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The adoption and growth of functional magnetic resonance imaging (fMRI) technology, especially through the use of Pearson's correlation (PC) for constructing brain functional networks (BFN), has significantly advanced brain disease diagnostics by uncovering the brain's operational mechanisms and offering biomarkers for early detection. However, the PC always tends to make for a dense BFN, which violates the biological prior. Therefore, in practice, researchers use hard-threshold to remove weak connection edges or introduce l 1-norm as a regularization term to obtain sparse BFNs. However, these approaches neglect the spatial neighborhood information between regions of interest (ROIs), and ROI with closer distances has higher connectivity prospects than ROI with farther distances due to the principle of simple wiring costs in resent studies. Thus, we propose a neighborhood structure-guided BFN estimation method in this article. In detail, we figure the ROIs' Euclidean distances and sort them. Then, we apply the K-nearest neighbor (KNN) to find out the top K neighbors closest to the current ROIs, where each ROI's K neighbors are independent of each other. We establish the connection relationship between the ROIs and these K neighbors and construct the global topology adjacency matrix according to the binary network. Connect ROI nodes with k nearest neighbors using edges to generate an adjacency graph, forming an adjacency matrix. Based on adjacency matrix, PC calculates the correlation coefficient between ROIs connected by edges, and generates the BFN. With the purpose of evaluating the performance of the introduced method, we utilize the estimated BFN for distinguishing individuals with mild cognitive impairment (MCI) from the healthy ones. Experimental outcomes imply this method attains better classification performance than the baselines. Additionally, we compared it with the most commonly used time series methods in deep learning. Results of the performance of K-nearest neighbor-Pearson's correlation (K-PC) has some advantage over deep learning.
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Brain , Cognitive Dysfunction , Magnetic Resonance Imaging , Humans , Cognitive Dysfunction/diagnosis , Cognitive Dysfunction/diagnostic imaging , Cognitive Dysfunction/physiopathology , Magnetic Resonance Imaging/methods , Brain/diagnostic imaging , Brain/physiopathology , Nerve Net/diagnostic imaging , Nerve Net/physiopathology , Brain Mapping/methods , AlgorithmsABSTRACT
BACKGROUND: Markerless motion capture (MMC) uses video cameras or depth sensors for full body tracking and presents a promising approach for objectively and unobtrusively monitoring functional performance within community settings, to aid clinical decision-making in neurodegenerative diseases such as dementia. OBJECTIVE: The primary objective of this systematic review was to investigate the application of MMC using full-body tracking, to quantify functional performance in people with dementia, mild cognitive impairment, and Parkinson disease. METHODS: A systematic search of the Embase, MEDLINE, CINAHL, and Scopus databases was conducted between November 2022 and February 2023, which yielded a total of 1595 results. The inclusion criteria were MMC and full-body tracking. A total of 157 studies were included for full-text screening, out of which 26 eligible studies that met the selection criteria were included in the review.â¯. RESULTS: Primarily, the selected studies focused on gait analysis (n=24), while other functional tasks, such as sit to stand (n=5) and stepping in place (n=1), were also explored. However, activities of daily living were not evaluated in any of the included studies. MMC models varied across the studies, encompassing depth cameras (n=18) versus standard video cameras (n=5) or mobile phone cameras (n=2) with postprocessing using deep learning models. However, only 6 studies conducted rigorous comparisons with established gold-standard motion capture models. CONCLUSIONS: Despite its potential as an effective tool for analyzing movement and posture in individuals with dementia, mild cognitive impairment, and Parkinson disease, further research is required to establish the clinical usefulness of MMC in quantifying mobility and functional performance in the real world.
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Cognitive Dysfunction , Motion Capture , Humans , Activities of Daily Living , Cognitive Dysfunction/physiopathology , Cognitive Dysfunction/diagnosis , Dementia/physiopathology , Dementia/diagnosis , Motion Capture/methods , Neurodegenerative Diseases/physiopathology , Parkinson Disease/physiopathology , Physical Functional PerformanceABSTRACT
BACKGROUND: Orthostatic hypotension (OH) is a common condition in Parkinson's disease (PD) with a possible link to cognitive decline. OBJECTIVE: The aim was to explore the association between OH and PD-associated mild cognitive impairment (PD-MCI) and dementia (PDD) over 9 years in a population-based incident PD cohort. METHODS: We prospectively followed up patients from PD diagnosis with serial blood pressure measurements, clinical examinations, and neuropsychological assessments. We defined OH using (1) consensus-based criteria and (2) clinically significant OH by mean arterial pressure (MAP) in standing position ≤75 mmHg. PD-MCI and PDD were diagnosed according to acknowledged criteria. We applied generalized estimating equations models to investigate associations between OH measurements and cognitive impairment over time. Weibull accelerated failure time regression models were used to study if early OH (≤3 years of PD diagnosis) accelerates the time to incident PD-MCI and PDD. RESULTS: Of 186 enrolled patients, consensus-based OH affected 68.8%, clinically significant OH 33.9%, PD-MCI 60.8%, and PDD 31.2%. Consensus-based OH was associated with PD-MCI (odds ratio [OR]: 2.04, 95% confidence interval: 1.44-2.90, P < 0.001), whereas clinically significant OH was associated with both PD-MCI (OR: 1.95, 1.11-3.43, P = 0.020) and PDD (OR: 3.66, 1.95-6.86, P < 0.001). Early clinically significant OH, but not early consensus-based OH, reduced time to incident PD-MCI by 54% (P = 0.021) and time to PDD by 44% (P = 0.003) independently of potential confounders, including supine hypertension and cardiovascular disease. CONCLUSIONS: MAP in standing position emerged as a stronger predictor of cognitive decline than OH determined using consensus-based criteria. These findings have implications for both research and clinical practice.
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Background and Purpose: The Korean-Mini Mental State Examination, 2nd edition (K-MMSE~2) was recently released. This study aimed to determine whether the K-MMSE~2: Standard Version (K-MMSE~2:SV) had the same test characteristics as the K-MMSE. Methods: A total of 1,514 healthy community-based participants aged 19 to 90 years were administered the K-MMSE~2:SV Blue Form along with the language items from the K-MMSE. The item and test characteristics and test information for the K-MMSE~2:SV and K-MMSE were compared using Item Response Theory analysis. Results: Item discriminations for the K-MMSE~2:SV and K-MMSE were above the moderate range for all items except Recall. Most of the items on the K-MMSE~2:SV and K-MMSE had item category difficulty in the very easy or easy range. The test information curve (TIC) showed that the K-MMSE~2:SV and K-MMSE provide almost the same amount of information (27.86 vs. 28.44), with both tests providing the most information at an ability level of -1.57. The generalizability (G) coefficient for the K-MMSE~2:SV and K-MMSE was 0.99. Conclusions: These results indicate that the K-MMSE~2:SV and K-MMSE are equally optimal tests for screening for mild cognitive impairment and early dementia. Given that the amount of test information provided by the two tests was almost identical, the shapes of the TICs were very similar, and the G coefficient was close to 1, we can conclude that the K-MMSE and K-MMSE~2:SV are equivalent tests.
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Introduction: In this study, we investigated the correlation between serum albumin levels and cognitive function, and examined the impact of including serum albumin values in the input layer on the prediction accuracy when forecasting cognitive function using deep learning and other machine learning models. Methods: We analyzed the electronic health record data from Osaka Medical and Pharmaceutical University Hospital between 2014 and 2021. The study included patients who underwent cognitive function tests during this period; however, patients from whom blood test data was not obtained up to 30 days before the cognitive function tests and those with values due to measurement error in blood test results were excluded. The Mini-Mental State Examination (MMSE) was used as the cognitive function test, and albumin levels were examined as the explanatory variable. Furthermore, we estimated MMSE scores from blood test data using deep learning models (DLM), linear regression models, support vector machines (SVM), decision trees, random forests, extreme gradient boosting (XGBoost), and light gradient boosting machines (LightGBM). Results: Out of 5,017 patients who underwent cognitive function tests, 3,663 patients from whom blood test data had not been obtained recently and two patients with values due to measurement error were excluded. The final study population included 1,352 patients, with 114 patients (8.4%) aged below 65 and 1,238 patients (91.6%) aged 65 and above. In patients aged 65 and above, the age and male sex showed significant associations with MMSE scores of less than 24, while albumin and potassium levels showed negative associations with MMSE scores of less than 24. Comparing MMSE estimation performance, in those aged below 65, the mean squared error (MSE) of DLM was improved with the inclusion of albumin. Similarly, the MSE improved when using SVM, random forest and XGBoost. In those aged 65 and above, the MSE improved in all models. Discussion: Our study results indicated a positive correlation between serum albumin levels and cognitive function, suggesting a positive correlation between nutritional status and cognitive function in the elderly. Serum albumin levels were shown to be an important explanatory variable in the estimation of cognitive function for individuals aged 65 and above.
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Background: Earlier research focuses primarily on the cognitive changes due to Alzheimer's disease (AD); however, little is known with regard to changes in language competence across the lifespan. Objective: The present study aims to investigate the decline of language skills at the grammatical and syntactic levels due to changes in cognitive function. Methods: We administered the Litmus Sentence Repetition Task (SRT) to 150 native speakers of Greek who fall into five groups: 1) young healthy speakers, 2) cognitively intact elder healthy speakers, 3) speakers with subjective cognitive impairment (SCI), 4) speakers with mild cognitive impairment (MCI); and 5) speakers with AD dementia at the mild/moderate stages. All participants underwent a physical and neurological examination and cognitive screening with a standardized neuropsychological battery to assess cognitive status comprehensively and evaluate aspects like working memory, executive function, attention and memory to appropriately classify them. Results: The data analysis revealed that the SRT had high discriminatory value in the development of AD; specifically, both accuracy and grammaticality indices were related to cognitive decline. Additionally, syntax significantly affected the performance of speakers with structures such as clitics being particularly challenging and in most structures the performance of speakers with MCI drops significantly compared to speakers with SCI. Conclusions: Linguistic indices revealed subtle early signs of cognitive decline that can be helpful in the early detection of AD, thus facilitating the clinical process offering support to language-based assessment tools such as sentence repetition, a non-invasive type of assessment to evaluate symptoms of AD.
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INTRODUCTION: Whether brain functional connectivity (FC) is consistently disrupted in individuals with mild cognitive impairment (MCI) with isolated language impairment (ilMCI), and its potential to differentiate between MCI subtypes remains uncertain. METHODS: Cross-sectional data from 404 participants in two cohorts (the Chinese Preclinical Alzheimer's Disease Study and the Alzheimer's Disease Neuroimaging Initiative) were analyzed, including neuropsychological tests, resting-state functional magnetic resonance imaging (fMRI), cerebral amyloid positivity, and apolipoprotein E (APOE) status. RESULTS: Temporo-frontoparietal FC, particularly between the bilateral superior temporal pole and the left inferior frontal/supramarginal gyri, was consistently decreased in ilMCI compared to amnestic MCI (aMCI) and normal controls, which was correlated with semantic impairment. Using mean temporo-frontoparietal FC as a classifier could improve accuracy in identifying ilMCI subgroups with positive cerebral amyloid deposition and APOE risk alleles. DISCUSSION: Temporal-frontoparietal hypoconnectivity was observed in individuals with ilMCI, which may reflect semantic impairment and serve as a valuable biomarker to indicate potential mechanisms of underlying neuropathology. HIGHLIGHTS: Temporo-frontoparietal hypoconnectivity was observed in impaired language mild cognitive impairment (ilMCI). Temporo-frontoparietal hypoconnectivity may reflect semantic impairment. Temporo-frontoparietal functional connectivity can classify ilMCI subtypes.
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Brain hypoperfusion is associated with cognitive impairment. Higher cerebrovascular impedance modulus (Z) may contribute to brain hypoperfusion. We tested hypotheses that patients with amnestic mild cognitive impairment (aMCI) (i.e., those who have high risk of developing Alzheimer's disease) have higher Z than age-matched cognitively normal individuals, and that high Z is correlated with brain hypoperfusion. Fifty-eight patients with aMCI (67±7 years) and 25 cognitively normal subjects (CN, 65±6 years) underwent simultaneous measurements of carotid artery pressure (CAP, via applanation tonometry) and middle cerebral arterial blood velocity (CBV, via transcranial Doppler). Z was quantified using cross-spectral and transfer function analyses between dynamic changes in CBV and CAP. Patients with aMCI exhibited higher Z than NC (1.18±0.34 vs. 1.01±0.35 mmHg/cm/s, P=0.044) in the frequency range from 0.78 to 4.29 Hz. The averaged Z in the frequency range (0.78-3.13 Hz) of high coherence (>0.9) was inversely correlated with total cerebral blood flow measured with 2D Doppler ultrasonography normalized by the brain tissue mass (via structural MRI) across both patients with aMCI and NC (r=-0.311, P=0.007), and in patients with aMCI alone (r=-0.306, P=0.007). Our findings suggest that patients with aMCI have higher cerebrovascular impedance than cognitively normal older adults and that increased cerebrovascular impedance is associated with brain hypoperfusion.
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BACKGROUND: Multicomponent exercise has the potential to improve cognitive function in people with mild cognitive impairment. However, the effects of multicomponent exercise on specific cognitive subdomains in mild cognitive impairment and the optimal combination of exercise components remain unclear. OBJECTIVE: This systematic review aimed to (a) investigate the effects of multicomponent exercise on different cognitive subdomains in people with mild cognitive impairment and (b) investigate the effects of different combinations of multicomponent exercise on global cognition in people with mild cognitive impairment. DESIGN: A systematic review and meta-analysis. METHODS: Six electronic databases, including PubMed, Medline, EMBASE, Web of Science, Cochrane Library, and CINAHL were systematically searched from inception to January 1st, 2023. Randomized controlled trials assessing the effect of multicomponent exercise interventions on cognitive function in people with mild cognitive impairment were included. The risk of bias was assessed using the Cochrane collaborative bias assessment tool. A random-effects model was used to calculate standardized mean difference. Subgroup analyses, meta-regression, and sensitive analysis were performed. If a meta-analysis was not feasible, studies were synthesized narratively. RESULTS: Twenty studies were identified for systematic review and meta-analysis. Multicomponent exercise significantly improved global cognition [SMDâ¯=â¯1.04; 95â¯% confidence interval (CI): 0.53, 1.55], cognitive flexibility (SMDâ¯=â¯-1.04; 95â¯% CI: -1.81, -0.27), processing speed (SMDâ¯=â¯0.43; 95â¯% CI: 0.04, 0.82), verbal fluency (SMDâ¯=â¯0.38; 95â¯% CI: 0.13, 0.63), attention (SMDâ¯=â¯-0.90; 95â¯% CI: -1.68, -0.12) and memory (SMDâ¯=â¯0.36; 95â¯% CI: 0.04, 0.69) in mild cognitive impairment. The multicomponent exercise including cardiovascular (exercise that promotes cardiovascular health, such as endurance training or aerobic exercise) and motor (exercises that improve physical abilities, such as balance, coordination, agility, flexibility, etc.) components positively affected global cognition in people with mild cognitive impairment (SMDâ¯=â¯1.06; 95â¯% CI: 0.55, 1.57). CONCLUSIONS: The findings of this study suggest that multicomponent exercise has a positive impact on various cognitive domains, including global cognition, cognitive flexibility, processing speed, verbal fluency, attention and memory in mild cognitive impairment. Specifically, the combination of exercises including cardiovascular and motor components was found to be effective in improving global cognition. However, further research is needed to investigate the optimal frequency and intensity of the multicomponent exercise intervention, and more detail about exercise combinations of the motor component (not classified in this study) for individuals with mild cognitive impairment. REGISTRATION: The protocol was registered on PROSPERO (CRD42023400302).
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INTRODUCTION: Mild cognitive impairment is a common feature of Parkinson's disease (PD-MCI), even at the earliest disease stages. Growing evidence supports the instability of PD-MCI over time, without a consistent linear evolution to dementia, and in some patients, the potential of reversion to normal cognition. However, which features are associated with reversion from PD-MCI to normal cognition in early PD-MCI are not fully known. METHODS: In our longitudinal study of early drug naïve PD patients, 65 of 134 (48 %) patients had PD-MCI at baseline. Study participants underwent comprehensive assessments at baseline and 1-year follow-up. Sixteen (24.6 %) patients with PD-MCI reverted to normal cognition (Reverters), and 49 (75.4 %) had persistent PD-MCI (Non-Reverters) after 1-year follow-up. We performed single- and multiple-variable logistic regression analyses to identify baseline variables predicting reversion of PD-MCI to normal cognition after 1-year. We also compared brain morphometric measures (cortical thickness and volumes) at baseline between the PD-MCI Reverters and Non-Reverters. RESULTS: Higher educational level and better performance on measures of attention and memory at baseline predicted the reversion to normal cognition at 1-year follow-up. Reverters had greater cortical thickness in the left inferior temporal gyrus than Non-Reverters. CONCLUSIONS: Our results show PD-MCI with a higher chance of reverting to normal cognition over time have a higher educational level, better frontotemporal-related cognitive function, and increased thickness of the inferior temporal lobe gyrus. These findings may potentially help researchers to select the candidates for clinical trials focusing on the treatment of cognitive impairment in the early stages of PD.
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Objectives: This study aimed to examine the association between the food-based index of dietary inflammatory potential (FBDI) and the risk of mild cognitive impairment (MCI) in Korean older adults. Methods: The subjects were 798 Korean adults aged 60 years and older. The FBDI was calculated based on the intake of 7 anti-inflammatory and 3 inflammatory food groups. Cognitive function was assessed using the Korean version of the Mini-Mental State Examination (MMSE-KC). A general linear model and multiple logistic regression were applied to assess the association between FBDI and the risk of MCI. Results: As the FBDI increased, the intake of white rice, cookies/candies, and sweetened drinks tended to increase, but the intake of niacin, ß-carotene, calcium, and potassium tended to decrease (p for trend < 0.05). The highest FBDI group had a higher MCI risk (odds ratio [OR], 1.60; 95% CI, 1.01 - 2.52) than the lowest FBDI group, adjusted for sex, age, and education level; and this trend was significant in a fully adjusted model (p for trend = 0.039). No significant associations were found in men after adjusting for confounding factors. Among women, MCI risk increased as the FBDI increased (p for trend = 0.007); and the highest FBDI group had a higher MCI risk (OR, 2.22; 95% CI, 1.04 - 4.74) than the lowest FBDI group in a fully adjusted model. Conclusion: These results suggest that the appropriate intake of anti-inflammatory foods and nutrients may be associated with a reduced risk of MCI among older adults.
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INTRODUCTION: Sodium phenylbutyrate and taurursodiol (PB and TURSO) is hypothesized to mitigate endoplasmic reticulum stress and mitochondrial dysfunction, two of many mechanisms implicated in Alzheimer's disease (AD) pathophysiology. METHODS: The first-in-indication phase 2a PEGASUS trial was designed to gain insight into PB and TURSO effects on mechanistic targets of engagement and disease biology in AD. The primary clinical efficacy outcome was a global statistical test combining three endpoints relevant to disease trajectory (cognition [Mild/Moderate Alzheimer's Disease Composite Score], function [Functional Activities Questionnaire], and total hippocampal volume on magnetic resonance imaging). Secondary clinical outcomes included various cognitive, functional, and neuropsychiatric assessments. Cerebrospinal fluid (CSF) biomarkers spanning multiple pathophysiological pathways in AD were evaluated in participants with both baseline and Week 24 samples (exploratory outcome). RESULTS: PEGASUS enrolled 95 participants (intent-to-treat [ITT] cohort); cognitive assessments indicated significantly greater baseline cognitive impairment in the PB and TURSO (n = 51) versus placebo (n = 44) group. Clinical efficacy outcomes did not significantly differ between treatment groups in the ITT cohort. CSF interleukin-15 increased from baseline to Week 24 within the placebo group (n = 34). In the PB and TURSO group (n = 33), reductions were observed in core AD biomarkers phosphorylated tau-181 (p-tau181) and total tau; synaptic and neuronal degeneration biomarkers neurogranin and fatty acid binding protein-3 (FABP3); and gliosis biomarker chitinase 3-like protein 1 (YKL-40), while the oxidative stress marker 8-hydroxy-2-deoxyguanosine (8-OHdG) increased. Between-group differences were observed for the Aß42/40 ratio, p-tau181, total tau, neurogranin, FABP3, YKL-40, interleukin-15, and 8-OHdG. Additional neurodegeneration, inflammation, and metabolic biomarkers showed no differences between groups. DISCUSSION: While between-group differences in clinical outcomes were not observed, most likely due to the small sample size and relatively short treatment duration, exploratory biomarker analyses suggested that PB and TURSO engages multiple pathophysiologic pathways in AD. Highlights: Proteostasis and mitochondrial stress play key roles in Alzheimer's disease (AD).Sodium phenylbutyrate and taurursodiol (PB and TURSO) targets these mechanisms.The PEGASUS trial was designed to assess PB and TURSO effects on biologic AD targets.PB and TURSO reduced exploratory biomarkers of AD and neurodegeneration.Supports further clinical development of PB and TURSO in neurodegenerative diseases.
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Objective: The objective of the current pilot study was to investigate the feasibility and acceptability of a videoconference-based cognitive behavioral (CBT) intervention for caregivers of individuals living with mild cognitive impairment or early Alzheimer's disease. The intervention included psychoeducation on emotions, strategies for management of unhelpful emotions and thoughts, behavioral activation, breathing and relaxation, strategies for communication and information on external resources. Methods: This study used a cross-sectional design with two groups of four caregivers who received an 8-week CBT-based intervention via videoconference. Measures of feasibility and acceptability were collected post-intervention as well as suggestions for improvements. Results: Eight female caregivers were enrolled in the intervention, one participant opted out at the seventh session. Of those who completed the program, all participants reported that it was very easy to participate using the online modality. All participants felt that the intervention was at least partly adapted to their experience and needs as a caregiver. Five out of seven participants (71%) indicated that they felt better and would recommend the intervention to another caregiver. Conclusion: The current study demonstrated that it is feasible and acceptable to use a videoconference CBT-based group intervention with MCI or mild AD female caregivers. Innovation: This is the first videoconference-based cognitive behavioral intervention for caregivers of individuals living with MCI or mild AD.
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OBJECTIVE: To assess the role of Machine Learning (ML) in identification critical factors of dementia and mild cognitive impairment. METHODS: 371 elderly individuals were ultimately included in the ML analysis. Demographic information (including gender, age, parity, visual acuity, auditory function, mobility, and medication history) and 35 features from 10 assessment scales were used for modeling. Five machine learning classifiers were used for evaluation, employing a procedure involving feature extraction, selection, model training, and performance assessment to identify key indicative factors. RESULTS: The Random Forest model, after data preprocessing, Information Gain, and Meta-analysis, utilized three training features and four meta-features, achieving an area under the curve of 0.961 and a accuracy of 0.894, showcasing exceptional accuracy for the identification of dementia and mild cognitive impairment. CONCLUSIONS: ML serves as a identification tool for dementia and mild cognitive impairment. Using Information Gain and Meta-feature analysis, Clinical Dementia Rating (CDR) and Neuropsychiatric Inventory (NPI) scale information emerged as crucial for training the Random Forest model.
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Cognitive Dysfunction , Dementia , Machine Learning , Humans , Cognitive Dysfunction/diagnosis , Female , Aged , Male , Dementia/diagnosis , China , Aged, 80 and over , Neuropsychological Tests/standards , Neuropsychological Tests/statistics & numerical data , East Asian PeopleABSTRACT
INTRODUCTION: Mild cognitive impairment (MCI) is a significant public health concern and a potential precursor to Alzheimer's disease (AD). This study leverages electronic health record (EHR) data to explore rural-urban differences in MCI incidence, risk factors, and healthcare navigation in West Michigan. METHODS: Analysis was conducted on 1,528,464 patients from Corewell Health West, using face-to-face encounters between 1/1/2015 and 7/31/2022. MCI cases were identified using International Classification of Diseases (ICD) codes, focusing on patients aged 45+ without prior MCI, dementia, or AD diagnoses. Incidence rates, cumulative incidences, primary care physicians (PCPs), and neuropsychology referral outcomes were examined across rural and urban areas. Risk factors were evaluated through univariate and multivariate Cox regression analyses. The geographic distribution of patient counts, hospital locations, and neurology department referrals were examined. RESULTS: Among 423,592 patients, a higher MCI incidence rate was observed in urban settings compared to rural settings (3.83 vs. 3.22 per 1,000 person-years). However, sensitivity analysis revealed higher incidence rates in rural areas when including patients who progressed directly to dementia. Urban patients demonstrated higher rates of referrals to and completion of neurological services. While the risk factors for MCI were largely similar across urban and rural populations, urban-specific factors for incident MCI are hearing loss, inflammatory bowel disease, obstructive sleep apnea, insomnia, being African American, and being underweight. Common risk factors include diabetes, intracranial injury, cerebrovascular disease, coronary artery disease, stroke, Parkinson's disease, epilepsy, chronic obstructive pulmonary disease, depression, and increased age. Lower risk was associated with being female, having a higher body mass index, and having a higher diastolic blood pressure. DISCUSSION: This study highlights rural-urban differences in MCI incidence and access to care, suggesting potential underdiagnosis in rural areas likely due to reduced access to specialists. Future research should explore socioeconomic, environmental, and lifestyle determinants of MCI to refine prevention and management strategies across geographic settings. Highlights: Leveraged EHRs to explore rural-urban differences in MCI in West Michigan.Revealed a significant underdiagnosis of MCI, especially in rural areas.Observed lower rates of neurological referrals and completions for rural patients.Identified risk factors specific to rural and urban populations.
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AIM: To investigate motor, non-motor and cognitive progression in early Parkinson's disease (PD) patients with Mild Cognitive Impairment (MCI). METHODS: PD patients were recruited within 1 year of diagnosis and were classified into PD-MCI group and PD with normal cognition (PD-NC) group. H&Y staging scale, MDS-UPDRS part III were used to assess disease severity and motor progression. Non-motor symptom scale (NMSS) was used to evaluate the NMS progression. Cognitive progression was assessed from 5 cognitive domains. Annual progression changes in the longitudinal outcomes were examined via linear mixed model with random intercept effect. False discovery rate (FDR) method was performed to control for multiple testing comparison and q-value was calculated. We set the threshold of q-values as 0.1. RESULT: A total of 205 PD patients, including 107 PD-MCI and 98 PD-NC patients were assessed prospectively over a 5-year period. PD-MCI patients, compared to PD-NC group, had a significantly higher progression rate in H&Y score (0.11 vs. 0.06, p=0.03, q=0.08), MDS-UPDRS motor score (3.11 vs. 1.90 p<0.001, q=0.06) and postural instability gait difficulty (PIGD) score (0.40 vs. 0.20, p=0.02, q=0.07). PD-MCI group also exhibited significantly faster deterioration in NMSS perceptual domain (PD-MCI vs. PD-NC: 0.38 vs. -0.04, p=0.01, q=0.06) and cognitive visuospatial domain (PD-MCI vs. PD-NC: 0.13 vs. -0.06, p=0.048, q=0.09) after adjustment for confounders and multiple comparisons. CONCLUSIONS: PD-MCI patients had faster decline in motor functions, visuo-perceptual and visuospatial performance. These findings provide a more comprehensive prognosis of PD-MCI, which could be helpful for clinician to manage PD-MCI patients.
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Despite the growing interest in precision medicine-based therapies for Alzheimer's disease (AD), little research has been conducted on how individual AD risk factors influence changes in cognitive function following transcranial direct current stimulation (tDCS). This study evaluates the cognitive effects of sequential tDCS on 63 mild cognitive impairment (MCI) patients, considering AD risk factors such as amyloid-beta deposition, APOE ε4, BDNF polymorphism, and sex. Using both frequentist and Bayesian methods, we assessed the interaction of tDCS with these risk factors on cognitive performance. Notably, we found that amyloid-beta deposition significantly interacted with tDCS in improving executive function, specifically Stroop Word-Color scores, with strong Bayesian support for this finding. Memory enhancements were differentially influenced by BDNF Met carrier status. However, sex and APOE ε4 status did not show significant effects. Our results highlight the importance of individual AD risk factors in modulating cognitive outcomes from tDCS, suggesting that precision medicine may offer more effective tDCS treatments tailored to individual risk profiles in early AD stages.
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Alzheimer Disease , Bayes Theorem , Cognition , Cognitive Dysfunction , Transcranial Direct Current Stimulation , Humans , Alzheimer Disease/therapy , Transcranial Direct Current Stimulation/methods , Male , Female , Cognitive Dysfunction/therapy , Cognitive Dysfunction/etiology , Aged , Risk Factors , Amyloid beta-Peptides/metabolism , Apolipoprotein E4/genetics , Brain-Derived Neurotrophic Factor/metabolism , Middle AgedABSTRACT
The expression of inflamma-miRs and human leukocyte antigen (HLA) haplotypes could indicate mild cognitive impairment (MCI) and Alzheimer's disease (AD). We used international databases to conduct a systematic review of studies on HLA variants and a meta-analysis of research on microRNAs (miRNAs). We aimed to analyze the discriminative value of HLA variants and miRNAs in MCI, AD and controls to evaluate the protective or causative effect of HLA in cognitive decline, establish the role of miRNAs as biomarkers for the early detection of AD, and find a possible link between miRNAs and HLA. Statistical analysis was conducted using Comprehensive Meta-analysis software, version 2.2.050 (Biostat Inc., Englewood, NJ, USA). The effect sizes were estimated by the logarithm base 2 of the fold change. The systematic review revealed that some HLA variants, such as HLA-B*4402, HLA-A*33:01, HLA-A*33:01, HLA-DPB1, HLA-DR15, HLA-DQB1*03:03, HLA-DQB1*06:01, HLA-DQB1*03:01, SNPs on HLA-DRB1/DQB1, and HLA-DQA1, predisposed to cognitive decline before the occurrence of AD, while HLA-A1*01, HLA-DRB1∗13:02, HLA-DRB1*04:04, and HLA-DRB1*04:01 demonstrated a protective role. The meta-analysis identified let-7 and miR-15/16 as biomarkers for the early detection of AD. The association between these two miRNA families and the HLA variants that predispose to AD could be used for the early screening and prevention of MCI.
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Alzheimer Disease , Cognitive Dysfunction , Genetic Predisposition to Disease , HLA Antigens , MicroRNAs , Humans , MicroRNAs/genetics , Alzheimer Disease/genetics , Cognitive Dysfunction/genetics , HLA Antigens/genetics , Biomarkers , Polymorphism, Single NucleotideABSTRACT
PURPOSE: Post-stroke (PS) cognitive impairment (CI) is frequent and its devastating functional and vital consequences are well known. Despite recent guidelines, they are still largely neglected. A large number of recent studies have re-examined the epidemiology, diagnosis, imaging determinants and management of PSCI. The aim of this update is to determine whether these new data answer the questions that are essential to reducing PSCI, the unmet needs, and steps still to be taken. METHODS: Literature review of stroke unit-era studies examining key steps in the management of PSCI: epidemiology and risk factors, diagnosis (cognitive profile and assessments), imaging determinants (quantitative measures, voxelwise localization, the disconnectome and associated Alzheimer's disease [AD]) and treatment (secondary prevention, symptomatic drugs, rehabilitation and noninvasive brain stimulation) of PSCI. FINDINGS: (1) the prevalence of PSCI of approximately 50% is probably underestimated; (2) the sensitivity of screening tests should be improved to detect mild PSCI; (3) comprehensive assessment is now well-defined and should include apathy; (4) easily available factors can identify patients at high risk of PSCI; (5) key imaging determinants are the location and volume of the lesion and the resulting disconnection, associated AD and brain atrophy; WMH, ePVS, microhemorrhages, hemosiderosis, and cortical microinfarcts may contribute to cognitive impairment but are more likely to be markers of brain vulnerability or associated AD that reduce PS recovery; (6) remote and online assessment is a promising approach for selected patients; (7) secondary stroke prevention has not been proven to prevent PSCI; (8) symptomatic drugs are ineffective in treating PSCI and apathy; (9) in addition to cognitive rehabilitation, the benefits of training platforms and computerized training are yet to be documented; (10) the results and the magnitude of improvement of noninvasive brain stimulation, while very promising, need to be substantiated by large, high-quality, sham-controlled RCTs. DISCUSSION AND CONCLUSION: These major advances pave the way for the reduction of PSCI. They include (1) the development of more sensitive screening tests applicable to all patients and (2) online remote assessment; crossvalidation of (3) clinical and (4) imaging factors to (5) identify patients at risk, as well as (6) factors that prompt a search for associated AD; (7) the inclusion of cognitive outcome as a secondary endpoint in acute and secondary stroke prevention trials; and (8) the validation of the benefit of noninvasive brain stimulation through high-quality, randomized, sham-controlled trials. Many of these objectives can be rapidly and easily attained.
ABSTRACT
BACKGROUND: This study aims to evaluate the add-on effects of oral Chinese herbal medicine (CHM) for mild cognitive impairment (MCI), when used in addition to donepezil compared to donepezil alone. METHODS: Randomized controlled trials comparing these treatments across all types of MCI were identified from nine databases and three registers until August 2023. Outcome measures were Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and adverse events (AEs). Methodological quality was assessed using Cochrane risk-of-bias tool, and evidence certainty was evaluated using the GRADE method. RESULTS: Involving 1611 participants across 20 studies, meta-analysis results indicate that oral CHM combined with donepezil significantly improved cognitive function in MCI patients compared to donepezil alone, as evidenced by MMSE (1.88 [1.52, 2.24], I2 = 41%, 12 studies, 993 participants) and MoCA (MD: 2.01 [1.57, 2.44], I2 = 52%, 11 studies, 854 participants). Eleven studies reported details of AEs, identifying gastrointestinal symptoms and insomnia as the most common symptoms. No significant difference in AEs frequency was found between the groups (RR: 0.91 [0.59, 1.39], I2 = 4%, 11 studies, 808 participants). All 20 studies were evaluated as having "some concerns" regarding the overall risk of bias. The certainty of evidence for MMSE was "moderate" and "low" for MoCA. From frequently utilized herbs, two classical CHM formulae were identified: Kai xin san and Si wu decoction. The observed treatment effects of commonly used herbs may be exerted through multiple pharmacological mechanisms, including anti-inflammatory, anti-oxidative stress, anti-apoptotic actions, promotion of neuronal survival and modulation of the cholinergic system. CONCLUSIONS: The concurrent use of oral CHM and donepezil appears to be more effective than donepezil alone in improving the cognitive function of MCI, without leading to an increase in AEs. While recognizing concerns of overall methodological quality, this combined therapy should be considered as an alternative option for clinical practice.