Dementia and Geriatric Cognitive Disorders最新文献

Introduction: Studies suggest a role of vitamin D in the progression and symptomatology of Alzheimer's disease (AD), with few in vitro studies pointing to effects on serotonergic and amyloidogenic turnover. However, limited data exist in AD patients on the potential association with cognition and behavioral and psychological signs and symptoms of dementia (BPSD). In this retrospective cross-sectional study, we, therefore, explored potential correlations of serum 25-hydroxyvitamin D3 (25(OH)D3) concentrations, indicative of vitamin D status, with serum serotonin (5-hydroxytryptamine, 5-HT) levels, cognitive/BPSD scorings, and cerebrospinal fluid (CSF) biomarker levels.

Methods: Frozen serum samples of 25 well-characterized AD subjects as part of a previous BPSD cohort were analyzed, of which 15 had a neuropathologically confirmed diagnosis. Serum 25(OH)D3 levels were analyzed by means of LC-MS/MS, whereas 5-HT concentrations were quantified by competitive ELISA.

Results: Among AD patients, vitamin D deficiency was highly prevalent, defined as levels below 50 nmol/L. Regression analyses, adjusted for age, gender, and psychotropic medications, revealed that serum 25(OH)D3 and 5-HT levels were positively associated (p = 0.012). Furthermore, serum 25(OH)D3 concentrations correlated inversely with CSF amyloid-beta (Aβ1-42) levels (p = 0.006), and serum 5-HT levels correlated positively with aggressiveness (p = 0.001), frontal behavior (p = 0.001), depression (p = 0.004), and partly with cognitive performance (p < 0.005). Lastly, AD patients on cholinesterase inhibitors had higher serum 25(OH)D3 (p = 0.030) and lower serum 5-HT (p = 0.012) levels.

Conclusions: The molecular associations between low vitamin D status, serum 5-HT, and CSF Aβ1-42 levels are highly remarkable, warranting further mechanistic and intervention studies to disclose potential involvement in the clinico-biobehavioral pathophysiology of AD.

Introduction: As the population ages, the prevalence of cognitive impairment is expanding. Given the recent pandemic, there is a need for remote testing modalities to assess cognitive deficits in individuals with neurological disorders. Self-administered, remote, tablet-based cognitive assessments would be clinically valuable if they can detect and classify cognitive deficits as effectively as traditional in-person neuropsychological testing.

Methods: We tested whether the Miro application, a tablet-based neurocognitive platform, measured the same cognitive domains as traditional pencil-and-paper neuropsychological tests. Seventy-nine patients were recruited and then randomized to either undergo pencil-and-paper or tablet testing first. Twenty-nine age-matched healthy controls completed the tablet-based assessments. We identified Pearson correlations between Miro tablet-based modules and corresponding neuropsychological tests in patients and compared scores of patients with neurological disorders with those of healthy controls using t tests.

Results: Statistically significant Pearson correlations between the neuropsychological tests and their tablet equivalents were found for all domains with moderate (r > 0.3) or strong (r > 0.7) correlations in 16 of 17 tests (p < 0.05). All tablet-based subtests differentiated healthy controls from neurologically impaired patients by t tests except for the spatial span forward and finger tapping modules. Participants reported enjoyment of the tablet-based testing, denied that it provoked anxiety, and noted no preference between modalities.

Conclusions: This tablet-based application was found to be widely acceptable to participants. This study supports the validity of these tablet-based assessments in the differentiation of healthy controls from patients with neurocognitive deficits in a variety of cognitive domains and across multiple neurological disease etiologies.

Introduction: Lewy body disease (LBD) is the second most common neurodegenerative disorder in patients older than 65 years. LBD is characterized by heterogeneous symptoms like fluctuation in attention, visual hallucinations, Parkinsonism, and REM sleep behaviour disorders. Considering the relevant social impact of the disease, identifying effective non-pharmacological treatments is becoming a priority. The aim of this systematic review was to provide an up-to-date literature review of the most effective non-pharmacological treatments in patients with LBD, focussing on evidence-based interventions.

Methods: Following PRISMA criteria, we carried out a systematic search through three databases (PubMed, Cochrane Libraries, and PEDro) including physical therapy (PT), cognitive rehabilitation (CR), light therapy (LT), transcranial direct current stimulation (tDCS), transcranial magnetic stimulation (TMS), electroconvulsive therapy (ECT), deep brain stimulation (DBS). All studies were qualitatively assessed using standardized tools (CARE and EPHPP).

Results: We obtained a total of 1,220 studies of which 23 original articles met eligibility criteria for inclusion. The total number of LBD patients included was 231; mean age was 69.98, predominantly men (68%). Some PT studies highlighted improvements in motor deficits. CR produced significant improvements in mood, cognition, and patient's quality of life and satisfaction. LT outlined a partial trend of improvements in mood and sleep quality. DBS, ECT, and TMS showed some partial improvements mainly on neuropsychiatric symptoms, whereas tDCS provided partial improvements in attention.

Conclusion: This review highlights the efficacy of some evidence-based rehabilitation studies in LBD; however, further randomized controlled trials with larger samples are needed to provide definitive recommendations.

Introduction: We examined the relationship between previous fluctuations in Mini-Mental State Examination (MMSE) scores, future changes in MMSE scores, and attrition from follow-up surveys, which helps in a more comprehensive interpretation of repeatedly collected MMSE scores.

Methods: This 4-year longitudinal study included 2,073 community-dwelling older adults aged ≥65 years in Japan. The MMSE was administered at baseline (T0), 2 years (T1), and 4 years (T2) follow-up. We performed multinomial logistic regression analysis with the dependent variable, indicating the change in MMSE score from T1 to T2 (categorized as increase, no change [reference category], and decrease) and attrition at T2. The independent variables included the change in MMSE scores from T0 to T1 and MMSE scores at T0 and T1.

Results: The mean MMSE score was 29 across the three time points. A one-point decrease in MMSE score from T0 to T1 was associated with 79% (95% confidence interval: 1.62, 1.97) higher odds of an increase in MMSE score from T1 to T2 and 28% (1.17, 1.40) higher odds of attrition at T2. A one-point decrement in the MMSE score at T0 and T1 was also associated with an increase in the MMSE score from T1 to T2 and attrition at T2.

Conclusion: Focusing on cognitive fluctuation for 2 years, rather than cognitive function at a point in time, would have no remarkable advantage when focusing on future cognitive function and attrition. Our results emphasize the need for further studies to identify factors that distinguish between those who continue to attend follow-up surveys and show improvements in cognitive test scores and those who drop out.

Introduction: Alzheimer's disease (AD) is the most prevalent type of dementia and can cause abnormal cognitive function and progressive loss of essential life skills. Early screening is thus necessary for the prevention and intervention of AD. Speech dysfunction is an early onset symptom of AD patients. Recent studies have demonstrated the promise of automated acoustic assessment using acoustic or linguistic features extracted from speech. However, most previous studies have relied on manual transcription of text to extract linguistic features, which weakens the efficiency of automated assessment. The present study thus investigates the effectiveness of automatic speech recognition (ASR) in building an end-to-end automated speech analysis model for AD detection.

Methods: We implemented three publicly available ASR engines and compared the classification performance using the ADReSS-IS2020 dataset. Besides, the SHapley Additive exPlanations algorithm was then used to identify critical features that contributed most to model performance.

Results: Three automatic transcription tools obtained mean word error rate texts of 32%, 43%, and 40%, respectively. These automated texts achieved similar or even better results than manual texts in model performance for detecting dementia, achieving classification accuracies of 89.58%, 83.33%, and 81.25%, respectively.

Conclusion: Our best model, using ensemble learning, is comparable to the state-of-the-art manual transcription-based methods, suggesting the possibility of an end-to-end medical assistance system for AD detection with ASR engines. Moreover, the critical linguistic features might provide insight into further studies on the mechanism of AD.

Introduction: A rapidly increasing number of patients with dementia present a serious social problem. Recently, the incidence of epilepsy in patients with Alzheimer's disease (AD) is increasing, drawing attention to the pathological relationship between the two conditions. Clinical studies have suggested the protective action of antiepileptic agents on dementia; however, the underlying mechanism remains unknown. We evaluated the effects of multiple antiepileptic drugs using tau aggregation assay systems to determine the effects of antiepileptic agents on tau aggregation, a major neuropathological finding associated with AD.

Methods: We evaluated the effects of seven antiepileptic agents on intracellular tau aggregation using a tau-biosensor cell-based high-throughput assay. Next, we tested these agents in a cell-free tau aggregation assay using thioflavin T (ThT).

Results: The assay results revealed that phenobarbital inhibited tau aggregation, whereas sodium valproate, gabapentin, and piracetam promoted tau aggregation. In the cell-free tau aggregation assay using ThT, we confirmed that phenobarbital significantly inhibited tau aggregation.

Conclusion: Antiepileptic drugs may modify the tau pathology in AD in a neural activity-independent manner. Our finding may provide an important insight into the optimization of antiepileptic drug therapy in older adults with dementia.

Introduction: Visual and spatial perception (VSP) are cognitive domains frequently assessed in the screening and neuropsychological assessment of dementia. Evidence suggests that VSP impairment is common in the early stages of Alzheimer's disease (AD). Despite this evidence, the ability of VSP tests to discriminate between healthy older adults and people with AD remains mixed. The purpose of this literature review was to employ a systematic search strategy to identify empirical evidence supporting the diagnostic utility of VSP tests which may be used in the screening and diagnosis of AD.

Methods: Specified criteria were used to perform a systematic literature search of the PsycINFO and PubMed databases with no date restrictions. Relevant data from the selected studies were extracted, and a published appraisal tool (the Quality Assessment of Diagnostic Accuracy Studies-2) was used to evaluate methodological quality.

Results: Of the 144 articles returned, six studies and 11 VSP tests met review inclusion criteria. Four tests demonstrated both sensitivity and specificity values above 80%. A computerised 3D Visual Task demonstrated the highest sensitivity and specificity values (90% and 95%, respectively). The quality of the identified studies was considered to be satisfactory. Identified limitations and the implications of issues relating to study methodology are discussed, and recommendations for future research are suggested.

Conclusion: The evidence from this review suggests that certain tests of VSP may be a useful addition to the routine screening of AD.