Search Results (22)

Background: Late-onset depression (LOD) has been increasingly recognized as a risk factor for dementia, yet the temporal and causal nature of this relationship remains unclear. Objective: The purpose of this review is to investigate the temporal association between LOD and dementia. Methods: A comprehensive search for studies examining the temporal relationship between LOD and dementia was conducted using MEDLINE via Ovid. The end date of the search was 9 September 2024. A total of 3450 studies were identified, of which 27 met the inclusion criteria. This review was conducted in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines and an article quality assessment was completed. Results: The review demonstrated a significant temporal association between LOD and the risk of dementia, with the highest risk observed within the first decade following depression onset. LOD was consistently associated with an increased likelihood of developing dementia, particularly Alzheimer’s disease, compared to depression at earlier life stages. Conclusions: This systematic review highlights the significant association between LOD and dementia risk, emphasizing the need for early recognition and intervention. Future research should investigate the age at which LOD becomes a risk factor for dementia, the relationship between depression severity, family history of dementia, and dementia risk, as well as the efficacy of preventative treatments. Full article

Background/Objectives: Dementia involves the loss of cognitive abilities and impairs functional abilities in daily life. In motor imagery (MI) techniques, motor acts are mentally rehearsed without any overt body movements. The purpose of the randomized controlled trial was to examine the effects of MI on the motor function of older adults with dementia. Methods: Overall, 160 participants (43 men, 117 women, MMSE M = 23.20, SD = 0.15) from an Athens Day Care Center of the Alzheimer Association were randomized to (a) the MI and exercise group (experimental group) (n = 55), (b) the only exercise group (1st control group) (n = 52) and (c) the neither MI nor exercise group (2nd control group) (n = 53). The exercise session comprised 24 physiotherapy exercise sessions, lasting 45 min each, twice a week for 12 weeks. The exercises were selected from the Otago Exercise Program. Three assessments were performed: (a) one week prior to the program, (b) at one and a half months and (c) after the program. The experimental group performed a 30-minute MI with exercise program content after the end of every physiotherapy exercise session. The Multidirectional Reach Test, Five Times Sit-to-Stand Test (FTSST), Timed Up and Go test (TUG), Functional Gait Assessment (FGA) and Berg Balance Scale (BBS) were used to assess participants’ balance and functional status. Results: In the intention to treat analysis (18 participants dropped out), the 3 × 3 repeated measures ANOVA indicated statistically significant results between the three groups on (a) the TUG (F = 3.06, df (2), p = 0.04), (b) the FTSST (F = 3.00, df (2), p = 0.05), (c) the forward direction test (F = 4.14 df (2), p = 0.02), the lateral right and the lateral left direction tests (F = 3.90, df (2), p = 0.02 and F = 7.87, df (2), p = 0.00, respectively), and (d) the FGA (F = 4.35, df (2), p = 0.01). The Friedman test showed significant statistical significant differences among the three groups for BBS (X² = 7.62, df = 2, p = 0.22), and an effect size of partial η² coefficient for F-tests was found. Post hoc comparisons using a Bonferroni test for ANOVA and Wilcoxon test for Friedman indicated that the mean scores for the experimental group and the 1st control were significantly better than the 2rd control group in many dependent variables. Conclusions: The study showed a positive effect of MI on balance and the functional status of older adults with early stages of dementia with possible beneficial effects on maintaining independence and reducing physical decline. Full article

Neurodegenerative diseases severely impact the life of millions of patients worldwide, and their occurrence is more and more increasing proportionally to longer life expectancy. Electroencephalography has become an important diagnostic tool for these diseases, due to its relatively simple procedure, but it requires analyzing a large number of data, often carrying a small fraction of informative content. For this reason, machine learning tools have gained a considerable relevance as an aid to classify potential signs of a specific disease, especially in its early stages, when treatments can be more effective. In this work, long short-term memory-based neural networks with different numbers of units were properly designed and trained after accurate data pre-processing, in order to perform a multi-class detection. To this end, a custom dataset of EEG recordings from subjects affected by five neurodegenerative diseases (Alzheimer’s disease, frontotemporal dementia, dementia with Lewy bodies, progressive supranuclear palsy, and vascular dementia) was acquired. Experimental results show that an accuracy up to 98% was achieved with data belonging to different classes of disease, up to six including the control group, while not requiring particularly heavy computational resources. Full article

Background: Chronic kidney disease (CKD) is a risk factor for cognitive impairment (CI), and this risk is the highest in patients with end-stage kidney disease (ESKD). As a multifactorial disease, CI may be influenced by several potentially modifiable lifestyle and behavioral factors that may reduce or increase the risk of dementia. The aim of this study was to evaluate the associations between the known modifiable risk factors for dementia and the risk of CI in patients with ESKD treated with renal replacement therapy. The Charlson Comorbidity Index and the risk of CI in patients with ESKD were also assessed. Methods: In this cross-sectional study, 225 consecutive patients with ESKD treated with different modalities of renal replacement therapy were assessed for cognitive decline using the Addenbrooke’s Cognitive Examination (ACE III) test. Information was also collected on modifiable risk factors for dementia, medical history and demographics. Results: This study included 117 patients after kidney transplantation (KT) and 108 patients with ESKD undergoing peritoneal dialysis and hemodialysis. The prevalence of modifiable risk factors for dementia differed between the groups; KT patients were more likely to be physically active, residing in cities with populations of less than 500,000 inhabitants, and were less likely to suffer from depression. Furthermore, the KT group had a lower Charlson Comorbidity Index score, indicating less severe comorbidities, and a lower risk of CI (3.6 ± 1.67 vs. 5.43 ± 2.37; p = 0.001). In both the KT and dialysis groups, patients with CI were more likely to have a sedentary lifestyle (45% vs. 9%, p = 0.001 and 88% vs. 48%, p = 0.001, respectively), whereas lower educational attainment and depression had a significant negative impact on ACE III test results, but only in KT patients. Finally, cognitive function in dialysis patients was negatively affected by social isolation and living in urban areas. Conclusions: Modifiable risk factors for dementia, particularly a sedentary lifestyle, are associated with a higher risk of CI in patients treated with different renal replacement therapy modalities. As CI is an irreversible condition, it is important to identify lifestyle-related factors that may lead to dementia in order to improve or maintain cognitive function in patients with ESKD. Full article

Background: Dementia involves the loss of cognitive abilities and represents a decline from the prior level of function, which impairs functional abilities in day-to-day life. The purpose of the present study is to examine the effectiveness of an exercise program on the muscle strength and range of motion of the upper limbs, the functional status, and the depression of elderly people with early stage dementia. Methods: The sample consisted of 60 elderly people with early stage dementia who were randomly divided into a control and an experimental group of 30 participants each. The experimental group received a 12-week Otago exercise program with 45 min duration of each session. The control group received usual care without doing exercise. The outcome measures of muscle strength and range of motion of the upper limbs, the functional status, and the depression were assessed by valid instruments and tests at the beginning and at the end of the intervention program. Repeated measures one-way ANOVA and Mann–Whitney tests examined the differences between the two groups at the end of the 12-week exercise program. Results: Statistically significant differences were found between the experimental and control groups in the entire outcome measures (functional ability F = 9.35 p < 0.05; muscle strength right hand F = 32.33, p < 0.05 left hand U = 95.50 p < 0.01; e.g., range of motion shoulder extension U = 104.00 p < 0.01), except depression. Conclusions: Both muscle strength and range of motion of the upper limbs, as well as the functional ability, were improved by the exercise program. Further research is needed to investigate the present results, in particular to explore the long-term cognitive, behavioral, and functional status outcomes of exercise in the early stages of dementia. Full article

The SUNshiners group includes people in the early stages of dementia with an interest in dementia activism and research. The group found that despite the growing awareness of invisible disabilities, there is very limited research into the pros and cons of the invisibility of dementia. Our paper explores the SUNshiners research which stemmed from varied individual experiences of disclosing diagnoses. The group designed and developed a short survey to explore what the public knew about dementia and what they thought about the invisibility of dementia. A mixture of open- and closed-ended questions were used to gain meaningful data. A total of 347 people completed the survey (315 online and 32 paper-based), which was then co-analysed. The findings suggest that the majority of the public felt that the invisibility of dementia was negative; that knowing someone had dementia when first meeting them would be beneficial; that people living with dementia should maintain the right to vote; and that people living with dementia do not automatically require a consistent, regular carer. Common themes from the open-ended answers included capacity, severity of dementia, and access to support. The findings support the disclosure of dementia diagnosis; however, more action is needed to tackle stigmatised views, particularly as the SUNshiners felt that people do not have enough dementia education to support a positive disclosure experience. They shared their experiences of the group and the project’s benefits, but also the losses they have faced. Our paper aims to be as accessible as possible. Full article

Background: For hip fracture patients with a limited life expectancy, operative and palliative non-operative management (P-NOM) can yield similar quality of life outcomes. However, evidence on when to abstain from surgery is lacking. The aim of this study was to quantify the influence of patient characteristics on surgeons’ decisions to recommend P-NOM. Methods: Dutch surgical residents and orthopaedic trauma surgeons were enrolled in a conjoint analysis and structured expert judgement (SEJ). The participants assessed 16 patient cases comprising 10 clinically relevant characteristics. For each case, they recommended either surgery or P-NOM and estimated the 30-day postoperative mortality risk. Treatment recommendations were analysed using Bayesian logistic regression, and perceived risks were pooled with equal and performance-based weights using Cooke’s Classical Model. Results: The conjoint analysis and SEJ were completed by 14 and 9 participants, respectively. Participants were more likely to recommend P-NOM to patients with metastatic carcinomas (OR: 4.42, CrI: 2.14–8.95), severe heart failure (OR: 4.05, CrI: 1.89–8.29), end-stage renal failure (OR: 3.54, CrI: 1.76–7.35) and dementia (OR: 3.35, CrI: 1.70–7.06). The patient receiving the most P-NOM recommendations (12/14) had a pooled perceived risk of 30-day mortality between 50.8 and 62.7%. Conclusions: Overall, comorbidities had the strongest influence on participants’ decisions to recommend P-NOM. Nevertheless, practice variation and heterogeneity in risk perceptions were substantial. Hence, more decision support for considering P-NOM is needed. Full article

Junk foods are typically low in essential nutrients, such as vitamins, minerals, and antioxidants. They are also loaded with trans fats and saturated fats, which can increase the level of triglycerides in the blood. High triglyceride levels can contribute to the development of non-alcoholic fatty liver disease (NAFLD), a condition where excess fat accumulates in the liver. A high intake of junk foods can lead to insulin resistance, a condition where the body’s cells become less responsive to insulin. A diet lacking in nutrients and loaded with unwanted toxins can impair the liver’s ability to detoxify harmful substances and damage its overall function. It is known that the regular consumption of junk food can be linked to memory impairment and cognitive decline. Several studies have shown that diets high in unhealthy fats, sugars, and processed foods can negatively impact brain health, including memory function. In this study, Wistar rats were used to model Late-Onset Alzheimer’s Disease (LOAD), which was inspired by knowledge of the liver–brain axis’s role in causing dementia. The model mimicked junk-food-induced liver–brain damage, and was developed by using the toxins d-galactosamine, ethanol and d-galactose. To begin with, the model rats demonstrated insulin resistance, a characteristic of LOAD patients. Glucose levels in both the brain and liver tissues were significantly elevated in the model, paralleling clinical findings in LOAD patients. High glucose levels in the brain lead to the increased production of advanced glycation end-products (AGEs), which, along with amyloid beta, harm neighbouring neurons. Histopathological analysis revealed deformed glial nodules, apoptotic neurons, and amyloid plaques in the brain section in the later stages of the disease. Simultaneously, the liver section displayed features of cirrhosis, including an effaced lobular architecture and the extravasation of red blood cells. Liver enzymes ALT, AST and ALP were consistently elevated with disease progression. Furthermore, immunohistochemistry confirmed the presence of amyloid precursor protein (APP) in the diseased brain. The positive expression of Hypoxia-Inducible Factor 3-Alpha (HIF3A) in the brain indicated hypoxic conditions, which is consistent with other LOAD studies. This model also exhibited damaged intestinal villi and excessive bowel and urinary incontinence, indicating malnutrition and a disturbed gut microbiome, which is also consistent with LOAD patients. Bioinformatics analysis on serum protein suggests a few affected molecular pathways, like the amyloid secretase pathway, androgen/oestrogen/progesterone biosynthesis, the apoptosis signalling pathway, the insulin/IGF pathway-protein kinase B signalling cascade, the Metabotropic glutamate receptor group I pathway, the Wnt signalling pathway, etc. Behavioural analysis confirmed memory decline and the loss of muscle strength with disease progression. Overall, this rat model of LOAD sheds valuable light on LOAD pathology and highlights the potential link between liver dysfunction, particularly induced by the excessive consumption of junk food, and LOAD. This study contributes to a deeper understanding of the complex molecular mechanisms involved in LOAD, paving the way for new possibilities in therapeutic interventions. Full article

Background: Patients with end-stage renal disease (ESRD) undergoing hemodialysis are at an elevated risk of developing dementia, potentially linked to the high prevalence of vitamin D deficiency in this population, which may contribute to cognitive impairment. Nevertheless, the impact of vitamin D supplementation on the risk of dementia in hemodialysis patients remains uncertain, necessitating further investigation to elucidate the potential benefits of vitamin D intervention in this vulnerable group. Methods: In this propensity-score-matched comparative cohort study, we sought to assess the impact of vitamin D supplementation on the occurrence of dementia in patients with end-stage renal disease (ESRD) undergoing hemodialysis. A total of 1424 patients were included and matched 1:1 using propensity scores. The study population was divided into two groups: those receiving vitamin D supplementation at a dose of ≥70 μg/week and those without any supplementation. The primary outcome of interest was the incidence of dementia. We calculated adjusted hazard ratios (aHRs) to examine the association between vitamin D supplementation and the risk of dementia while controlling for relevant covariates. Results: The adjusted hazard ratio (aHR) comparing vitamin D supplementation to no supplementation was 0.44 (95% CI 0.29–0.69; p < 0.0001), demonstrating a significant decrease in the risk of dementia associated with vitamin D supplementation. The aHRs for vitamin D supplementation at different dose ranges (70–105, 106–350, 351–1000, and >1000 μg/week) were 0.51, 0.49, 0.43, and 0.41, respectively (p for trend < 0.0001). These findings suggest a potential dose-dependent relationship between vitamin D supplementation and the reduction of dementia risk. Conclusions: In our study, we found that vitamin D supplementation at doses of ≥70 μg/week significantly reduced the risk of dementia in patients with end-stage renal disease (ESRD) undergoing hemodialysis. Furthermore, our results indicated a dose-dependent effect, with higher doses of supplementation correlating with a greater reduction in dementia risk. These findings underscore the potential of vitamin D supplementation as a preventive approach for cognitive impairment in this high-risk population. Full article

The aim of this review is to present evidence of the impact of ischemic changes in the blood–brain barrier on the maturation of post-ischemic brain neurodegeneration with features of Alzheimer’s disease. Understanding the processes involved in the permeability of the post-ischemic blood–brain barrier during recirculation will provide clinically relevant knowledge regarding the neuropathological changes that ultimately lead to dementia of the Alzheimer’s disease type. In this review, we try to distinguish between primary and secondary neuropathological processes during and after ischemia. Therefore, we can observe two hit stages that contribute to Alzheimer’s disease development. The onset of ischemic brain pathology includes primary ischemic neuronal damage and death followed by the ischemic injury of the blood–brain barrier with serum leakage of amyloid into the brain tissue, leading to increased ischemic neuronal susceptibility to amyloid neurotoxicity, culminating in the formation of amyloid plaques and ending in full-blown dementia of the Alzheimer’s disease type. Full article

Cost-effectiveness analysis (CEA) is the main way that economic evaluations are carried out in the health care field. However, CEA has limited validity in deciding whether any health care evaluation is socially worthwhile and hence justifies funding. Cost-Benefit Analysis (CBA) is the economic evaluation method that should be used to help decide what to invest in when the objective is to record the impact on everyone in society. Cost-utility analysis (CUA), which has its roots in CEA, can be converted into CBA under certain circumstances that are not general. In this article, the strengths and weaknesses of CEA relative to CBA are analyzed in stages, starting in its most classical form and then proceeding via CUA to end up as CBA. The analysis takes place mainly in the context of five actual dementia interventions that have already been found to pass a CBA test. The CBA data is recast into CEA and CUA terms in tabular form in order that the contrast been CEA and CBA is most transparent. We find that how much of the fixed budget that is used up to fund other alternatives determines how much is left over to fund the particular intervention one is evaluating. Full article

This study aimed to comparatively analyze the effect of the person-centered prescription (PCP) model on pharmacotherapeutic indicators and the costs of pharmacological treatment between a dementia-like trajectory and an end-stage organ failure trajectory, and two states of frailty (cut-off point 0.5). A randomized controlled trial was conducted with patients aged ≥65 years admitted to a subacute hospital and identified by the Necessity of Palliative Care test to require palliative care. Data were collected from February 2018 to February 2020. Variables assessed included sociodemographic, clinical, degree-of-frailty, and several pharmacotherapeutic indicators and the 28-day medication cost. Fifty-five patients with dementia-like trajectory and 26 with organ failure trajectory were recruited observing significant differences at hospital admission in the mean number of medications (7.6 vs. 9.7; p < 0.004), the proportion of people on more than 10 medications (20.0% vs. 53.8%; p < 0.002), the number of drug–drug interactions (2.7 vs. 5.1; p < 0.006), and the Medication Regimen Complexity Index (MRCI) (25.7 vs. 33.4; p < 0.006), respectively. Also, regarding dementia-like patients, after application of the PCP model, these patients improved significantly in the intervention group compared to the control group in the mean number of chronic medications, STOPP Frail Criteria, MRCI and the 28-day cost of regular medications (p < 0.05) between admission and discharge. As for the PCP effect on the control and the intervention group at the end-stage organ failure, we did not observe statistically significant differences. On the other hand, when the effect of the PCP model on different degrees of frailty was evaluated, no unequal behavior was observed. Full article

Advances in applied machine learning techniques for neuroimaging have encouraged scientists to implement models to diagnose brain disorders such as Alzheimer’s disease at early stages. Predicting the exact stage of Alzheimer’s disease is challenging; however, complex deep learning techniques can precisely manage this. While successful, these complex architectures are difficult to interrogate and computationally expensive. Therefore, using novel, simpler architectures with more efficient pattern extraction capabilities, such as transformers, is of interest to neuroscientists. This study introduced an optimized vision transformer architecture to predict the group membership by separating healthy adults, mild cognitive impairment, and Alzheimer’s brains within the same age group (>75 years) using resting-state functional (rs-fMRI) and structural magnetic resonance imaging (sMRI) data aggressively preprocessed by our pipeline. Our optimized architecture, known as OViTAD is currently the sole vision transformer-based end-to-end pipeline and outperformed the existing transformer models and most state-of-the-art solutions. Our model achieved F1-scores of $97\%\pm 0.0$ and $99.55\%\pm 0.39$ from the testing sets for the rs-fMRI and sMRI modalities in the triple-class prediction experiments. Furthermore, our model reached these performances using 30% fewer parameters than a vanilla transformer. Furthermore, the model was robust and repeatable, producing similar estimates across three runs with random data splits (we reported the averaged evaluation metrics). Finally, to challenge the model, we observed how it handled increasing noise levels by inserting varying numbers of healthy brains into the two dementia groups. Our findings suggest that optimized vision transformers are a promising and exciting new approach for neuroimaging applications, especially for Alzheimer’s disease prediction. Full article

In Japan, which has an aging society with many deaths, it is important that people discuss preferred place for end-of-life care in advance. This study aims to investigate whether the preferred place of end-of-life care differs by the assumed clinical scenario. This clinical scenario-based survey used data from a nationwide survey conducted in Japan in December 2017. Participants aged 20 years and older were randomly selected from the general population. The survey contained questions based on three scenarios: cancer, end-stage heart disease, and dementia. For each scenario, respondents were asked to choose the preferred place of end-of-life care among three options: home, nursing home, and medical facility. Eight hundred eighty-nine individuals participated in this study (effective response rate: 14.8%). The proportions of respondents choosing home, nursing home, and medical facility for the cancer scenario were 49.6%, 10.9%, and 39.5%, respectively; for the end-stage heart disease scenario, 30.5%, 18.9%, and 50.6%; and for the dementia scenario, 15.2%, 54.5%, and 30.3% (p < 0.0001, chi-square test). The preferred place of end-of-life care differed by the assumed clinical scenario. In clinical practice, concrete information about diseases and their status should be provided during discussions about preferred place for end-of-life care to reveal people’s preferences more accurately. Full article

Background: Alzheimer’s, the predominant formof dementia, is a neurodegenerative brain disorder with no known cure. With the lack of innovative findings to diagnose and treat Alzheimer’s, the number of middle-aged people with dementia is estimated to hike nearly to 13 million by the end of 2050. The estimated cost of Alzheimer’s and other related ailments is USD321 billion in 2022 and can rise above USD1 trillion by the end of 2050. Therefore, the early prediction of such diseases using computer-aided systems is a topic of considerable interest and substantial study among scholars. The major objective is to develop a comprehensive framework for the earliest onset and categorization of different phases of Alzheimer’s. Methods: Experimental work of this novel approach is performed by implementing neural networks (CNN) on MRI image datasets. Five classes of Alzheimer’s disease subjects are multi-classified. We used the transfer learning determinant to reap the benefits of pre-trained health data classification models such as the MobileNet. Results: For the evaluation and comparison of the proposed model, various performance metrics are used. The test results reveal that the CNN architectures method has the following characteristics: appropriate simple structures that mitigate computational burden, memory usage, and overfitting, as well as offering maintainable time. The MobileNet pre-trained model has been fine-tuned and has achieved 96.6 percent accuracy for multi-class AD stage classifications. Other models, such as VGG16 and ResNet50 models, are applied tothe same dataset whileconducting this research, and it is revealed that this model yields better results than other models. Conclusion: The study develops a novel framework for the identification of different AD stages. The main advantage of this novel approach is the creation of lightweight neural networks. MobileNet model is mostly used for mobile applications and was rarely used for medical image analysis; hence, we implemented this model for disease detection andyieldedbetter results than existing models. Full article