An algorithm for the early diagnosis and correct approach to dementia management: results of a multiprofessional team.

BACKGROUNG: The early identification of cognitive disorder is a primary scope, because it could reduce the rate of severe cognitive impairment and thus contribute to reduce healthcare costs in the next future. AIMS: The present paper aimed to build a virtuous diagnostic path of cognitive impairment, highlighting all the professionalism that can serve this purpose. METHODS: The Delphi method was used by the experts, who reviewed the information available during each meeting related to the following topics: early diagnosis of cognitive impairment, definition of Mild Cognitive Impairment, unmet needs in post-stroke patients, critical decision-making nodes in complex patients, risk factors, neuropsychological, imaging diagnosis, blood tests, the criteria for differential diagnosis and the possible treatments. RESULTS: The discussion panels analyzed and discussed the available evidences on these topics and the related items. At each meeting, the activities aimed at the creation of a diagnostic-welfare flow chart derived from the proposal of the board and the suggestions of the respondents. Subsequently, the conclusions of each panel were written, and the study group reviewed them until a global consensus was reached. Once this process was completed, the preparation of the final document was carried out. CONCLUSIONS: Eventually, we built an algorithm for the early diagnosis and treatment, the risk factors, with the possible differences among the different kinds of dementia.

Clinical validity of the Italian adaptation of the Uniform Data Set Neuropsychological Test Battery (I-UDSNB) in Mild Cognitive Impairment and Alzheimer's Disease.

BACKGROUND: The identification and staging of Alzheimer's Disease (AD) represent a challenge, especially in the prodromal stage of Mild Cognitive Impairment (MCI), when cognitive changes can be subtle. Worldwide efforts were dedicated to select and harmonize available neuropsychological instruments. In Italy, the Italian Network of Neuroscience and Neuro-Rehabilitation has promoted the adaptation of the Uniform Data Set Neuropsychological Test Battery (I-UDSNB), collecting normative data from 433 healthy controls (HC). Here, we aimed to explore the ability of I-UDSNB to differentiate between a) MCI and HC, b) AD and HC, c) MCI and AD. METHODS: One hundred thirty-seven patients (65 MCI, 72 AD) diagnosed after clinical-neuropsychological assessment, and 137 HC were included. We compared the I-UDSNB scores between a) MCI and HC, b) AD and HC, c) MCI and AD, with t-tests. To identify the test(s) most capable of differentiating between groups, significant scores were entered in binary logistic and in stepwise regressions, and then in Receiver Operating Characteristic curve analyses. RESULTS: Two episodic memory tests (Craft Story and Five Words test) differentiated MCI from HC subjects; Five Words test, Semantic Fluency (vegetables), and TMT-part B differentiated AD from, respectively, HC and MCI. CONCLUSIONS: Our findings indicate that the I-UDSNB is a suitable tool for the harmonized and concise assessment of patients with cognitive decline, showing high sensitivity and specificity for the diagnosis of MCI and AD.

Circulating HMGB1 in acute ischemic stroke and its association with post-stroke cognitive impairment.

Background: Ischemic stroke frequently leads to a condition known as post-stroke cognitive impairment (PSCI). Timely recognition of individuals susceptible to developing PSCI could facilitate the implementation of personalized strategies to mitigate cognitive deterioration. High mobility group box 1 (HMGB1) is a protein released by ischemic neurons and implicated in inflammation after stroke. Circulating levels of HMGB1 could potentially serve as a prognostic indicator for the onset of cognitive impairment following ischemic stroke. Objective: To investigate the predictive value of circulating HMGB1 concentrations in the acute phase of ischemic stroke for the development of cognitive dysfunction at the 3-month follow-up. Methods: A total of 192 individuals experiencing their initial episode of acute cerebral infarction were prospectively recruited for this longitudinal investigation. Concentrations of circulating HMGB1 were quantified using an enzyme-linked immunosorbent assay (ELISA) technique within the first 24 hours following hospital admission. Patients underwent neurological evaluation including NIHSS scoring. Neuropsychological evaluation was conducted at the 3-month follow-up after the cerebrovascular event, employing the Montreal Cognitive Assessment (MoCA) as the primary tool for assessing cognitive performance. Multivariable logistic regression models were employed to investigate the relationship between circulating HMGB1 concentrations and cognitive dysfunction following stroke, which was operationalized as a MoCA score below 26, while controlling for potential confounders including demographic characteristics, stroke severity, vascular risk factors, and laboratory parameters. Results: Of 192 patients, 84 (44%) developed PSCI. Circulating HMGB1 concentrations were significantly elevated in individuals who developed cognitive dysfunction following stroke compared to those who maintained cognitive integrity (8.4 ± 1.2 ng/mL vs 4.6 ± 0.5 ng/mL, respectively; p < 0.001). The prevalence of PSCI showed a dose-dependent increase with higher HMGB1 quartiles. After controlling for potential confounders such as demographic factors (age, gender, and education), stroke severity, vascular risk factors, and laboratory parameters in a multivariable logistic regression model, circulating HMGB1 concentrations emerged as a significant independent predictor of cognitive dysfunction following stroke (regression coefficient = 0.236, p < 0.001). Conclusion: Circulating HMGB1 concentrations quantified within the first 24 hours following acute cerebral infarction are significantly and independently correlated with the likelihood of developing cognitive dysfunction at the 3-month follow-up, even after accounting for potential confounding factors. HMGB1 may be a novel biomarker to identify patients likely to develop post-stroke cognitive impairment for targeted preventive interventions.

Serum Tau-A and Tau-C Levels and Their Association with Cognitive Impairment and Dementia Progression in a Memory Clinic Derived Cohort.

BACKGROUND: Serum-measured fragments of Tau cleaved by ADAM-10 (Tau-A) and Caspase-3 (Tau-C) have been found linked to change in cognitive function and risk of dementia. OBJECTIVES: 1) To determine the discriminatory abilities of Tau-A, and Tau-C in subjects with either mild cognitive impairment (MCI) due to Alzheimer's disease (AD) or AD dementia compared to a control group. 2) To determine if there is a relation between Tau-A, and Tau-C and established cerebrospinal fluid (CSF) markers of AD- ß-Amyloid1-42 (AB42), Phosphorylated-tau-181 (p-tau), and total-tau. 3) To determine if Tau-A and Tau-C are associated with progression rate from MCI due to AD to AD dementia. DESIGN: Cross-sectional and a substudy using a retrospective cohort design. SETTING: Memory clinic derived subjects contributing to the Danish Dementia Biobank. PARTICIPANTS: Cognitively unimpaired subjects (n=49), patients with mild cognitive impairment (MCI) due to AD (n=45), and Alzheimer's dementia (n=52). MEASUREMENTS: Competitive enzyme-linked immunosorbent assay (ELISA)-measured serum levels of Tau-A, and Tau-C. RESULTS: The ratio between Tau-A and Tau-C differed between the three groups (p=0.015). Age- and sex-adjusted Tau-A differed between groups with lower ratios being associated with more severe disease (p=0.023). Tau-C was trending towards significant correlation to CSF-levels of AB42 (Pearson correlation coefficient 0.164, p=0.051). Those with Tau-C-levels in the 2nd quartile had a hazard ratio (HR) of 2.91 (95% CI 1.01 - 8.44, p=0.04) of progression compared to those in the 1st quartile. Those in the 3rd quartile was found to have a borderline significant (p=0.055) HR of 2.63 (95% CI 0.98 - 7.05) when compared to those in the lowest quartile. CONCLUSIONS: Tau-A and the ratio between Tau-A and Tau-C showed significant differences between groups and were correlated to CSF-AB42. Tau-C values in the middle range were associated with faster progression from MCI to dementia. This pilot study adds to the mounting data suggesting serum-measured Tau-A and Tau-C as biomarkers useful in relation to diagnosis and progression rate in AD but need further validation.

An Exploration of the Memory Performance in Older Adult Hearing Aid Users on the Integrated Digit-in-Noise Test.

This study aimed to preliminarily investigate the associations between performance on the integrated Digit-in-Noise Test (iDIN) and performance on measures of general cognition and working memory (WM). The study recruited 81 older adult hearing aid users between 60 and 95 years of age with bilateral moderate to severe hearing loss. The Chinese version of the Montreal Cognitive Assessment Basic (MoCA-BC) was used to screen older adults for mild cognitive impairment. Speech reception thresholds (SRTs) were measured using 2- to 5-digit sequences of the Mandarin iDIN. The differences in SRT between five-digit and two-digit sequences (SRT5-2), and between five-digit and three-digit sequences (SRT5-3), were used as indicators of memory performance. The results were compared to those from the Digit Span Test and Corsi Blocks Tapping Test, which evaluate WM and attention capacity. SRT5-2 and SRT5-3 demonstrated significant correlations with the three cognitive function tests (rs ranging from -.705 to -.528). Furthermore, SRT5-2 and SRT5-3 were significantly higher in participants who failed the MoCA-BC screening compared to those who passed. The findings show associations between performance on the iDIN and performance on memory tests. However, further validation and exploration are needed to fully establish its effectiveness and efficacy.

Community screening for dementia among older adults in China: a machine learning-based strategy.

BACKGROUND: Dementia is a leading cause of disability in people older than 65 years worldwide. However, diagnosing dementia in its earliest symptomatic stages remains challenging. This study combined specific questions from the AD8 scale with comprehensive health-related characteristics, and used machine learning (ML) to construct diagnostic models of cognitive impairment (CI). METHODS: The study was based on the Shenzhen Healthy Ageing Research (SHARE) project, and we recruited 823 participants aged 65 years and older, who completed a comprehensive health assessment and cognitive function assessments. Permutation importance was used to select features. Five ML models using BalanceCascade were applied to predict CI: a support vector machine (SVM), multilayer perceptron (MLP), AdaBoost, gradient boosting decision tree (GBDT), and logistic regression (LR). An AD8 score ≥ 2 was used to define CI as a baseline. SHapley Additive exPlanations (SHAP) values were used to interpret the results of ML models. RESULTS: The first and sixth items of AD8, platelets, waist circumference, body mass index, carcinoembryonic antigens, age, serum uric acid, white blood cells, abnormal electrocardiogram, heart rate, and sex were selected as predictive features. Compared to the baseline (AUC = 0.65), the MLP showed the highest performance (AUC: 0.83 ± 0.04), followed by AdaBoost (AUC: 0.80 ± 0.04), SVM (AUC: 0.78 ± 0.04), GBDT (0.76 ± 0.04). Furthermore, the accuracy, sensitivity and specificity of four ML models were higher than the baseline. SHAP summary plots based on MLP showed the most influential feature on model decision for positive CI prediction was female sex, followed by older age and lower waist circumference. CONCLUSIONS: The diagnostic models of CI applying ML, especially the MLP, were substantially more effective than the traditional AD8 scale with a score of ≥ 2 points. Our findings may provide new ideas for community dementia screening and to promote such screening while minimizing medical and health resources.

An analysis of factors influencing cognitive dysfunction among older adults in Northwest China based on logistic regression and decision tree modelling.

BACKGROUND: Cognitive dysfunction is one of the leading causes of disability and dependence in older adults and is a major economic burden on the public health system. The aim of this study was to investigate the risk factors for cognitive dysfunction and their predictive value in older adults in Northwest China. METHODS: A cross-sectional study was conducted using a multistage sampling method. The questionnaires were distributed through the Elderly Disability Monitoring Platform to older adults aged 60 years and above in Northwest China, who were divided into cognitive dysfunction and normal cognitive function groups. In addition to univariate analyses, logistic regression and decision tree modelling were used to construct a model to identify factors that can predict the occurrence of cognitive dysfunction in older adults. RESULTS: A total of 12,494 valid questionnaires were collected, including 2617 from participants in the cognitive dysfunction group and 9877 from participants in the normal cognitive function group. Univariate analysis revealed that ethnicity, BMI, age, educational attainment, marital status, type of residence, residency status, current work status, main economic source, type of chronic disease, long-term use of medication, alcohol consumption, participation in social activities, exercise status, social support, total scores on the Balanced Test Assessment, total scores on the Gait Speed Assessment total score, and activities of daily living (ADL) were significantly different between the two groups (all P < 0.05). According to logistic regression analyses, ethnicity, BMI, educational attainment, marital status, residency, main source of income, chronic diseases, annual medical examination, alcohol consumption, exercise status, total scores on the Balanced Test Assessment, and activities of daily living (ADLs) were found to influence cognitive dysfunction in older adults (all P < 0.05). In the decision tree model, the ability to perform activities of daily living was the root node, followed by total scores on the Balanced Test Assessment, marital status, educational attainment, age, annual medical examination, and ethnicity. CONCLUSIONS: Traditional risk factors (including BMI, literacy, and alcohol consumption) and potentially modifiable risk factors (including balance function, ability to care for oneself in daily life, and widowhood) have a significant impact on the increased risk of cognitive dysfunction in older adults in Northwest China. The use of decision tree models can help health care workers better assess cognitive function in older adults and develop personalized interventions. Further research could help to gain insight into the mechanisms of cognitive dysfunction and provide new avenues for prevention and intervention.

Digital exclusion and cognitive impairment in older people: findings from five longitudinal studies.

OBJECTIVES: Older people are more likely to have digital exclusion, which is associated with poor health. This study investigated the relationship between digital exclusion and cognitive impairment in older adults from 23 countries across five longitudinal surveys. DESIGN AND MEASUREMENTS: Digital exclusion is defined as self-reported non-use of the Internet. We assessed cognitive impairment on three dimensions: orientation, memory, and executive function. We used generalized estimation equations fitting binary logistic regression with exchangeable correlations to study the relationship between digital exclusion and cognitive impairment, and apply the minimum sufficiently adjusted set of causally directed acyclic graphs as the adjusted variable. SETTING AND PARTICIPANTS: We pooled a nationally representative sample of older adults from five longitudinal studies, including the China Health and Retirement Longitudinal study (CHARLS), the English Longitudinal Study of Ageing (ELSA), the Health and Retirement Study (HRS), the Mexican Health and Ageing Study (MHAS) and the Survey of Health, Ageing and Retirement in European (SHARE). RESULTS: We included 62,413 participants from five longitudinal studies. Digital exclusion varied by country, ranging from 21.69% (SHARE) in Denmark to 97.15% (CHARLS) in China. In the original model, digital exclusion was significantly associated with cognitive impairment in all five studies. In the adjusted model, these associations remained statistically significant: CHARLS (Odds ratio [OR] = 2.81, 95% confidence interval [CI] 1.84-4.28, ELSA (1.92 [1.70-2.18]), HRS(2.48[2.28-2.71), MHAS (1.92 [1.74-2.12]), and SHARE (2.60 [2.34-2.88]). CONCLUSION: Our research shows that a significant proportion of older people suffer from digital exclusion, especially in China. Digital exclusion was positively correlated with cognitive impairment. These findings suggest that digital inclusion could be an important strategy to improve cognitive function and reduce the risk of cognitive impairment in older adults.

A multimodal machine learning model for predicting dementia conversion in Alzheimer's disease.

Alzheimer's disease (AD) accounts for 60-70% of the population with dementia. Mild cognitive impairment (MCI) is a diagnostic entity defined as an intermediate stage between subjective cognitive decline and dementia, and about 10-15% of people annually convert to AD. We aimed to investigate the most robust model and modality combination by combining multi-modality image features based on demographic characteristics in six machine learning models. A total of 196 subjects were enrolled from four hospitals and the Alzheimer's Disease Neuroimaging Initiative dataset. During the four-year follow-up period, 47 (24%) patients progressed from MCI to AD. Volumes of the regions of interest, white matter hyperintensity, and regional Standardized Uptake Value Ratio (SUVR) were analyzed using T1, T2-weighted-Fluid-Attenuated Inversion Recovery (T2-FLAIR) MRIs, and amyloid PET (αPET), along with automatically provided hippocampal occupancy scores (HOC) and Fazekas scales. As a result of testing the robustness of the model, the GBM model was the most stable, and in modality combination, model performance was further improved in the absence of T2-FLAIR image features. Our study predicts the probability of AD conversion in MCI patients, which is expected to be useful information for clinician's early diagnosis and treatment plan design.

Predictive value for cerebrospinal fluid Alzheimer's disease profile of different measures of verbal episodic memory in patients with MCI.

Neuropsychological evidence of memory impairment represents the main feature of the clinical onset of typical Alzheimer's disease (AD). Rey's Auditory Verbal Learning Test (RAVLT) and Logical Memory (LM) are two tests both assessing verbal episodic memory, widely used in clinical practice. Our aim was to investigate the added value of their combined use in predicting cerebrospinal fluid (CSF) AD biomarkers positivity in a retrospective consecutive series of patients with mild cognitive impairment (MCI). 169 MCI patients were included. For all of them neuropsychological assessment and CSF analysis were available. According to CSF A/T/(N) profile, 109 were defined as MCI due to AD (A+T+), and 60 were non-AD MCI (A-T-). Logistic regression model and receiver-operating characteristic (ROC) curves were analyzed to evaluate the discriminatory power of single and combined sub-measures between AD and non-AD patients. The combination of RAVLT-del with LM could acceptably discriminate the two groups (AUC: 0.69, CI 95% 0.617-0.761, sens: 0.75, spec. 0.58, p < 0.001), while the single tests did not show sufficient discriminative performance. Our study shows that the combination of RAVLT delayed recall with LM better predicts the biological AD diagnosis (A+T+), showing a good discriminative power between MCI-AD from non-AD MCI. Since RAVLT and LM assess different components of verbal episodic memory, they should be considered as complementary, rather than interchangeable, tests.

Prevalence and risk factors for dementia and mild cognitive impairment among older people in Southeast China: a community-based study.

BACKGROUND: With the aging population, the number of individuals with dementia in China is increasing rapidly. This community-based study aimed to investigate the prevalence and risk factors for dementia and mild cognitive impairment (MCI) among older adults in China. METHODS: In this study, 20,070 individuals aged ≥ 65 were recruited between January 1, 2022, and February 1, 2023, from ten communities in Xiamen City, China. We collected data on age, sex, level of education, and medical history, as well as global cognition and functional status. The prevalence of dementia and MCI was examined, and the risk factors for different groups were assessed. RESULTS: The overall prevalence of dementia and MCI was approximately 5.4% (95% confidence interval [CI], 5.1-5.7) and 7.7% (95% CI, 7.4-8.1), respectively. The results also indicated that dementia and MCI share similar risk factors, including older age, female sex, hypertension, and diabetes mellitus. Compared with individuals with no formal education, those with > 6 years of education had an odds ratio for MCI of 1.83 (95% CI, 1.49-2.25). We also found that only 5.5% of the positive participants chose to be referred to the hospital for further diagnosis and treatment during follow-up visits. CONCLUSIONS: This study estimated the prevalence and risk factors for dementia and MCI among individuals aged ≥ 65 years in Southeast China. These findings are crucial for preventing and managing dementia and MCI in China.

Combining plasma Aß and p-tau217 improves detection of brain amyloid in non-demented elderly.

BACKGROUND: Maximizing the efficiency to screen amyloid-positive individuals in asymptomatic and non-demented aged population using blood-based biomarkers is essential for future success of clinical trials in the early stage of Alzheimer's disease (AD). In this study, we elucidate the utility of combination of plasma amyloid-ß (Aß)-related biomarkers and tau phosphorylated at threonine 217 (p-tau217) to predict abnormal Aß-positron emission tomography (PET) in the preclinical and prodromal AD. METHODS: We designed the cross-sectional study including two ethnically distinct cohorts, the Japanese trial-ready cohort for preclinica and prodromal AD (J-TRC) and the Swedish BioFINDER study. J-TRC included 474 non-demented individuals (CDR 0: 331, CDR 0.5: 143). Participants underwent plasma Aß and p-tau217 assessments, and Aß-PET imaging. Findings in J-TRC were replicated in the BioFINDER cohort including 177 participants (cognitively unimpaired: 114, mild cognitive impairment: 63). In both cohorts, plasma Aß(1-42) (Aß42) and Aß(1-40) (Aß40) were measured using immunoprecipitation-MALDI TOF mass spectrometry (Shimadzu), and p-tau217 was measured with an immunoassay on the Meso Scale Discovery platform (Eli Lilly). RESULTS: Aß-PET was abnormal in 81 participants from J-TRC and 71 participants from BioFINDER. Plasma Aß42/Aß40 ratio and p-tau217 individually showed moderate to high accuracies when detecting abnormal Aß-PET scans, which were improved by combining plasma biomarkers and by including age, sex and APOE genotype in the models. In J-TRC, the highest AUCs were observed for the models combining p-tau217/Aß42 ratio, APOE, age, sex in the whole cohort (AUC = 0.936), combining p-tau217, Aß42/Aß40 ratio, APOE, age, sex in the CDR 0 group (AUC = 0.948), and combining p-tau217/Aß42 ratio, APOE, age, sex in the CDR 0.5 group (AUC = 0.955), respectively. Each subgroup results were replicated in BioFINDER, where the highest AUCs were seen for models combining p-tau217, Aß42/40 ratio, APOE, age, sex in cognitively unimpaired (AUC = 0.938), and p-tau217/Aß42 ratio, APOE, age, sex in mild cognitive impairment (AUC = 0.914). CONCLUSIONS: Combination of plasma Aß-related biomarkers and p-tau217 exhibits high performance when predicting Aß-PET positivity. Adding basic clinical information (i.e., age, sex, APOE Îµ genotype) improved the prediction in preclinical AD, but not in prodromal AD. Combination of Aß-related biomarkers and p-tau217 could be highly useful for pre-screening of participants in clinical trials of preclinical and prodromal AD.

A Combined Index Using the Mini-Mental State Examination and Lawton Index to Discriminate Between Clinical Dementia Rating Scores of 0.5 and 1: A Development and Validation Study.

Objective: To develop a combined index using cognitive function and instrumental activities of daily living (IADL) to discriminate between Clinical Dementia Rating (CDR) scores of 0.5 and 1 in the clinical setting, and to investigate its optimal cutoff values and internal and external validities.Methods: We included outpatients aged 65-89 years with CDR scores of 0.5 or 1. The optimal cutoff values and internal validity were verified using Japanese memory clinic-based datasets between September 2010 and October 2021 [National Center for Geriatrics and Gerontology (NCGG) datasets]. Cognitive function and IADL were assessed using the Mini-Mental State Examination (MMSE) and Lawton Index (LI), respectively. The optimal cutoff values were defined using the Youden Index. To verify internal validity, sensitivity and specificity were calculated using stratified 5-fold cross-validation. To verify external validity, sensitivity and specificity of the optimal cutoff values were assessed in the Organized Registration for the Assessment of dementia on Nationwide General consortium toward Effective treatment (ORANGE) Registry dataset between July 2015 and March 2022, which has multicenter clinical data.Results: A total of 800 (mean age, 77.53 years; men, 50.1%) and 1494 (mean age, 77.97 years; men, 43.3%) participants comprised the NCGG and ORANGE Registry datasets, respectively. The optimum cutoff values for men and women were determined as MMSE < 25 and LI < 5 and MMSE < 25 and LI < 8, respectively; such a combined index showed good discriminative performance in internal (sensitivity/specificity: men, 92.50/73.52; women, 88.57/65.65) and external validities (men, 81.43/77.62; women, 77.64/74.67).Conclusion: The index developed is useful in discriminating between CDR scores of 0.5 and 1 and should be applicable to various settings, such as memory clinics and clinical research.

Diagnostic accuracy of cognitive screening tools validated for older adults in Iran: a systematic review and meta-analysis.

BACKGROUND: This systematic review aims to comprehensively assess the diagnostic accuracy of cognitive screening tools validated for older adults in Iran, providing evidence-based recommendations for clinicians and researchers. METHODS: A comprehensive search in March 2023 across Web of Science, PubMed, Scopus, ScienceDirect, SID, IranMedex, and IranDoc, enhanced by hand-searching references and Google Scholar, identified cross-sectional studies on cognitive screening in Iranian seniors. We assessed diagnostic accuracy, cognitive domains, and test strengths and weaknesses. A bivariate random-effects meta-analysis provided summary estimates and 95% confidence intervals, illustrated in forest plots. RESULTS: Our review, derived from an initial screening of 38 articles, focused on 17 studies involving 14 cognitive screening tools and participant counts from 60 to 350, mostly from specialized clinics. The MMSE was the only tool examined in at least three studies, prompting a meta-analysis revealing its sensitivity at 0.89 and specificity at 0.77 for dementia detection, albeit amidst significant heterogeneity (I^2 > 80%). ACE-III demonstrated the highest diagnostic accuracy for MCI and dementia, while MoCA's performance was deemed adequate for MCI and excellent for dementia. High bias risk in studies limits interpretation. CONCLUSION: This review identifies key cognitive tools for dementia and MCI in Iranian older adults, tailored to educational levels for use in primary and specialized care. It emphasizes the need for further validation to enhance diagnostic precision across diverse settings, within a concise framework prioritizing brevity and accuracy for clinical applicability.

[Cognitive impairment in cerebrovascular diseases]. / Kognitivnye narusheniya pri sosudistykh zabolevaniyakh golovnogo mozga.

Cognitive impairment, which is highly prevalent, especially among older people, leads to a decrease in the quality of life of patients, impairment of daily activities, and an increased risk of dementia and mortality. Currently, much attention is paid to mild cognitive impairment. The article discusses diagnostic criteria and possible clinical variants of this syndrome. Given the high rate of progression of mild cognitive impairment to dementia, it is necessary to identify risk groups and carry out therapeutic preventive measures. Correction of potentially modifiable risk factors is considered as a promising direction of therapy. Sufficient physical and mental activity, proper diet, normalization of sleep, visual acuity and hearing are necessary. Preventing stroke and controlling vascular risk factors may reduce the risk of mild cognitive impairment progressing to dementia.

[Impairment of attention and executive functions in chronic cerebrovascular disease and Alzheimer's disease]. / Narushenie vnimaniya i upravlyayushchikh funktsii pri sosudistykh kognitivnykh narusheniyakh i bolezni Al'tsgeimera.

OBJECTIVE: To establish specific features of executive functions (EF) impairment and attention in vascular cognitive impairment (VCI) and Alzheimer's disease (AD). MATERIAL AND METHODS: Eighty people (over the age of 50) diagnosed with cerebrovascular disease (CVD) and AD, as well as 29 healthy volunteers (control group), were examined. The following neuropsychological methods were used to study the quantitative and qualitative characteristics of cognitive impairments: Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), EXIT-25, Frontal Assessment Battery (FAB), Clock Drawing Test, «12 Words¼ test, verbal associations (literal and categorical) method, Trail Making Test A and B, Symbol-Digit Modalities Test (SDMT), Stroop Test, and Benton Visual Retention Test. Mandatory inclusion criteria in the study included having a completed magnetic resonance imaging (MRI) of the brain (in T1, T2, FLAIR, DWI, SWI modes) within 1 year before enrollment in one of the groups. RESULTS: No significant differences in age, sex, and level of education were found between the groups. Groups AD and CVD were also comparable in the severity of cognitive impairment overall. Attention and working memory deficits were observed in both CVD and AD, with slightly more pronounced deficits in the AD group. Qualitative analysis of individual components of working memory revealed that both CVD and AD groups had comparable cognitive control impairment compared to the control group, while AD was characterized by a more significant decrease in intellectual flexibility compared to CVD. Sustained attention was equally impaired among patients in the CVD and AD groups, with a significant difference from the control group (p<0.05). In terms of memory, it was found that auditory-verbal memory and semantic memory were significantly more affected in AD, while visual memory was impaired in both conditions. CONCLUSION: Attention and EF impairments are not specific to the «subcortical¼ type of cognitive disorders. Already in the early stages, AD is characterized by a significant impairment of attention and EF, and such a component of EF as intellectual flexibility suffers at the onset of AD to a greater extent than in VCI. Memory impairments are not specific to AD; already at the onset of VCI, visual memory impairment comparable to AD is noted. The obtained data can be used for early neuropsychological diagnosis and differential diagnosis of dementing cerebral diseases.

[Cognitive impairment in patients with arterial hypertension]. / Kognitivnye narusheniya u patsientov s arterial'noi gipertenziei.

Arterial hypertension (AH) is a leading risk factor for cardiovascular diseases including cerebrovascular complications. Strokes and/or vascular cognitive impairment (VCI) are considered as a clinical sign of brain damage as a target organ in hypertension. To identify and assess the severity of VCI, patients with hypertension should undergo a neuropsychological assessment. Neuroimaging confirm the vascular origin of cognitive impairment. Patient management should include antihypertensive therapy along with neuroprotection. Among different neuroprotective therapy, ethylmethylhydroxypyridine succinate (mexidol) is one of medication with serious evidence of clinical efficacy.

[Algorithms for the diagnosis and treatment of cognitive impairment and dysphagia in stroke patients]. / Algoritmy diagnostiki i lecheniya kognitivnykh narushenii i disfagii u patsientov posle insul'ta.

Stroke is a socially significant neurological disease, the second most common cause of disability and mortality. A wide range of neurological problems that occur after stroke: cognitive, motor, speech, and language disfunction, neuropsychiatric, swallowing disorders and others, complicate rehabilitation, impair social and everyday adaptation, and reduce the quality of life of patients and their caregivers. Cognitive impairment (CI) is one of the most significant and common complications of stroke. Stroke increases the risk of their development by 5-8 times. Dysphagia is also a common symptom of stroke, the cause of aspiration complications (pneumonia), and nutritional imbalance. It increases the possibility of developing CI and dementia, and contributes to an increase in mortality. Older adults with CI are at a higher risk of developing dysphagia, therefore the early symptoms of dysphagia (presbyphagia) should be diagnosed. In recent years, the connection between CI and dysphagia has been actively studied. It is extremely important to identify CI and swallowing disorders as early as possible in patients both before and at all stages after stroke; as well as to develop combined multidisciplinary protocols for the rehabilitation of patients with these disorders with pharmacological support for the process.

[Diagnostic approaches to assessing mild behavioral impairment in patients with mild cognitive impairment]. / Diagnosticheskie podkhody k otsenke subklinicheskikh neiropsikhicheskikh simptomov u patsientov s myagkim kognitivnym snizheniem.

OBJECTIVE: To assess the prevalence of mild behavioral impairment (MBI ) in elderly individuals with mild cognitive impairment (MCI ), refine diagnostic criteria, and characterize the identified neuropsychiatric symptoms. MATERIAL AND METHODS: Sixty-three individuals over 50 years of age (median 72 [68; 77]) with MCI underwent psychiatric and psychometric assessments using clinical and psychopathological methods and scales. Statistical analysis was conducted to evaluate intergroup differences, ROC-analysis with calculation of the area under the curve (AUC) was performed, and sensitivity, specificity, and accuracy of MBI diagnosis were determined for MBI-C. RESULTS: The prevalence of MBI using only ISTAART research criteria was 65%. An optimal diagnostic cut point for the MBI-C scale with the highest AUC (0.793), at 10 points, was identified. Upon a comprehensive assessment of MBI using criteria and optimal cut point values from the MBI-C scale, the prevalence was 33% (median 16 [14; 20]). Patients with MBI+MCI and MCI only did not significantly differ in MMSE and MoCA test results. Significant intergroup differences were observed in the severity of symptoms such as apathy (p<0.001), depression and anxiety (p<0.001), agitation and impulsivity (p<0.001), social behavioral disturbances (p=0.009), and subsyndromal psychotic symptoms (p<0.001). The most common symptoms were related to impulse control deficits, irritability, agitation, depression, anxiety, and apathy, while less common symptoms were associated with social behavioral disturbances and subsyndromal psychotic symptoms. CONCLUSION: Novel data on the diagnostic features of MBI in elderly patients with MCI in the Russian-speaking population are presented. An optimal diagnostic cut point for the MBI-C scale in a sample of patients from specialized clinics for comprehensive use with commonly accepted criteria was determined. Further research is needed to adapt and validate the MBI-C scale and provide prognostic evaluation of MBI in the context of MCI progression to dementia.

Hyponatremia as a predictor of cognitive deterioration in hospitalized post-stroke patients.

PURPOSE: Evidence is scarce regarding the association between hyponatremia and alterations in cognitive function among hospitalized older patients. We aimed to investigate the associations between hyponatremia and the baseline cognitive status, as well as the improvement in cognitive function, in hospitalized post-stroke patients. METHODS: This retrospective cohort study included consecutive hospitalized post-stroke patients. Serum sodium concentrations were extracted from medical records based on blood tests performed within 24 h of admission, with hyponatremia defined as a serum sodium concentration < 135 mEq/L. The main outcomes included admission and discharge scores for cognitive levels, assessed through the cognitive domain of the Functional Independence Measure (FIM-cognition), as well as the score changes observed during the hospitalization period. Multivariate linear regression analyses were used to determine the association between hyponatremia and outcomes of interest, adjusted for potential confounders. RESULTS: Data from 955 patients (mean age 73.2 years; 53.6 % men) were included in the analysis. The median baseline blood sodium level was 139 [137, 141], and 84 patients (8.8 %) exhibited hyponatremia. After full adjustment for confounders, the baseline hyponatremia was significantly and negatively associated with FIM-cognition values at admission (ß = -0.009, p = 0.016), discharge (ß = -0.038, p = 0.043), and the gain during hospital stay (ß = -0.040, p = 0.011). CONCLUSION: Baseline hyponatremia has demonstrated a correlation with decline in cognitive level over the course of rehabilitation in individuals after stroke. Assessing hyponatremia at the outset proves to be a pivotal prognostic indicator.