Dementia Cases Research Articles

Acute Kidney Injury and Its Association With Dementia and Specific Dementia Types: Findings From a Population-Based Study in Sweden.

Preclinical studies suggest that acute kidney injury (AKI) results in biochemical and pathologic changes in the brain. We aimed to explore the association between experiencing AKI and subsequent risks of developing dementia. We conducted a study involving individuals aged 65 years and older in Stockholm from 2006 to 2019, who were free from dementia diagnosis and had data on kidney function. The exposure was an episode of AKI (time varying), ascertained by issued clinical diagnoses and transient creatinine elevations according to Kidney Disease Improving Global Outcomes criteria. The outcome was all-cause dementia and specific types of dementia, ascertained by clinically confirmed cases in the Swedish registry of cognitive/dementia disorders, the presence of 2 issued dementia diagnoses in outpatient care, or initiation of specific antidementia medications. We investigated associations with dementia through Cox proportional hazard regression by AKI, severity levels of AKI, AKI recurrence, and setting (community-acquired or hospital-acquired AKI). We included 305,122 individuals with a median age of 75 ± 8 years (56.6% women). During a median follow-up of 12.3 (interquartile range 8.7-13.3) years, there were 79,888 individuals (26%) suffering from at least 1 episode of AKI and 47,938 incident cases (16%) of dementia. The rate of dementia cases was 37.0 per 1,000 person-years (95% CI 36.2-37.8) after developing AKI, which was approximately 2 times higher than the rate observed during the periods before AKI (17.3, 95% CI 17.2-17.5). After multivariable adjustment, developing AKI was associated with a 49% higher rate of subsequent dementia (adjusted hazard ratio hazard ratio [HR] 1.49, 95% CI 1.45-1.53). This pattern was consistent across dementia types, with HRs of 1.88 (95% CI 1.53-2.32), 1.47 (1.38-1.56), and 1.31 (1.25-1.38) for dementia with Lewy bodies and Parkinson disease with dementia, vascular dementia, and Alzheimer dementia, respectively. Risk associations were stronger in magnitude across more severe AKIs and in hospital-acquired vs community-acquired AKI. Individuals who experienced an AKI were at increased risk of receiving a diagnosis of dementia.

Effect of a cash transfer intervention on memory decline and dementia probability in older adults in rural South Africa

Evidence on cash transfers as a population-level intervention to support healthy cognitive aging in low-income settings is sparse. We assessed the effect of a cash transfer intervention on cognitive aging outcomes in older South African adults. We leveraged the overlap in the sampling frames of a Phase 3 randomized cash transfer trial [HIV Prevention Trial Network (HPTN) 068, 2011-2015] and an aging cohort [Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community (HAALSI), 2014-2022] in rural Mpumalanga Province, South Africa. In 2011/12, young women and their primary caregivers were randomly assigned 1:1 to receive a monthly cash transfer or control. In 2014/2015, 862 adults aged 40+ y living in trial households were enrolled in the HAALSI cohort, with cognitive data collected in three waves over 7 y. We estimated the impact of the intervention on rate of memory decline and dementia probability scores. Memory decline in the cash transfer arm was 0.03 SD units (95% CI: 0.002, 0.05) slower per year than in the control arm. Dementia probability scores were three percentage points lower in the cash transfer arm than the control arm (β = -0.03; 95% CI: -0.05, -0.001). Effects were consistent across subgroups. A modestly sized household cash transfer delivered over a short period in mid- to later-life led to a meaningful slowing of memory decline and reduction in dementia probability 7 y later. Cash transfer programs could help stem the tide of new dementia cases in economically vulnerable populations in the coming decades.

Development of an AI-Based Predictive Algorithm for Early Diagnosis of High-Risk Dementia Groups among the Elderly: Utilizing Health Lifelog Data.

This study aimed to develop a predictive algorithm for the early diagnosis of dementia in the high-risk group of older adults using artificial intelligence technologies. The objective is to create an accessible diagnostic method that does not rely on traditional medical equipment, thereby improving the early detection and management of dementia. Lifelog data from wearable devices targeting this high-risk group were collected from the AI Hub platform. Various indicators from these data were analyzed to develop a dementia diagnostic model. Machine learning techniques such as Logistic Regression, Random Forest, LightGBM, and Support Vector Machine were employed. Data augmentation techniques were applied to address data imbalance, thereby enhancing the model performance. Data augmentation significantly improved the model's accuracy in classifying dementia cases. Specifically, in gait data, the SVM model performed with an accuracy of 0.879. In sleep data, a Logistic Regression was performed, yielding an accuracy of 0.818. This indicates that the lifelog data can effectively contribute to the early diagnosis of dementia, providing a practical solution that can be easily integrated into healthcare systems. This study demonstrates that lifelog data, which are easily collected in daily life, can significantly enhance the accessibility and efficiency of dementia diagnosis, aiding in the effective use of medical resources and potentially delaying disease progression.

Vascular cognitive impairment and dementia: Mechanisms, treatment, and future directions.

Worldwide, around 50 million people live with dementia, and this number is projected to triple by 2050. It has been estimated that 20% of all dementia cases have a predominant cerebrovascular pathology, while perhaps another 20% of vascular diseases contribute to a mixed dementia picture. Therefore, the vascular contribution to dementia affects 20 million people currently and will increase markedly in the next few decades, particularly in lower- and middle-income countries.In this review, we discuss the mechanisms of vascular cognitive impairment (VCI) and review management. VCI refers to the spectrum of cerebrovascular pathologies that contribute to any degree of cognitive impairment, ranging from subjective cognitive decline, to mild cognitive impairment, to dementia. While acute cognitive decline occurring soon after a stroke is the most recognized form of VCI, chronic cerebrovascular disease, in particular cerebral small-vessel disease, can cause insidious cognitive decline in the absence of stroke. Moreover, cerebrovascular disease not only commonly co-occurs with Alzheimer's disease (AD) and increases the probability that AD pathology will result in clinical dementia, but may also contribute etiologically to the development of AD pathologies.Despite its enormous health and economic impact, VCI has been a neglected research area, with few adequately powered trials of therapies, resulting in few proven treatments. Current management of VCI emphasizes prevention and treatment of stroke and vascular risk factors, with most evidence for intensive hypertension control. Reperfusion therapies in acute stroke may attenuate the risk of VCI. Associated behavioral symptoms such as apathy and poststroke emotionalism are common. We also highlight novel treatment strategies that will hopefully lead to new disease course-modifying therapies. Finally, we highlight the importance of including cognitive endpoints in large cardiovascular prevention trials and the need for an increased research focus and funding for this important area.

A - 124 A Case of Lewy Body Dementia and Charles Bonnet Syndrome in a Patient with Bilateral Enucleation

Abstract Objective The patient presented with a history of blindness due to bilateral enucleation (age 10 and 23) and visual hallucinations for approximately 2 years. Approximately 30% of visually impaired individuals are affected by Charles Bonnet syndrome, characterized by complex visual hallucinations in visually challenged patients, possibly stemming from the brain’s attempt to fill the visual void. Additionally, she was diagnosed with Lewy Body dementia (LBD) 2 years prior by her neurologist, and she reported challenges with completing instrumental activities of daily living (IADLs). Method The patient was a left-handed 83-year-old woman, with a history of total blindness and bilateral enucleation, who presented with progressive memory loss 3–4 years prior, along with balance/gait disturbances for 1–1.5 years. The patient and her family sought neuropsychological testing to clarify her cognitive functioning in light of her physical and neurologic symptoms. Results Premorbid functioning was estimated in the low average range, with 11 years of education. Due to her total vision loss, neuropsychological evaluation was limited. Her cognitive profile was marked by impairments in immediate memory, delayed memory, recognition, executive functioning, and language. Conclusions In light of the patient’s marked cognitive deficits in memory, attention, and executive functioning, along with visual hallucinations (although also attributed to possible Charles Bonnet syndrome), balance/gait disturbances, fluctuating awareness, autonomic dysfunction (i.e., bladder/bowel control), and sleep changes (i.e., acting out dreams), her presentation is consistent with LBD, in the moderate stage of severity. Given the symptomatology, it raises the possibility the patient may be experiencing Charles Bonnet syndrome along with LBD.

Association of adherence to the EAT-Lancet diet with risk of dementia according to social economic status: a prospective cohort in UK Biobank.

The EAT-Lancet Commission has proposed a reference diet aiming to promote human health and environmental sustainability. Socioeconomic disadvantage and poor diet are well-known risk factors for dementia; however, whether the effect of this reference diet on dementia varies by socioeconomic status has not been investigated. The dietary habits of 190,893 participants from UK-Biobank were assessed; the association of EAT-Lancet diet with incident dementia across socioeconomic status was determined by Cox models. One thousand seven hundred twenty-eight dementia cases were identified during a median of 12.24 years follow-up. An inverse association between adherence to EAT-Lancet diet and all-cause dementia (high vs. low; hazard ratio [HR], 95% confidence interval [CI]: 0.82, 0.72-0.94) or late-onset dementia (high vs. low; HR, 95% CI: 0.78, 0.68-0.91) was observed only in individuals with high socioeconomic status. On the contrary, no protective effects of EAT-Lancet diet on early-onset dementia were observed, regardless of the socioeconomic status. Our findings indicated that adherence to an environment-friendly diet helps attenuate risk of dementia only in individuals with high socioeconomic level.

Slow Gait Speed Predicts Incident Dementia, Mortality, and Long-Term Functional Outcome in Cerebral Small-Vessel Disease.

Gait impairment is observed in patients with small vessel disease (SVD); however, the association between gait function and long-term outcome remains unclear. This study aimed to clarify the predictive value of gait function on incident dementia, survival and functional outcome. Data were derived from a Japanese cohort of patients with SVD. This study included 522 participants who underwent 3-m timed up and go test (TUG), and gait speed, TUG time, was divided into tertiles. Magnetic resonance imaging was used to evaluate severity of white matter hyperintensities, lacunes, and medial temporal atrophy. Primary outcome was dementia. All-cause death and functional outcome by modified Rankin scale at the last visit was also evaluated. The median age was 71 years, and median TUG time was 9.91 s. During follow-up period of 4.8 years, 32 cases of dementia occurred. Cox proportional hazard analysis revealed that slow gait speed (TUG time > 10.88 s) was associated with a significantly higher risk of incident dementia than fast (TUG time < 9.03) and middle (TUG time, 9.04-10.87 s) speeds after adjusting risk factors, Mini-Mental State Examination, SVD severity and brain atrophy (adjusted hazard ratio, 2.73; 95% confidence interval, 1.16-6.42, p = 0.022). Slow speed was also associated with mortality and poor functional outcome compared with other speeds (adjusted odds ratio, 4.19; 95% confidence interval 1.92-9.18, p < 0.001). Gait function was associated with incident dementia, mortality and poor functional outcome independently of cognitive function, brain atrophy, and SVD severity.

Functional Principal Component Analysis as an Alternative to Mixed-Effect Models for Describing Sparse Repeated Measures in Presence of Missing Data.

Analyzing longitudinal data in health studies is challenging due to sparse and error-prone measurements, strong within-individual correlation, missing data and various trajectory shapes. While mixed-effect models (MM) effectively address these challenges, they remain parametric models and may incur computational costs. In contrast, functional principal component analysis (FPCA) is a non-parametric approach developed for regular and dense functional data that flexibly describes temporal trajectories at a potentially lower computational cost. This article presents an empirical simulation study evaluating the behavior of FPCA with sparse and error-prone repeated measures and its robustness under different missing data schemes in comparison with MM. The results show that FPCA is well-suited in the presence of missing at random data caused by dropout, except in scenarios involving most frequent and systematic dropout. Like MM, FPCA fails under missing not at random mechanism. The FPCA was applied to describe the trajectories of four cognitive functions before clinical dementia and contrast them with those of matched controls in a case-control study nested in a population-based aging cohort. The average cognitive declines of future dementia cases showed a sudden divergence from those of their matched controls with a sharp acceleration 5 to 2.5 years prior to diagnosis.

Low Intake of Total Antioxidant Nutrients as a Risk Factor for Incident Dementia in Older Adults: The Shanghai Aging Study

Introduction: Previous longitudinal studies reported the impact of antioxidant nutrients (ANs) on cognitive impairment in the older population, but the conclusions were inconsistent. This study aimed to verify the hypothesis that dietary intake of total AN was associated with incident dementia among older individuals. Methods: Community residents without dementia aged ≥60 years were prospectively followed up for an average of 5.2 years in the Shanghai Aging Study. At baseline, daily intakes of total dietary AN (the sum of carotene, vitamin C, vitamin E, lutein, and flavonoids) and energy were calculated based on an interviewer-administered food frequency questionnaire measuring the dietary intake over the past 1 year for each participant. A battery of neuropsychological tests was used to evaluate cognitive function, and a consensus diagnosis of dementia was made according to the DSM-IV criteria at baseline and follow-up. Results: Among 1,550 dementia-free participants, 135 (8.7%) incident dementia cases were identified during the average of 5.2 years of follow-up. Participants with low AN intake (<112 mg/day) had a significantly higher risk of incident dementia than those with high AN intake (≥112 mg/day) (hazard ratio 1.87, 95% confidence interval 1.26–2.77) after adjusting for age, gender, education, obesity, APOE-ε4, hypertension, diabetes, depression, baseline Mini-Mental State Examination score, and total energy intake. The significant association of total AN intake with incident dementia was only found in individuals ≥70 years. Conclusion: Low total AN intake may be a risk factor for incident dementia among older adults. Maintaining sufficient AN intake may be beneficial against age-related cognitive decline.

Eye-Tracking-Based Cognitive Assessment Efficiently Detects Mild Cognitive Decline in the Predementia Stage

Introduction: The early detection of cognitive decline is key to maximizing the benefits of preventive and therapeutic interventions against dementia. Generally, dementia is first assessed by interview-based neuropsychological tests, but the lengthy interview and mental stress during the assessment process make screenings inefficient. We previously developed a rapid screening test for dementia using an eye-tracking technology (eye-tracking-based cognitive assessment [ETCA]) and reported its utility for clinically detecting cognitive impairment in dementia cases. However, the ETCA’s performance in detecting people with mild cognitive decline, which is the major target population for dementia prevention strategies, remains insufficiently examined. Therefore, this study aimed to evaluate the ETCA’s performance in individuals aged 40 years and older (n = 94, mean age: 61.0 [SD 13.1] years) without being formally diagnosed with dementia. Methods: All participants underwent both the ETCA and neuropsychological tests, including the Mini-Mental State Examination (MMSE), Rivermead Behavioral Memory Test (RBMT), and Addenbrooke’s Cognitive Examination-III (ACE-III) on the same day. We examined the correlations in scores between the ETCA and each neuropsychological test. Furthermore, we selected participants who earned normal scores in each neuropsychological test and evaluated the ETCA’s performance in this subgroup. Results: Participants’ ETCA scores correlated significantly with their scores on neuropsychological tests, including the MMSE, RBMT, and ACE-III. Notably, the ETCA scores correlated with the RBMT or ACE-III scores in individuals who showed normal scores in each neuropsychological test. Conclusion: The ETCA has the potential to screen mild cognitive decline efficiently at the predementia stage in nonclinical settings.

A rare case of early onset lewy body dementia with parkinsonism associated with chronic exposure to copper contaminated drinking water.

There is a well-recognized relationship between a person's body burden of essential trace elements such as copper and their neurological function in which both deficiencies and exposures to excessive concentrations are associated with adverse clinical outcomes. Preclinical studies indicate chronic excess copper exposure is associated with altered motor function, dopaminergic neuronal loss, astrocytosis, and microgliosis. Copper also promotes oligomerization and fibrilization of α-synuclein suggesting it may hasten the course of an α-synucleinopathy. Here we report a rare case of early onset Lewy Body Dementia with Parkinsonism in a 53-year-old Caucasian woman exposed to copper contaminated drinking water for more than 10 years. Her hair and that of her daughter had streaks of blue-green discoloration as did the porcelain sinks in their home. Testing confirmed copper contamination of the drinking water. A neurologist diagnosed her with Lewy Body Dementia with Parkinsonism. Skin biopsy for phosphorylated α was consistent with a diagnosis of an α-synucleinopathy. These findings suggest chronic exposure to excessive copper may act as disease modifying factor in Lewy Body Dementia with Parkinsonism. It has previously been recommended that individuals at risk of Alzheimer's disease (AD) avoid excessive intake of copper. Genetic studies indicate that Lewy Body Dementia shares risk factors and pathways with AD. Based on the observations in this patient we recommend that individuals at risk for an α-synucleinopathy based on a positive family history, genetic testing, and/or positive results on a skin biopsy for phosphorylated α-synuclein avoid exposure to excess copper.

Persistent delirium is associated with cerebrospinal fluid markers of neuronal injury.

Delirium is associated with the risk of future long-term cognitive impairment, but the degree to which markers of neuronal injury may be distinct or shared with dementia has yet to be comprehensively described. We investigated CSF biomarkers of dementia, astrocytosis and neuronal damage in a clinical cohort with persistent delirium, comparing them with an outpatient memory clinic sample. Our aim was to determine if different patterns of biomarker changes could implicate specific mechanisms for delirium-related neuronal injury over and above that attributable to comorbid dementia. We recruited 35 participants from the Prince of Wales Hospital, Sydney, Australia. We included inpatients with delirium persisting for at least 5 days (n = 15, 10 with underlying dementia) and participants from outpatient memory clinics (n = 20, 17 with dementia). CSF assays were as follows: amyloid-β42, amyloid-β40, phosphorylated tau181, neurofilament light chain and glial fibrillary acidic protein. We used propensity score matching to estimate effect sizes for each standardized CSF biomarker separately for persistent delirium (irrespective of underlying dementia) and dementia (irrespective of superimposed delirium). Compared with individuals without delirium, persistent delirium was associated with elevated glial fibrillary acidic protein (normalized coefficient per transformed standard deviation, β = 0.85; 95% confidence interval: 0.03-1.68) and neurofilament light chain (β = 1.1; 95% confidence interval: 0.5-1.6), but not phosphorylated tau181. Compared with individuals without dementia, glial fibrillary acidic protein, neurofilament light chain and phosphorylated tau181 were all increased to expected levels in dementia cases, with the former two biomarkers at levels comparable to those seen in persistent delirium [glial fibrillary acidic protein (β = 1.54; 95% confidence interval: 1.05-2.0) and neurofilament light chain (β = 0.65; 95% confidence interval: 0.24-1.1)]. Persistent delirium was linked with changes in CSF biomarkers not necessarily attributable to dementia. These findings support the potential that delirium is associated with direct neuronal injury independent of dementia pathophysiology. Whether this neuronal injury involves astrocyte dysfunction or direct axonal damage are both possibilities. Future work examining acute brain injury in delirium is needed.

Cortical surface-based morphometry in cognitive impairment in sporadic cerebral small vessel disease

Background: Analysis of structural MR images plays a key role in assessing the underlying substrate of cognitive impairment (CI) in sporadic age-related cerebral small vessel disease (SVD), leading to up to 45% of all cases of dementia. The variety of MR-morphometry results in SVD requires extensive research and comparisons with clinical data. Aims: to assess the characteristics of brain atrophy in cognitive impairment in patients with SVD using surface-based morphometry (SBM). Materials and methods: A prospective study was conducted assessing patients with SVD and CI of varying severity (subjective - subCI, moderate - MCI and dementia) and a group of volunteers matched by gender and age. MRI was performed with subsequent analysis of MRI signs of SVD and calculation of the general SVD index and processing of T1mpr images using the SBM method with general and regional quantitative assessment of the brain, including the thickness of the cerebral cortex. Results: the main group with SVD consisted of 173 patients, the control group included 47 healthy volunteers. As the severity of structural changes in the brain and the severity of CI increased, there was a significant (p0.05) decrease in the thickness of the cortex of certain regions according to a similar pattern: the cingulate gyri, mainly their posterior sections; medial and middle sections of the frontal lobes, various parts of the insular cortex, temporo-parietal areas (especially the supramarginal gyri). The volume of the brain itself (total volume, gray and white matter) in SVD had significant differences only with controls, but not between groups of patients with different severity of CI. The volume of white matter hyperintensities was significantly different between the groups with dementia and MCI, dementia and sub-CI (p 0.0001). Conclusions: The data obtained during the study confirm the secondary/mixed nature of atrophy in SVD. The wide variety of regions with significant thinning of the cortex limits the specification of the progression of CI in SVD based on their atrophy. This allows the quantitative measurement of the cortex to be used only as an auxiliary method in assessing the prediction of SVD progression.

Young Onset Dementia in New South Wales, Australia in 1891: What has Changed Since Then?

This study aimed to determine the prevalence and types of young onset dementia (YOD) in New South Wales (NSW), Australia, in 1891 with comparisons to 21st century estimates. Changes might inform future service planning for persons with YOD. Medical case books of two Hospitals for the Insane were examined at the State Archives and clinical and sociodemographic information extracted of persons who were under the age of 65 in April 1891, when a NSW Census occurred, and were given a dementia diagnosis or had symptoms consistent with dementia. Consensus 21st century 'probable' and 'possible' all cause dementia and major neurocognitive disorder diagnoses were determined by two psychiatrists. Prevalence estimates of moderate-severe dementia were determined and compared with 21st century estimates and dementia types. Of 161 potential dementia cases, 123 were given a consensus 'probable' dementia diagnosis, 28 a 'possible' dementia diagnosis, and ten were given a non-dementia diagnosis, with 'all cause dementia' and 'major neurocognitive disorder' diagnoses identical. Most dementia cases were male (n=119, 78.8%). 'Unspecified dementia' was the most frequent diagnosis (n=47, 31.1%), followed by dementia secondary to syphilis (n=35, 23.2%), epileptic dementia (n=30, 19.9%), alcohol-related dementia (n=17, 11.3%), and mixed dementia (n=16, 10.6%). Epileptic dementia had the youngest average age of admission (34.9years). Other than epileptic dementia, all other dementia types were more frequent in males. Prominent clinical symptoms included neurological signs (n=79, 52.3%), psychosis (n=77, 51.0%), agitation (n=75, 49.7%), and aggression (n=45, 29.8%). Most dementia cases either died in hospital (n=79, 52.3%) or were transferred to a long stay hospital (n=57, 37.7%). The estimated point prevalence of YOD in persons aged 30-59 in 1891 (86 per 100,000) was higher than current Australian and global estimates in this age group due to the high rates in males (126per 100,000), but in those aged 60-64, the prevalence in 1891 (159per 100,000) was much lower than current estimates. This first examination of YOD in the nineteenth century found high rates of dementia in those under the age of 60 compared with current estimates, particularly in men aged between 30 and 59years old, and largely due to syphilis, alcohol and epilepsy, conditions that are now treatable and thus demonstrating the potential of effective treatments for YOD.

Analysis of Atypical Antipsychotics-Induced Adverse Events Related to Diabetes Mellitus in Patients With Dementia Using the Japanese Adverse Drug Event Report Database.

Patients with dementia are prescribed low-dose atypical antipsychotics (AAPs) to treat psycho-behavioral symptoms. Although AAPs are known to cause diabetes mellitus-related adverse events (DMAEs), information regarding AAPs-induced DMAEs experienced by patients with dementia is lacking. To use the Japan Adverse Drug Event Report (JADER) database to assess the onset tendencies and patterns of DMAEs attributable to AAPs prescribed to patients with dementia. We performed an analysis using dementia cases from the JADER database that were registered from April 2004 to December 2022. Data in the JADER database are completely anonymized; thus, we did not require institutional review board approval for using the JADER database in our study. The reporting odds ratio and proportional reporting ratio (PRR) were used to assess the onset tendencies of DMAEs with AAPs. In addition, Weibull shape parameters were used to assess the patterns of DMAEs that occur with the use of AAPs. We identified AAPs associated with DMAEs. In particular, low doses of quetiapine showed the potential to induce DMAEs. An analysis of the onset of DMAEs showed the early failure patterns for AAPs (median onset = 38 days). The AAPs may cause DMAEs in patients with dementia. Low doses of quetiapine may induce DMAEs. Health care workers should focus on the development of DMAEs during the early administration period of AAPs. These results may assist with the safe management of patients with dementia who use AAPs.

Anti-amyloid Antibody Drugs as Disease-Modifying Therapies for Alzheimer's Disease

Alzheimer's disease (AD) is a common dementia disorder in the elderly individuals, accounting for approximately 60-70% of all dementia cases. Recently, significant progress has been made in developing and approving anti-amyloid antibody drugs as one of the disease-modifying therapies (DMT) that aim to slow the progression of AD by targeting amyloid-beta accumulation in the brain. Notable drugs such as aducanumab, lecanemab, and donanemab have shown potential in clinical trials, leading to the approval of aducanumab and lecanemab, and approval is also expected for donanemab. Other anti-amyloid drugs such as remternetug and trontinemab are also under development. However, challenges remain, including adverse effects like amyloid-related imaging abnormalities (ARIA) and the need for addressing healthcare preparedness to support their use. This paper outlines the current status of DMT for AD, including the clinical trial results and current applications of these drugs. It also discusses the existing challenges to improve the safety and accessibility of DMTs.

An optimised deep learning approach for alzheimer’s disease classification

&lt;p&gt;Alzheimer’s disease (AD) is a progressive and incurable brain disorder. It starts out subtly and gets worse with time. 60 to 70 percent of dementia cases are brought on by this illness. An Alzheimer’s patient is diagnosed every two seconds, according to research. The complexity of the brain makes it often very challenging to identify in elderly people. In the area of medical imaging, deep learning is growing. Several deep learning techniques that attempted to identify and categorise the magnetic resonance imaging (MRI) brain images into four stages of AD will be compared in this work. 6400 MRI brain images were extracted from a dataset and divided into training, validation, and testing datasets. In our research on twelve deep learning architectures, inceptionV3 has given the best results with 99.56% and 97.75% accuracy on train and validation, respectively, and on test data, the model has achieved an accuracy of 95.81%. We trained the models using optimised ImageNet weights, which resulted in higher accuracy across all twelve models.&lt;/p&gt;

Advances in Understanding and Managing Alzheimer's Disease: From Pathophysiology to Innovative Therapeutic Strategies.

Alzheimer's disease (AD) is a debilitating neurodegenerative disorder characterized by the presence of amyloid-β (Aβ) plaques and tau-containing neurofibrillary tangles, leading to cognitive and physical decline. Representing the majority of dementia cases, AD poses a significant burden on healthcare systems globally, with onset typically occurring after the age of 65. While most cases are sporadic, about 10% exhibit autosomal forms associated with specific gene mutations. Neurofibrillary tangles and Aβ plaques formed by misfolded tau proteins and Aβ peptides contribute to neuronal damage and cognitive impairment. Currently, approved drugs, such as acetylcholinesterase inhibitors and N-methyl D-aspartate receptor agonists, offer only partial symptomatic relief without altering disease progression. A promising development is using lecanemab, a humanized IgG1 monoclonal antibody, as an immune therapeutic approach. Lecanemab demonstrates selectivity for polymorphic Aβ variants and binds to large soluble Aβ aggregates, providing a potential avenue for targeted treatment. This shift in understanding the role of the adaptive immune response in AD pathogenesis opens new possibilities for therapeutic interventions aiming to address the disease's intricate mechanisms. This review aims to summarize recent advancements in understanding Alzheimer's disease pathophysiology and innovative therapeutic approaches, providing valuable insights for both researchers and clinicians.

Association of sleep duration with excess risk of dementia among shift workers in the UK biobank: a population-based cohort study.

Shift work was associated with elevated dementia risk. Definitive guidelines for sleep duration among shift workers have not been proposed. We aimed to identify sleep durations associated with elimination of excess dementia risk in shift workers. 285,213 dementia-free UK Biobank participants at baseline, aged 38-71years, were enrolled between 2006 and 2010 and followed up through 2022 in this cohort study. Cox proportional hazards models were used to examine the associations between shift work, sleep duration, and risk of dementia. The 285,213 participants included 49,079 shift workers and 236,134 non-shift workers. Over a median follow-up of 13.8years, 1887 dementia cases were documented. Current shift workers had significantly higher dementia risk than non-shift workers (hazard ratio [HR] 1.26; 95% CI 1.11-1.42). However, this excess risk was eliminated in shift workers with 8h of sleep (HR 1.02; 95% CI 0.80-1.29). Analysis of shift work frequency indicated that "sometimes" and "usually/always" shift work were associated with increased dementia risk compared to that of non-shift workers, but excess dementia risk was eliminated in members of either frequency group receiving 8h of sleep ("sometimes", HR 1.05; 95% CI 0.75-1.48; "usually/always", HR 0.98; 95% CI 0.70-1.35). Both "non-night shift" and "night shift" workers showed increased dementia risk compared to non-shift workers. Workers with 8h of sleep mitigated the excess risk (HR 1.13; 95% CI 0.84-1.53 and HR 0.86; 95% CI 0.59-1.26, respectively). 8-h sleep may eliminate excess dementia risk among shift workers, suggesting a potentially effective dementia prevention guideline for shift workers.

Guardians of memory: The urgency of early dementia screening in an aging society.

The global aging population has led to a significant rise in the prevalence of age-related non-communicable diseases such as dementia and other cognitive disorders. In 2019, there were 57.4 million people with dementia worldwide, and this number is projected to triple by 2050. Intervening in and managing 12 potentially modifiable dementia risk factors can prevent or delay the onset and progression of about 40% of dementia cases. Neuroimaging, biomarkers, and advanced neuropsychological testing offer promising pathways for the early detection of dementia. Emphasis should be placed on educating the public about the importance of brain health and the early signs of cognitive impairment, as well as promoting dementia prevention measures. Adopting a healthy lifestyle - including a balanced diet, regular physical exercise, active social engagement, cognitive activities, and avoiding smoking and excessive alcohol consumption - can help reduce the risk of cognitive decline and prevent cognitive disorders. Government policies on dementia prevention and health care, along with early and regular dementia screening programs, can enhance the early identification and management of individuals at risk. In addition, integrating cognitive health assessments into routine medical check-ups is essential for the early screening and management of dementia.