Dementia and Geriatric Cognitive Disorders最新文献

Introduction: Neurodegenerative diseases are a growing concern in an aging global population. Frailty, often conceptualized as a state of diminished physiological reserve and increased susceptibility to stressors, emerges as a pivotal factor in this context. While frailty may be modified, it is essential to recognize its frequently irreversible nature, necessitating a careful approach when considering its role and influence in the progression from mild cognitive impairment (MCI) to dementia and within dementia progression.

Methods: A retrospective study including 1,284 participants, attending a Cognitive Disturbances and Dementia unit from January 2021 to May 2023, was conducted. Frailty was assessed using the clinical frailty scale (CFS) score. Multilevel univariate and multivariate logistic regression models were developed to determine the contributions of patient characteristics, including frailty, to disease progression.

Results: Frailty significantly increased with higher global clinical dementia rating (CDR) subgroups, suggesting escalating frailty burden with disease progression. Age, CFS, and mini-mental state examination (MMSE) scores were significant predictors of progression from MCI to dementia and to more severe dementia stages, even when considering the independence from variables contributing to frailty. Patients transitioning to a higher CDR group exhibited higher CFS scores. Age, education, anticholinergic burden, cumulative illness rating scale - geriatric, MMSE, and neuropsychiatric inventory scores significantly contributed to frailty.

Conclusions: Frailty plays a critical role in the transition from MCI to dementia and within dementia progression. Age, cognitive impairment, and frailty were identified as significant predictors of disease progression. The CFS is a clinically applicable tool for frailty assessment. Regular frailty assessments may be valuable in early detection and management of dementia.

Introduction: We comprehensively evaluated how self- and informant-reported neuropsychiatric symptoms (NPS) were differentially associated with cerebral amyloid-beta (Aβ) PET levels in older adults without dementia.

Methods: Two hundred and twenty-one participants (48% female, age = 73.4 years ± 8.4, Clinical Dementia Rating = 0 [n = 184] or 0.5 [n = 37]) underwent an Aβ-PET scan (florbetapir or PIB), comprehensive neuropsychological testing, and self-reported (Geriatric Depression Scale - 30 item [GDS-30]) and informant-reported interview (Neuropsychiatric Inventory Questionnaire [NPI-Q]) of NPS. Cerebral Aβ burden was quantified using centiloids (CL). NPI-Q and GDS-30 queried the presence of NPS within 4 subdomains and 6 subscales, respectively. Regression models examined the relationship between NPS and Aβ-PET CL.

Results: Both higher self- and informant-reported NPS were associated with higher Aβ burden. Among specific NPI-Q subdomains, informant-reported changes in depression, anxiety, and irritability were all associated with higher Aβ-PET. Similarly, self-reported (GDS-30) subscales of depression, apathy, anxiety, and cognitive concern were associated with higher Aβ-PET. When simultaneously entered, only self-reported cognitive concern was associated with Aβ-PET in the GDS-30 model, while both informant-reported anxiety and depression were associated with Aβ-PET in the NPI-Q model. Clinical status moderated the association between self-reported NPS and Aβ-PET such that the positive relationship between self-perceived NPS and Aβ burden strengthened with increasing functional difficulties.

Conclusions: In a cohort of older adults without dementia, both self- and informant-reported measures of global NPS, particularly patient-reported cognitive concerns and informant-reported anxiety and depression, corresponded with cerebral Aβ burden. NPS may appear early in the prodromal disease state and relate to initial AD proteinopathy burden, a relationship further exaggerated in those with greater clinical severity.

Introduction: Cerebral amyloid angiopathy (CAA) is characterized by amyloid β (Aβ) deposition in brain vessels, leading to hemorrhagic phenomena and cognitive impairment. Magnetic resonance imaging (MRI)-based criteria allow a diagnosis of probable CAA in vivo, but such a diagnosis cannot predict the eventual development of CAA.

Methods: We conducted a retrospective cohort study of 464 patients with cognitive disorders whose data were included in a brain health biobank. De-identified parameters including sex, age, cognitive score, APOE status, and cerebrospinal fluid (CSF) levels of Aβ 1-40, Aβ 1-42, phosphorylated tau, and total tau were assessed in those with and without CAA. Odds ratios (ORs) and 95% confidence intervals (CIs) were determined.

Results: CAA was present in 53 of 464 (11.5%) patients. P-tau level was significantly higher in those with CAA (115 vs. 84.3 pg/mL p = 0.038). In univariate analyses, the risk of developing CAA was higher with increased age (OR, 1.036; 95% CI: 1.008, 1.064; p = 0.011) and decreased CSF level of Aβ 1-40 (OR, 0.685; 95% CI: 0.534, 0.878; p = 0.003). In multivariate analyses, the risk of CAA remained higher with a decreased CSF level of Aβ 1-40 (OR, 0.681; 95% CI: 0.531, 0.874; p = 0.003).

Conclusion: These findings suggest that Aβ 1-40 levels in the CSF might be a useful molecular biomarker of CAA in patients with dementia.

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: 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: 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: Antipsychotics are still commonly prescribed to patients with dementia, despite the many issues that have been identified. This study aimed to quantify antipsychotic prescription in patients with dementia and the types of concomitant medications prescribed with antipsychotics.

Methods: A total of 1,512 outpatients with dementia who visited our department between April 1, 2013 and March 31, 2021, were included in this study. Demographic data, dementia subtypes, and regular medication use at the time of the first outpatient visit were investigated. The association between antipsychotic prescriptions and referral sources, dementia subtypes, antidementia drug use, polypharmacy, and prescription of potentially inappropriate medications (PIMs) was evaluated.

Results: The antipsychotic prescription rate for patients with dementia was 11.5%. In a comparison of dementia subtypes, the antipsychotic prescription rate was significantly higher for patients with dementia with Lewy bodies (DLB) than for those with all other dementia subtypes. In terms of concomitant medications, patients taking antidementia drugs, polypharmacy, and PIMs were more likely to receive antipsychotic prescriptions than those who were not taking these medications. Multivariate logistic regression analysis showed that referrals from psychiatric institutions, DLB, N-methyl-d-aspartate (NMDA) receptor antagonists, polypharmacy, and benzodiazepine were associated with antipsychotic prescriptions.

Conclusions: Referrals from psychiatric institutions, DLB, NMDA receptor antagonist, polypharmacy, and benzodiazepine were associated with antipsychotic prescriptions for patients with dementia. To optimise prescription of antipsychotics, it is necessary to improve cooperation between local and specialised medical institutions for accurate diagnosis, evaluate the effects of concomitant medication administration, and solve the prescribing cascade.

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.