between the different methods was measured using intraclass correlation (ICC) coefficient, Bland and Altman method, and linearly weighted Kappa. RESULTS: The study included 139 patients (means ± SD age 80.1 ± 6, 58.3% women, 71.9% with dementia). The ICC for the CDR-SB score assessed by face-to-face and with all the information available in the patient's medical record was 0.95 (95% CI: 0.93-0.97). The mean difference between the CDR-SB score assessed by face-to-face and with the medical record was 0.098 ± 1.036, and 92.4% of the patients lay within the 95% limits of agreement. The ICC for the 5-point scale CDR assessed by face-to-face and with the patient's medical record was 0.92 (95% CI: 0.88-0.95) when all the available information of the patient's medical record was used. The linear weighted Kappa coefficients was 0.79 (95% CI: 0.68-0.91) for the 5-point scale CDR comparison between the two evaluation methods. The analysis by domain of the CDR showed ICC ranging from 0.65 to 0.91 depending of the domains and the methods of evaluation. CONCLUSION: This study showed an excellent level of agreement of the evaluation of the CDR- SB and the 5-point scale CDR when using all the information of the patient's medical record compared to the face-to-face interview. TRIAL REGISTRATION: https//clinicaltrials.gov/ct2/show/NCT04763941 Registration Date 02/17/2021.