Dementia and Geriatric Cognitive Disorders最新文献

Introduction: Stroke is a devastating medical disorder associated with significant morbidity and mortality among adults and the elderly worldwide. Although numerous primary studies have been conducted to determine the pooled predictors of poststroke cognitive decline among stroke survivors in Sub-Saharan Africa, these studies presented inconsistent findings. Hence, the review aimed to determine the pooled predictors of poststroke cognitive decline among stroke survivors in Sub-Saharan Africa.

Methods: The eligible studies were accessed through Google Scholar, Scopus, PubMed, and Web of Science databases. A manual search of the reference lists of included studies was performed. A weighted inverse-variance random-effects model was used to determine the pooled predictors of poststroke cognitive decline among stroke survivors in Sub-Saharan Africa.

Results: A total of 1,710 stroke survivors from 10 primary studies were included in the final meta-analysis. Increased age (≥45 years) (adjusted odds ratio [AOR] = 1.32, 95% CI: 1.13, 1.54), lower educational level (AOR = 4.58, 95% CI: 2.98, 7.03), poor functional recovery (AOR = 1.75, 95% CI: 1.42, 2.15), and left hemisphere stroke (AOR = 4.88, 95% CI: 2.98, 7.99) were significantly associated with poststroke cognitive decline.

Conclusions: Increased age, lower educational level, poor functional recovery, and left hemisphere stroke were the pooled independent predictors of poststroke cognitive decline in Sub-Saharan Africa Healthcare providers, and other concerned bodies should give attention to these risk factors as the early identification may help to improve the cognitive profile of stroke survivors.

Introduction: The prevalence of cognitive impairment and dementia in the older population is increasing, and thereby, early detection of cognitive decline is essential for effective intervention.

Methods: This study included 2,288 participants with normal cognitive function from the Ma'anshan Healthy Aging Cohort Study. Forty-two potential predictors, including demographic characteristics, chronic diseases, lifestyle factors, anthropometric indices, physical function, and baseline cognitive function, were selected based on clinical importance and previous research. The dataset was partitioned into training, validation, and test sets in a proportion of 60% for training, 20% for validation, and 20% for testing, respectively. Recursive feature elimination was used for feature selection, followed by six machine learning algorithms that were employed for model development. The performance of the models was evaluated using area under the curve (AUC), specificity, sensitivity, and accuracy. Moreover, SHapley Additive exPlanations (SHAP) was conducted to access the interpretability of the final selected model and to gain insights into the impact of features on the prediction outcomes. SHAP force plots were established to vividly show the application of the prediction model at the individual level.

Results: The final predictive model based on the Naive Bayes algorithm achieved an AUC of 0.820 (95% CI, 0.773-0.887) on the test set, outperforming other algorithms. The top ten influential features in the model included baseline Mini-Mental State Examination (MMSE), education, self-reported economic status, collective or social activities, Pittsburgh sleep quality index (PSQI), body mass index, systolic blood pressure, diastolic blood pressure, instrumental activities of daily living, and age. The model demonstrated the potential to identify individuals at a higher risk of cognitive impairment within 3 years from older adults.

Conclusion: The predictive model developed in this study contributes to the early detection of cognitive impairment in older adults by primary healthcare staff in community settings.

Introduction: The prevalence of mild and major neurocognitive disorders (NCDs), also referred to as mild cognitive impairment and dementia, is rising globally. The prevention of NCDs is a major global public health interest. We sought to synthesize the literature on potentially modifiable risk factors for NCDs.

Methods: We conducted an umbrella review using a systematic search across multiple databases to identify relevant systematic reviews and meta-analyses. Eligible reviews examined potentially modifiable risk factors for mild or major NCDs. We used a random-effects multi-level meta-analytic approach to synthesize risk ratios for each risk factor while accounting for overlap in the reviews. We further examined risk factors for major NCD due to two common etiologies: Alzheimer's disease and vascular dementia.

Results: A total of 45 reviews with 212 meta-analyses were synthesized. We identified fourteen broadly defined modifiable risk factors that were significantly associated with these disorders: alcohol consumption, body weight, depression, diabetes mellitus, diet, hypertension, less education, physical inactivity, sensory loss, sleep disturbance, smoking, social isolation, traumatic brain injury, and vitamin D deficiency. All 14 factors were associated with the risk of major NCD, and five were associated with mild NCD. We found considerably less research for vascular dementia and mild NCD.

Conclusion: Our review quantifies the risk associated with 14 potentially modifiable risk factors for mild and major NCDs, including several factors infrequently included in dementia action plans. Prevention strategies should consider approaches that reduce the incidence and severity of these risk factors through health promotion, identification, and early management.

Introduction: Sleep duration is proposed as a lifestyle-related risk factor for cognitive impairment. We investigated the association between sleep duration and cognitive function in a large population-based cohort aged 62-65 years.

Methods: Cross-sectional analyses from the Akershus Cardiac Examination 1950 Study. Linear and nonlinear models were conducted to explore the association between self-reported sleep duration and cognitive function, adjusted for established risk factors for cognitive impairment.

Results: We included 3,348 participants, mean age (SD) was 63.9 ± 0.6 years, 48.2% were women, and 47.9% had education >12 years. Mean sleep duration (SD) was 7.0 ± 1.0 h, and 10.2% had abnormal sleep duration (<6 or >8 h). Individuals reporting <6 h or >8 h of sleep scored significantly lower on MoCA test and delayed recall trial in adjusted analysis.

Conclusions: Sleep duration showed an inverted U-shaped association with global cognitive function and memory, suggesting that both shortened and prolonged sleep are related to adverse brain health.

Introduction: Tau protein accumulation in the brain is thought to be one of the causes of progressive supranuclear palsy (PSP). The glymphatic system was discovered a decade ago as a waste drainage system in the brain that promotes the elimination of amyloid-beta and tau protein. We here evaluated the relationships between glymphatic system activity and regional brain volumes in PSP patients.

Method: Subjects were 24 patients with PSP and 42 healthy participants who underwent diffusion tensor imaging (DTI). We computed the diffusion tensor image analysis along the perivascular space (DTI‑ALPS) index as a proxy of glymphatic system activity, and estimated the relationships between the DTI‑ALPS index and regional brain volume in PSP patients by whole-brain and region-of-interest analyses, including analyses of the midbrain and third and lateral ventricles.

Results: The DTI‑ALPS index was significantly lower in patients with PSP, compared with healthy subjects. Further, there were significant correlations between the DTI‑ALPS index and the regional brain volumes in the midbrain tegmentum, pons, right frontal lobe, and lateral ventricles in patients with PSP.

Conclusions: Our data suggest that the DTI‑ALPS index is a good biomarker for PSP and might be effective to distinguish PSP from other neurocognitive disorders.

Introduction: Identifying health conditions of persons with cognitive impairment (PCI) in the community and exploring their implications for caregiving experience are vital for effective allocation of healthcare resources. This study examined distinct PCI health profiles among community-dwelling PCI and their association with caregiving burden and benefits.

Methods: Latent profile analysis and multivariable regression were applied to dyadic data from 266 PCI and their caregivers in Singapore.

Results: Three PCI health profiles were identified: less impaired (40% of PCI), moderately impaired (30%), and severely impaired (30%). Caregivers for severely impaired PCI were more likely to report a higher level of caregiving burden, and caregivers for moderately impaired PCI were more likely to report a higher level of caregiving benefits, compared to caregivers for less impaired PCI.

Conclusion: The findings captured heterogeneity in health status among PCI in the community. Tailored interventions, based on PCI health profiles, should be designed to reduce caregiving burden and increase caregiving benefits.

Introduction: Vascular factors have been shown to be associated with increased risk of dementia. However, clinical trials have so far been unsuccessful, suggesting new approaches are needed. The aim of this study was to use population-based real-world data to investigate risk factors and preventive factors for dementia, including the effects of traditional Chinese medicine (TCM).

Methods: This is a retrospective cohort study using LHID2000, a dataset randomly selected from Taiwan's National Health Insurance Research Database. Subjects with occlusion and stenosis of precerebral and cerebral arteries, cerebral atherosclerosis without mention of cerebral infarction, and transient cerebral ischemia were included. Subjects with dementia at baseline were excluded. The primary endpoint was dementia. Data for demographic and clinical comorbid status and treatments administered at baseline in 2000 and at the end of follow-up in 2013 were included.

Results: A total of 4,207 subjects with cerebral vascular disease and no cognitive impairment were included, of whom 392 converted to dementia during an average 5.15-year (SD: 3.79) follow-up. Depression (adjusted HR: 1.54, 95% confidence interval [CI]: 1.13-2.09), osteoporosis (adjusted HR: 1.34, 95% CI: 1.04-1.74), and the use of enalapril (adjusted HR: 1.37, 95% CI: 1.09-1.73) were risk factors for dementia, while nitroglycerin (adjusted HR: 0.67, 95% CI: 0.53-0.85) was a protecting factor, in subjects with cerebrovascular diseases without mention of cerebral infarction. In total, statins were shown to be associated with decreased risk of dementia (HR: 0.73, 95% CI: 0.59-0.91); however, no one statin subtype or TCM had such an effect.

Conclusion: Depression, osteoporosis, and the use of enalapril were associated with a higher risk of dementia, while nitroglycerin might be a protecting factor for dementia, in subjects with cerebrovascular diseases without mention of cerebral infarction.

Introduction: Both physical and cognitive functions are required to be assessed to determine the level of gait independence in patients with Alzheimer's disease (AD); nonetheless, a method to achieve this assessment has not been established. This study aimed to investigate the accuracy of an assessment method that combined muscle strength, balance ability, and cognitive function parameters in discriminating the level of gait independence in a real-world setting in hospitalized patients with AD.

Methods: In this cross-sectional study, 63 patients with AD (mean age: 86.1 ± 5.8 years) were classified into three groups according to their gait level: independent, modified independent (independent walking with walking aids), and dependent groups. Discrimination accuracy was calculated for single items of muscle strength, balance ability, and cognitive function tests and for combinations of each.

Results: The combined accuracy of muscle strength, balance ability, and cognitive function had a positive predictive value of 100.0% and a negative predictive value of 67.7% between the independent and modified independent groups. The positive and negative predictive values were 100.0% and 72.4%, respectively, between the modified independent and dependent groups.

Conclusion: This study emphasizes the importance of assessing the level of gait independence in a real-world setting in patients with AD from the perspective of both physical and cognitive functions and proposes a novel method for discriminating an optimal state.

Introduction: Cerebral infarction is one of the most common cerebrovascular diseases. The sequelae caused by cerebral infarction, including limb paralysis, crooked mouth corners, language barriers, etc., seriously affect the patient's physical and mental health and enthusiasm for rehabilitation training. Therefore, psychological intervention has important positive significance for the rehabilitation and nursing of patients with cerebral infarction.

Methods: This is a single-blind controlled study. 168 patients with cerebral infarction who met the inclusion criteria and visited our hospital from January 2018 to January 2020 were randomly divided into a control group (n = 84) and an intervention group (n = 84). The patients in the intervention group received an additional 3-month psychological treatment on the basis of the patients in the control group. The National Institutes of Health Stroke Scale (NIHSS), Activities of Daily Living (ADL) scale, Mini-Mental State Examination (MMSE), and Hamilton Depression Rating Scale (HAMD) were measured before and after the psychological intervention.

Results: The 3-month psychological intervention we designed significantly reduced the NIHSS and HAMD scores of patients with cerebral infarction compared with traditional rehabilitation care for cerebral infarction, implying that our psychological intervention courses can improve patients' cognitive function and suppress patients' depression. Consistently, our psychological intervention also significantly improved ADL and MMSE scores 3 months after the onset of cerebral infarction patients, implying that this psychological intervention helped patients recover their daily functions relative to conventional care.

Conclusion: Psychological intervention can be used as an adjunct therapy in the treatment and nursing of patients with cerebral infarction.