Explore the vast range of titles available.

The serotonin-receptor modulator pimavanserin reduces psychosis in patients with Parkinson’s disease. In a randomized discontinuation trial involving patients with psychosis related to several types of dementia, the frequency of relapse over a period of 26 weeks was 13% with pimavanserin and 28% with placebo.

This study examines the associations between baseline risk factors and future cognitive decline in individuals with and without elevated brain amyloid. Furthermore, the study investigates whether predictors of cognitive impairment differ based on amyloid status. Among 1144 Participants from the A4 Study who attended the 4.5-year visit (visit 66), 1133 with available Clinical Dementia Rating (CDR) data were included in the analysis. Baseline predictors assessed at visit 1 included age, sex, education, APOE genotype, amyloid-β (Aβ) standard uptake value ratio (SUVR), Preclinical Alzheimer's Cognitive Composite (PACC) score, Geriatric Depression Scale (GDS) score, and State-Trait Anxiety Inventory (STAI) score. Logistic regression models were used to evaluate the impact of these predictors on future cognitive impairment (CDR>0 at visit 66) in Aβ-positive (Aβ+) and Aβ-negative (Aβ-) participants. Additionally, baseline GDS total and item scores were compared between those who developed cognitive impairment and those who remained cognitively unimpaired. Among 1133 participants (825 Aβ+ and 308 Aβ-), 282 (34.2%) Aβ+ and 51 (16.6%) Aβ- participants developed cognitive impairment over 4.5 years. Common predictors of cognitive impairment in both Aβ+ and Aβ- groups included older age, male sex, and lower PACC scores. Aβ SUVR was the strongest predictor of cognitive impairment in Aβ+ individuals, increasing the risk 15-fold (OR=15.34, p <0.001), while its effect was not statistically significant in Aβ- participants (OR=3.04, p = 0.703). Similarly, baseline STAI scores were significantly associated with cognitive decline in the Aβ+ group (OR=1.07, p = 0.005) but not in the Aβ- group (OR=1.01, p = 0.882). Higher baseline GDS scores were significantly associated with cognitive impairment in both groups (Aβ+: OR=1.16, p =  0.008; Aβ-: OR=1.27, p = 0.012). However, item-level analysis revealed distinct patterns: in Aβ+ individuals, memory concerns showed the strongest association with future cognitive decline (p <0.001), whereas in Aβ- individuals, low energy levels were the most predictive symptom (p = 0.013). While common risk factors are associated with cognitive impairment regardless of amyloid status, some predictors and their presentations vary between Aβ+ and Aβ- individuals, suggesting distinct underlying mechanisms of cognitive decline.

Alterations to spatial navigation have been suggested by previous studies to represent an early cognitive marker for those with and at risk of Alzheimer's Disease (AD). However, with most of these studies focusing on spatial memory (usage of formed spatial representations), very little is known about the extent to which spatial exploration (process by which spatial representations are formed) may be altered in AD. The aim of this study is to investigate how spatial exploration behavior may be altered in individuals with and at risk of AD, and the extent to which individuals can be classified into their clinical status based on their exploration behavior. 10 cognitively unimpaired older adults, 10 adults with mild cognitive impairment (MCI), and 10 adults with clinical AD are recruited (all participants aged > 50 years). All participants undergo a Virtual Supermarket Learning Task using immersive walking virtual reality to measure their exploration behavior and spatial memory. In the exploration phase, participants freely explore a 13×6-meter virtual supermarket for 7 minutes and learn the locations of 6 floating target objects. Here, various exploration behaviors (distance travelled, turning angles, object visits, etc.) are measured. In the wayfinding phase, participants are instructed to navigate from one target object to another, without feedback, and wayfinding success (proportion of correct trials) is measured. In the pointing phase, participants are instructed to point from one target object to another, without feedback, and angular error (deviation from correct location) is measured. Performance of the AD and MCI groups in all task phases are compared to that of the healthy controls to assess alterations to exploration behavior as well as wayfinding and pointing performance. Furthermore, we assess how well we can classify the AD and MCI groups from controls using their exploration behavior, and compare this with the classification accuracy obtained from using their wayfinding/pointing performance. The study results will highlight the extent to which spatial exploration behavior can be considered a novel and sensitive cognitive marker for AD, having important implications for understanding early cognitive changes in AD and potentially identifying candidates for therapeutic intervention.

Abstract Objective Emotional awareness and expression therapy (EAET) emphasizes the importance of the central nervous system and emotional processing in the etiology and treatment of chronic pain. Prior trials suggest EAET can substantially reduce pain; however, only one has compared EAET with an established alternative, demonstrating some small advantages over cognitive behavioral therapy (CBT) for fibromyalgia. The current trial compared EAET with CBT in older, predominately male, ethnically diverse veterans with chronic musculoskeletal pain. Design Randomized comparison trial. Setting Outpatient clinics at the West Los Angeles VA Medical Center. Subjects Fifty-three veterans (mean age = 73.5 years, 92.4% male) with chronic musculoskeletal pain. Methods Patients were randomized to EAET or CBT, each delivered as one 90-minute individual session and eight 90-minute group sessions. Pain severity (primary outcome), pain interference, anxiety, and other secondary outcomes were assessed at baseline, post-treatment, and three-month follow-up. Results EAET produced significantly lower pain severity than CBT at post-treatment and follow-up; differences were large (partial η2 = 0.129 and 0.157, respectively). At post-treatment, 41.7% of EAET patients had >30% pain reduction, one-third had >50%, and 12.5% had >70%. Only one CBT patient achieved at least 30% pain reduction. Secondary outcomes demonstrated small to medium effect size advantages of EAET over CBT, although only post-treatment anxiety reached statistical significance. Conclusions This trial, although preliminary, supports prior research suggesting that EAET may be a treatment of choice for many patients with chronic musculoskeletal pain. Psychotherapy may achieve substantial pain reduction if pain neuroscience principles are emphasized and avoided emotions are processed.

Neuropsychiatric symptoms (NPS) are highly prevalent in older adults. While the association between NPS and cognitive decline in older adults is widely acknowledged, there remains a lack of specificity regarding emerging NPS and cognitive outcomes in cognitively unimpaired older individuals. Our study assessed the incidence of NPS development, its link to cognitive decline, and other factors associated with development of MCI among cognitively unimpaired older adults without NPS at baseline. Utilizing data from the UCI ADRC cohort, we included cognitively unimpaired participants without neuropsychiatric symptoms at baseline, followed longitudinally for at least 5 years. Comprehensive clinical assessments and expert diagnostic classifications occurred annually. NPS were evaluated using the Neuropsychiatric Inventory (NPI), the Mild Behavioral Impairment Checklist (MBI-C), and the Geriatric Depression Scale (GDS). Demographic characteristics, cognitive test scores, ApoE genotype, CSF pTau181 level, and progression to MCI were compared between NPS developers and non-developers. Logistic regression analysis, with progression to MCI as a dependent variable, was employed to explore factors influencing the likelihood of cognitive decline. Participants were followed for an average of 8.4 years. The rate of NPS development was 32.4%, and 13.1% of participants progressed to MCI. There was no significant difference in demographic characteristics, baseline cognitive test scores, or biological markers between NPS developers and non-developers. NPS developers exhibited a significantly higher rate of progression to MCI compared to non-developers (24.6% vs. 7.6%, p = 0.002). In logistic regression analysis to predict progression to MCI, NPS development emerged as the most significant factor (OR = 5.209, p<0.001), followed by high CSF pTau181 level (OR = 1.122, p = 0.012), ApoE4 carrier status (OR = 2.928, p = 0.027), and low 5-minute recognition score on the CERAD Word List Test (OR = 0.405, p = 0.029). These findings underscore the importance of assessing cognitive change in cognitively unimpaired older adults with recent-onset NPS. Additionally, they indicate the potential benefits of combining NPS assessments with biological markers and cognitive test scores to predict those at risk of cognitive decline. These results further support the role of NPS in the pathophysiology of cognitive decline.

In a study of patients with Alzheimer's disease and associated psychosis or agitation that had responded to risperidone, the risk of relapse was greater among patients randomly assigned to switch to placebo than among those who continued to receive risperidone. Symptoms of psychosis or agitation are common in Alzheimer's disease. 1 , 2 These symptoms are associated with distress on the part of the patient, an increased burden on caregivers, more rapid cognitive decline, an increased likelihood of institutionalization, and increased health care costs. 3 Nonpharmacologic behavioral treatment approaches may help, 4 – 9 but large, controlled trials are needed to confirm the effectiveness of these strategies. Among psychotropic medications, only antipsychotic agents show superiority over placebo for the treatment of psychosis and agitation–aggression in patients with dementia, although they are associated with only low-to-moderate efficacy. 10 – 12 Side effects of antipsychotic drugs include sedation, extrapyramidal . . .

Background Cholinergic neurotransmitter system dysfunction contributes to cognitive impairment in Alzheimer’s disease and other syndromes. However, the specific cholinergic mechanisms and brain structures involved, time course of alterations, and relationships with specific cognitive deficits are not well understood. Methods This study included 102 older adults: 42 cognitively unimpaired (CU), 28 with mild cognitive impairment (MCI), and 32 with Alzheimer’s disease (AD) dementia. Each participant underwent a neuropsychological assessment. Regional brain α4β2 nicotinic cholinergic receptor binding ( V T / fp ) was measured using 2-[ 18 F]fluoro-3-(2(S)azetidinylmethoxy)pyridine (2FA) and PET imaging. Voxel-wise analyses of group differences were performed. Relationships between receptor binding and cognition, age, and cholinesterase inhibitor medication use were assessed using binding values in six prespecified regions of interest. Results SPM analysis showed the group V T / f p binding differences in the bilateral entorhinal cortex, hippocampus, insula, anterior cingulate, thalamus, and basal ganglia ( p  < .05, FWE-corrected). Pairwise comparisons revealed lower binding in the AD group compared to the CU group in similar regions. Binding in the entorhinal cortex was lower in the MCI group than in the CU group; binding in the hippocampus was lower in the AD group than in the MCI group. AD participants taking cholinesterase inhibitor medication had lower 2FA binding in the bilateral hippocampus and thalamus compared to those not taking medication. In the CU group, age was negatively associated with 2FA binding in each region of interest ( r s  = − .33 to − .59, p  < .05 for each, uncorrected). Attention, immediate recall, and delayed recall scores were inversely associated with 2FA binding in most regions across the full sample. In the combined group of CU and MCI participants, attention was inversely associated with 2FA binding in most regions, beyond the effect of hippocampal volume. Conclusions Nicotinic cholinergic receptor binding in specific limbic and subcortical regions is lower in MCI and further reduced in AD dementia, compared to CU older adults, and is related to cognitive deficits. Cognitive decline with age may be a consequence of reduced cholinergic receptor density or binding affinity that may also promote vulnerability to other Alzheimer’s processes. Contemporary modification of the “cholinergic deficit” of aging and AD may reveal opportunities to prevent or improve clinical symptoms.

Although nearly one-third of older diabetics are cognitively impaired, their diabetes management remains poorly understood. To examine the relationship between cognitive impairment and diabetes self-management in a population-based community sample of older adults with Type 2 diabetes. Cross-sectional observational analysis. 1,398 persons with diabetes, aged 60 years or older, who responded to the 2003 Health and Retirement Study Diabetes Survey. We conducted logistic regressions on the effects of cognitive impairment on respondents’ self-management ability after controlling for diabetes comorbidities, demographics, and clinical characteristics. Participants with greater cognitive impairment were less likely to adhere to exercise (Adjusted Odds ratio [ AOR ] = 0.725 and 0.712 for moderate and severe cognitive impairment, both P  < 0.05), and to diet (AOR = 0.906 and 0.618 for moderate and severe cognitive impairment, both P  < 0.01). Cognitive impairment is associated with worse self-care and may pose challenges to diabetic older persons, notably in diet and exercise. Cognitive screening may be indicated in this high risk group.

There is a crucial need for accessible and scalable methods of diagnosis for cognitive impairment and Alzheimer's disease. Our proposed deep learning-based approach uses participants' speech samples to compare acoustic and linguistic features to recognize early-stage cognitive decline. Participants of the Alzheimer's Disease Research Center (ADRC) at the University of California, Irvine, provided speech samples, which were processed and denoised to isolate participants' speech. Of 162 audio samples (81 Picture Descriptions and 81 Spontaneous Speech), 80% were used for model training, 10% for validation, and 10% for testing; participants within each dataset were unique. We employed a Bidirectional Long Short-term Memory (BiLSTM) model to capture patterns from both past and future data sequences. The model was applied independently for each feature set, one trained on acoustic features of speech and the other on linguistic features (Figure 1). The acoustic features consisted of Mel-Frequency Cepstral Coefficients (MFCCs), Spectral Centroid, and Spectral Contrast, capturing the energy and quality of the speech audio; the linguistic features, extracted from transcriptions of participant speech samples, included vocabulary richness, average word length, sentiment score, and grammatical errors. Before input into their respective models, acoustic and linguistic features were transformed into 1D representations with 2-fold cross-validation to avoid overfitting. We ran the model to identify cognitive diagnosis as the outcome. Accuracy indicates the correctness of classification between mild cognitive impairment (MCI) and unimpaired cognition (UC) participants, while F1 score indicates overall model performance. The study included 81 native English-speaking participants (Table 1). 19 participants had MCI, and 62 participants had UC. Our proposed BiLSTM model achieved 87.50% accuracy with a 93.33% F1 score using acoustic features, and 81.25% accuracy with an 88.89% F1 score using linguistic features (Table 2). Our BiLSTM model outperformed machine learning and LSTM models in linguistic and acoustic features. Our results show that our proposed BiLSTM architecture outperforms machine learning and deep learning models, and that acoustic speech features are better predictors of cognitive impairment than linguistic features. The proposed model has the potential to improve the clinical diagnosis of cognitive impairment in an easy and scalable fashion.