Projected prevalence and incidence of dementia accounting for secular trends and birth cohort effects: a population-based microsimulation study

Cognitive performance classification of older patients using machine learning and electronic medical records

Dementia rates are projected to increase significantly by 2050, posing considerable challenges for healthcare systems worldwide. Developing efficient diagnostic tools is critical, and machine learning (ML) algorithms have shown potential for improving the accuracy of cognitive impairment classification. This study aims to address challenges in current systems by leveraging readily available electronic medical record (EMR) data to simplify and enhance the classification of cognitive impairment. The analysis includes 283 older adults, categorized into three groups: 144 individuals with mild cognitive impairment (MCI), 38 with dementia, and 101 healthy controls. Various ML techniques are evaluated to classify cognitive performance levels based on input features such as sociodemographic variables, lab results, comorbidities, Body Mass Index (BMI), and functional scales. Key predictors for distinguishing healthy controls from individuals with MCI are identified. These are history of myocardial infarction, vitamin D3 levels, the Instrumental Activities of Daily Living (IADL) scale, age, and sodium levels. The nonlinear Support Vector Machine (SVM) with a Radial Basis Function (RBF) kernel achieve the best performance for MCI classification, with an accuracy of 69%, an AUC of 0.75, and a Matthews Correlation Coefficient (MCC) of 0.43. For distinguishing healthy controls from those with dementia, the most influential factors include the IADL scale, the Activities of Daily Living (ADL) scale, education, vitamin D3 levels, and age. Here, the Random Forest algorithm demonstrates superior performance, achieving 84% accuracy, an AUC of 0.96, and an MCC of 0.71. These two models consistently outperform other ML techniques, such as K-Nearest Neighbors, Multi-Layer Perceptron, linear SVM, Naive Bayes, Quadratic Discriminant Analysis, Linear Discriminant Analysis, AdaBoost, and Gaussian Process Classifiers. The findings suggest that EMR data can be an effective resource for the initial classification of cognitive impairments. Integrating these ML-driven approaches into primary care settings may facilitate the early identification of older patients who could benefit from further cognitive assessments.

Time to nursing home admission and death in people with dementia: systematic review and meta-analysis

OBJECTIVE

To summarise available evidence on time to nursing home admission and death among people with dementia, and to explore prognostic indicators.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

Medline, Embase, Web of Science, Cochrane, and Google Scholar from inception to 4 July 2024.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Longitudinal studies on survival or nursing home admission in people with dementia. Studies with fewer than 150 participants, recruitment during acute hospital admission, or less than one year of follow-up were excluded.

RESULTS

19 307 articles were identified and 261 eligible studies included. 235 reported on survival among 5 553 960 participants and 79 reported on nursing home admission among 352 990 participants. Median survival from diagnosis appeared to be strongly dependent on age, ranging from 8.9 years at mean age 60 for women to 2.2 years at mean age 85 for men. Women overall had shorter survival than men (mean difference 4.1 years (95% confidence interval 2.1 to 6.1)), which was attributable to later age at diagnosis in women. Median survival was 1.2 to 1.4 years longer in Asia than in the US and Europe, and 1.4 years longer for Alzheimer's disease compared with other types of dementia. Compared with studies before 2000, survival was longer in contemporary clinic based studies (Ptrend=0.02), but not in community based studies. Taken together, variation in reported clinical characteristics and study methodology explained 51% of heterogeneity in survival. Median time to nursing home admission was 3.3 years (interquartile range 1.9 to 4.0). 13% of people were admitted in the first year after diagnosis, increasing to 57% at five years, but few studies appropriately accounted for competing mortality risk when assessing admission rates.

CONCLUSIONS

The average life expectancy of people with dementia at time of diagnosis ranged from 5.7 years at age 65 to 2.2 at age 85 in men and from 8.0 to 4.5, respectively, in women. About one third of remaining life expectancy was lived in nursing homes, with more than half of people moving to a nursing home within five years after a dementia diagnosis. Prognosis after a dementia diagnosis is highly dependent on personal and clinical characteristics, offering potential for individualised prognostic information and care planning.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42022341507.

Dementia Incidence in Quebec Over 20 Years

This cross-sectional study examines the incidence of dementia from 2003 to 2023 in Quebec, Canada.

The Digitized Memory Clinic

Several major challenges, including an ageing population and declining workforce and the implementation of recent breakthrough therapies for Alzheimer disease, are prompting a necessary rethink of how people with neurodegenerative dementias are diagnosed and medically managed. Digital health technologies could play a pivotal part in this transformation, with new advances enabling the collection of millions of data points from a single individual. Possible applications include unobtrusive monitoring that aids early detection of disease and artificial intelligence-based health advice. To translate these advances to meaningful benefits for people living with a disease, technologies must be implemented within a system that retains the physician expert as a central figure in decision-making. This Perspective presents a new framework, termed the Digitized Memory Clinic, for the diagnostic pathway of neurodegenerative dementias that incorporates digital health technologies with currently available assessment tools, such as fluid and imaging biomarkers, in an interplay with the physician. The Digitized Memory Clinic will manage people across the entire disease spectrum, from the detection of risk factors for cognitive decline and the earliest symptoms to dementia, and will replace the present paradigm of a pure 'brick-and-mortar' memory clinic. Important ethical, legal and societal barriers associated with the implementation of digital health technologies in memory clinics need to be addressed. The envisioned Digitized Memory Clinic aims to improve diagnostics and enable precise disease-tracking prognostication for individuals with memory disorders and to open new possibilities, such as precision medicine for prevention and treatment.

Changes in prevalence and incidence of dementia and risk factors for dementia: an analysis from cohort studies

BACKGROUND

Some cohort studies have reported a decline in dementia prevalence and incidence over time, although these findings have not been consistent across studies. We reviewed evidence on changes in dementia prevalence and incidence over time using published population-based cohort studies that had used consistent methods with each wave and aimed to quantify associated changes in risk factors over time using population attributable fractions (PAFs).

METHODS

We searched for systematic reviews of cohort studies examining changes in dementia prevalence or incidence over time. We searched PubMed for publications from database inception up to Jan 12, 2023, using the search terms "systematic review" AND "dementia" AND ("prevalence" OR "incidence"), with no language restrictions. We repeated this search on March 28, 2024. From eligible systematic reviews, we searched the references and selected peer-reviewed publications about cohort studies where dementia prevalence or incidence was measured in the same geographical location, at a minimum of two timepoints, and that reported age-standardised prevalence or incidence of dementia. Additionally, data had to be from population-based samples, in which participants' cognitive status was assessed and where validated criteria were used to diagnose dementia. We extracted summary-level data from each paper about dementia risk factors, contacting authors when such data were not available in the published paper, and calculated PAFs for each risk factor at all available timepoints. Where possible, we linked changes in dementia prevalence or incidence with changes in the prevalence of risk factors.

FINDINGS

We identified 1925 records in our initial search, of which five eligible systematic reviews were identified. Within these systematic reviews, we identified 71 potentially eligible primary papers, of which 27 were included in our analysis. 13 (48%) of 27 primary papers reported change in prevalence of dementia, ten (37%) reported change in incidence of dementia, and four (15%) reported change in both incidence and prevalence of dementia. Studies reporting change in dementia incidence over time in Europe (n=5) and the USA (n=5) consistently reported a declining incidence in dementia. One study from Japan reported an increase in dementia prevalence and incidence and a stable incidence was reported in one study from Nigeria. Overall, across studies, the PAFs for less education or smoking, or both, generally declined over time, whereas PAFs for obesity, hypertension, and diabetes generally increased. The decrease in PAFs for less education and smoking was associated with a decline in the incidence of dementia in the Framingham study (Framingham, MA, USA, 1997-2013), the only study with sufficient data to allow analysis.

INTERPRETATION

Our findings suggest that lifestyle interventions such as compulsory education and reducing rates of smoking through country-level policy changes could be associated with an observed reduction, and therefore future reduction, in the incidence of dementia. More studies are needed in low-income and middle-income countries, where the burden of dementia is highest, and continues to increase.

FUNDING

National Institute for Health and Care Research Three Schools' Dementia Research Programme.

Investigating molecular interactions between human transferrin and resveratrol through a unified experimental and computational approach: Role of natural compounds in Alzheimer's disease therapeutics

Disruptions to iron metabolism and iron homeostasis have emerged as significant contributors to the development and progression of Alzheimer's disease (AD). Human transferrin plays a key part in maintaining iron equilibrium throughout the body, highlighting its importance in AD. Many plant-derived compounds and dietary constituents show promise for preventing AD. Polyphenols that are abundant in fruits, vegetables, teas, coffee, and herbs possess neuroprotective attributes. Resveratrol is a natural polyphenol present in various plant sources like grapes, berries, peanuts, and red wine that has garnered research interest due to its wide range of biological activities. Notably, resveratrol exhibits neuroprotective effects that may help prevent or treat AD through multiple mechanisms. In the present study, we employed a combination of molecular docking and all-atom molecular dynamic simulations (MD) along with experimental approaches to unravel the intricate interactions between transferrin and resveratrol deciphering the binding mechanism. Through molecular docking analysis, it was determined that resveratrol occupies the iron binding pocket of transferrin. Furthermore, MD simulations provided a more profound insight into the stability and conformational dynamics of the complex suggesting that the binding of resveratrol introduced localized flexibility, while maintaining overall stability. The spectroscopic observations yielded clear evidence of substantial binding between resveratrol and transferrin, confirming the computational findings. The identified binding mechanism and conformational stability hold potential for advancing the development of innovative therapeutic approaches targeting AD through resveratrol, particularly concerning iron homeostasis. These insights serve as a platform for considering the natural compounds in the realm of AD therapeutics.

Clinical trials in vascular cognitive impairment following SPRINT-MIND: An international perspective

A large interventional trial, the Systolic Blood Pressure Intervention Trial sub-study termed Memory and Cognition in Decreased Hypertension (SPRINT-MIND), found reduced risk of cognitive impairment in older adults with intensive, relative to standard, blood-pressure-lowering targets (systolic BP < 120 vs. <140 mm Hg). In this perspective, we discuss key questions and make recommendations for clinical practice and for clinical trials, following SPRINT-MIND. Future trials should embody cognitive endpoints appropriate to the participant group, ideally with adaptive designs that ensure robust answers for cognitive and cardiovascular endpoints. Reliable data from diverse populations, including the oldest-old (age > 80 years), will maximize external validity and global implementation of trial findings. New biomarkers will improve phenotyping to stratify patients to optimal treatments. Currently no antihypertensive drug class stands out for dementia risk reduction. Multi-domain interventions, incorporating lifestyle change (exercise, diet) alongside medications, may maximize global impact. Given the low cost and wide availability of antihypertensive drugs, intensive BP reduction may be a cost-effective means to reduce dementia risk in diverse, aging populations worldwide.