A vascular risk factor index in relation to mortality and incident dementia

Frailty in relation to the risk of carotid atherosclerosis and cardiovascular events in Chinese community-dwelling older adults: A five-year prospective cohort study

OBJECTIVE

To investigate the frailty, as estimated by accumulated health deficits, in association with the symptomatic carotid atherosclerosis and in relation to five-year cardiovascular (CVD) outcomes.

METHODS

This is a five-year prospective cohort study. Secondary analysis of data from the Beijing Longitudinal Study on Aging. Community-dwelling people aged 55+ years (n = 1257) have been followed between 2009 and 2014, and having carotid ultrasonography examinations with no CVD events at baseline. Frailty was quantified using the deficit accumulation-based frailty index (FI), constructed from 37 health deficits assessed at baseline. The association between the degree of frailty and carotid atherosclerosis was examined using odds ratios (OR) with multivariate logistic regression analyses. Effects of frailty on the probability of five-year cardiovascular events and mortality were evaluated using Cox proportional hazard ratios (HR). The analyses were adjusted for demographics, baseline carotid atherosclerosis status, and CVD risk factors.

RESULTS

The FI showed characteristic properties and was independently associated with the major carotid atherosclerosis symptoms, including carotid artery intima-media thickening (the most frail vs. the least frail: OR = 4.39: 1.98-7.82), carotid plaque (OR = 3.41: 1.28-6.54), and carotid plaque stability (OR = 1.19, 95 % CI: 1.01-3.59). Compared with the least frail, the most frail individuals were more likely to develop a cardiovascular event in five years, including myocardial infarction (HR = 3.38, 95 % CI = 1.84-6.19), stroke (HR = 1.26, 95 % CI = 1.00-5.87), CVD death (HR = 6.33, 95 % CI = 1.69-11.02), and all-cause death (HR = 5.95, 95 % CI = 2.74-8.95).

CONCLUSION

Deficit accumulation was closely associated with carotid atherosclerosis risks and strongly predicted five-year CVD events. The frailty index can be used to help identify older adults at high risks of CVD for improved preventive healthcare.

A flexible modeling approach for biomarker-based computation of absolute risk of Alzheimer's disease dementia

INTRODUCTION

As Alzheimer's disease (AD) biomarkers rapidly develop, tools are needed that accurately and effectively communicate risk of AD dementia.

METHODS

We analyzed longitudinal data from >10,000 cognitively unimpaired older adults. Five-year risk of AD dementia was modeled using survival analysis.

RESULTS

A demographic model was developed and validated on independent data with area under the receiver operating characteristic curve (AUC) for 5-year prediction of AD dementia of 0.79. Clinical and cognitive variables (AUC = 0.79), and apolipoprotein E genotype (AUC = 0.76) were added to the demographic model. We then incorporated the risk computed from the demographic model with hazard ratios computed from independent data for amyloid positron emission tomography status and magnetic resonance imaging hippocampal volume (AUC = 0.84), and for plasma amyloid beta (Aβ)42/Aβ40 (AUC = 0.82).

DISCUSSION

An adaptive tool was developed and validated to compute absolute risks of AD dementia. This approach allows for improved accuracy and communication of AD risk among cognitively unimpaired older adults.

Associations Between Korean Coronary Heart Disease Risk Score and Cognitive Function in Dementia-Free Korean Older Adults

BACKGROUND

Cardiovascular risk is a modifiable factor that can help prevent dementia. Given the dearth of optimal treatment options, managing dementia risk factors is crucial. We examined the association between cardiovascular risk, as measured by the Korean coronary heart disease risk score (KRS), and cognitive function in dementia-free elderly individuals.

METHODS

We enrolled 8,600 individuals (average age: 69.74 years; 5,206 women) who underwent a medical evaluation from the National Health Insurance Service. KRS was calculated using age, sex, blood pressure, lipid profile, diabetes, and smoking status. Cognitive function was evaluated using Korean Dementia Screening Questionnaire-Cognition (KDSQ-C). Scores of ≥ 6 indicated a cognitive decline. Logistic regression analysis was used to estimate the odds ratio (OR) and 95% confidence interval (CI). Weight, height, stroke history, coronary heart disease history, alcohol consumption, and physical activity engagement were adjusted.

RESULTS

The lowest, middle, and highest groups, according to the KRS, were 5,923 (68.9%), 2,343 (27.2%), and 334 (3.9%), respectively. The highest KRS group in all participants exhibited a greater risk of cognitive decline than the lowest KRS group (OR, 1.339; 95% CI, 1.034-1.734; P = 0.027). The highest KRS female group aged 71-75 years old exhibited greater cognitive decline than the corresponding lowest KRS group (OR, 1.595; 95% CI, 1.045-2.434; P = 0.031).

CONCLUSION

Individuals with high cardiovascular risk were associated with poorer cognitive function than those with low risk, especially older women. Cardiovascular risk factors should be carefully managed to promote healthy mental aging in dementia-free elderly individuals.

Cardiovascular Disease Risk Burden, Cognitive Impairments and Incident Dementia among Community-Dwelling Middle-Aged and Older Adults: An 8-Year Longitudinal Follow-up Study

OBJECTIVES

To evaluate the associations between cardiovascular disease (CVD) risk burden (estimated by the World Health Organization (WHO) algorithm) and cognitive impairments (e.g., incident dementia, global and domain-specific impairments) among CVD-, dementia- and disability-free, community-dwelling middle-aged and older adults during an 8-year follow-up.

DESIGN

A community-based longitudinal cohort study.

SETTING

Yuanshan township in Yi-Lan County, Taiwan.

PARTICIPANTS

A total of 889 community-dwelling residents aged 50 years or older.

MEASUREMENTS

Age, sex, educational level, employment status, alcohol status, body mass index, physical activity, gait speed, depressive symptoms, WHO region-specific CVD risk scores (10-year CV risk, low: <10% vs. moderate-to-high: ≥ 10%), Chinese version of the Mini-Mental State Examination (MMSE), verbal memory by the delay-free recall in the Chinese Version Verbal Learning Test (CVVLT), language function by the Boston Naming Test and the category (animal) Verbal Fluency Test, visuospatial function by the Taylor Complex Figure Test, executive function by the digit backward and the Clock Drawing Test.

RESULTS

Compared to those with low CVD risk, middle-aged and older adults with moderate-to-high CVD risk were at greater risk for cognitive impairments with respect to the MMSE (adjusted odds ratio (aOR) 1.60 [95% confidence interval (CI) 1.19-2.15], P=0.002), verbal memory (aOR 1.97 [1.43-2.70], P< 0.001) and language (aOR 1.99 [1.46-2.70], P< 0.001), as well as incident dementia (aOR 2.40 [1.33-4.33], P=0.004). After adjusting for all covariates, CVD risk was not associated with other domains of cognitive impairment.

CONCLUSIONS

Among healthy, community-dwelling, middle-aged and older adults, those with moderate-to-high cardiovascular risk burden were significantly associated with incident dementia and global and domain-specific cognitive impairments (verbal memory and language), which suggests the existence of a relationship between early cognitive deficits and CVD risk burden. Further studies are needed to elucidate the pathophysiological mechanism of the link between CVD risk burden and cognitive impairment.

Cardiovascular risk moderates the effect of aerobic exercise on executive functions in older adults with subcortical ischemic vascular cognitive impairment

Aerobic training (AT) can promote cognitive function in adults with Subcortical Ischemic Vascular Cognitive Impairment (SIVCI) by modifying cardiovascular risk factors. However, pre-existing cardiovascular health may attenuate the benefits of AT on cognitive outcomes in SIVCI. We examined whether baseline cardiovascular risk moderates the effect of a 6-month progressive AT program on executive functions with a secondary analysis of a randomized controlled trial in 71 adults, who were randomized to either: (1) 3×/week progressive AT; or (2) education program (CON). Three executive processes were measured: (1) response inhibition by Stroop Test; (2) working memory by digits backward test; and (3) set shifting by the Trail Making Test. Baseline cardiovascular risk was calculated using the Framingham cardiovascular disease (CVD) Risk Score (FCRS), and participants were classified as either low risk (< 20% FCRS score; LCVR) or high risk (≥ 20% FCRS score; HCVR). A complete case analysis (n = 58) was conducted using an analysis of covariance (ANCOVA) to evaluate between-group differences in the three executive processes. A significant interaction was found between cardiovascular risk group and intervention group (AT or CON) for the digit span backward and the Trail Making Test. AT improved performance compared with CON in those with LCVR, while in those with HCVR, AT did not improve performance compared with CON. Baseline cardiovascular risk significantly moderates the efficacy of AT on cognition. Our findings highlight the importance of intervening early in the disease course of SIVCI, when cardiovascular risk may be lower, to reap maximum benefits of aerobic exercise.

Combining modifiable risk factors and risk of dementia: a systematic review and meta-analysis

OBJECTIVE

To systematically review the literature relating to the impact of multiple co-occurring modifiable risk factors for cognitive decline and dementia.

DESIGN

A systematic review and meta-analysis of the literature relating to the impact of co-occurring key risk factors for incident cognitive decline and dementia. All abstracts and full text were screened independently by two reviewers and each article assessed for bias using a standard checklist. A fixed effects meta-analysis was undertaken.

DATA SOURCES

Databases Medline, Embase and PsycINFO were searched from 1999 to 2017.

ELIGIBILITY CRITERIA

For inclusion articles were required to report longitudinal data from participants free of cognitive decline at baseline, with formal assessment of cognitive function or dementia during follow-up, and an aim to examine the impact of additive or clustered comorbid risk factor burden in with two or more core modifiable risk factors.

RESULTS

Seventy-nine full-text articles were examined. Twenty-two articles (18 studies) were included reporting data on >40 000 participants. Included studies consistently reported an increased risk associated with greater numbers of intraindividual risk factors or unhealthy behaviours and the opposite for healthy or protective behaviours. A meta-analysis of studies with dementia outcomes resulted in a pooled relative risk for dementia of 1.20 (95% CI 1.04 to 1.39) for one risk factor, 1.65 (95% CI 1.40 to 1.94) for two and 2.21 (95% CI 1.78 to 2.73) for three or more, relative to no risk factors. Limitations include dependence on published results and variations in study outcome, cognitive assessment, length of follow-up and definition of risk factor exposure.

CONCLUSIONS

The strength of the reported associations, the consistency across studies and the suggestion of a dose response supports a need to keep modifiable risk factor exposure to a minimum and to avoid exposure to additional modifiable risks. Further research is needed to establish whether particular combinations of risk factors confer greater risk than others.

PROSPERO REGISTRATION NUMBER

42016052914.

Current Developments in Dementia Risk Prediction Modelling: An Updated Systematic Review

BACKGROUND

Accurate identification of individuals at high risk of dementia influences clinical care, inclusion criteria for clinical trials and development of preventative strategies. Numerous models have been developed for predicting dementia. To evaluate these models we undertook a systematic review in 2010 and updated this in 2014 due to the increase in research published in this area. Here we include a critique of the variables selected for inclusion and an assessment of model prognostic performance.

METHODS

Our previous systematic review was updated with a search from January 2009 to March 2014 in electronic databases (MEDLINE, Embase, Scopus, Web of Science). Articles examining risk of dementia in non-demented individuals and including measures of sensitivity, specificity or the area under the curve (AUC) or c-statistic were included.

FINDINGS

In total, 1,234 articles were identified from the search; 21 articles met inclusion criteria. New developments in dementia risk prediction include the testing of non-APOE genes, use of non-traditional dementia risk factors, incorporation of diet, physical function and ethnicity, and model development in specific subgroups of the population including individuals with diabetes and those with different educational levels. Four models have been externally validated. Three studies considered time or cost implications of computing the model.

INTERPRETATION

There is no one model that is recommended for dementia risk prediction in population-based settings. Further, it is unlikely that one model will fit all. Consideration of the optimal features of new models should focus on methodology (setting/sample, model development and testing in a replication cohort) and the acceptability and cost of attaining the risk variables included in the prediction score. Further work is required to validate existing models or develop new ones in different populations as well as determine the ethical implications of dementia risk prediction, before applying the particular models in population or clinical settings.

Frailty and the risk of cognitive impairment

Aging occurs as a series of small steps, first causing cellular damage and then affecting tissues and organs. This is also true in the brain. Frailty, a state of increased risk due to accelerated deficit accumulation, is robustly a risk factor for cognitive impairment. Community-based autopsy studies show that frail individuals have brains that show multiple deficits without necessarily demonstrating cognitive impairment. These facts cast a new light on the growing number of risk factors for cognitive impairment, suggesting that, on a population basis, most health deficits can be associated with late-life cognitive impairment. The systems mechanism by which things that are bad for the body are likely to be bad for the brain can be understood like this: the burden of health deficits anywhere indicates impaired ability to withstand or repair endogenous and environmental damage. This in turn makes additional damage more likely. If true, this suggests that a life course approach to preventing cognitive impairment is desirable. Furthermore, conducting studies in highly selected, younger, healthier individuals to provide ‘proof of concept’ information is now common. This strategy might exclude the very circumstances that are required for disease expression in the people in whom dementia chiefly occurs (that is, older adults who are often in poor health).

Cardiovascular disease risk models and longitudinal changes in cognition: a systematic review

Background

Cardiovascular disease and its risk factors have consistently been associated with poor cognitive function and incident dementia. Whether cardiovascular disease prediction models, developed to predict an individual's risk of future cardiovascular disease or stroke, are also informative for predicting risk of cognitive decline and dementia is not known.

Objective

The objective of this systematic review was to compare cohort studies examining the association between cardiovascular disease risk models and longitudinal changes in cognitive function or risk of incident cognitive impairment or dementia.

Materials and Methods

Medline, PsychINFO, and Embase were searched from inception to March 28, 2014. From 3,413 records initially screened, 21 were included.

Results

The association between numerous different cardiovascular disease risk models and cognitive outcomes has been tested, including Framingham and non-Framingham risk models. Five studies examined dementia as an outcome; fourteen studies examined cognitive decline or incident cognitive impairment as an outcome; and two studies examined both dementia and cognitive changes as outcomes. In all studies, higher cardiovascular disease risk scores were associated with cognitive changes or risk of dementia. Only four studies reported model prognostic performance indices, such as Area Under the Curve (AUC), for predicting incident dementia or cognitive impairment and these studies all examined non-Framingham Risk models (AUC range: 0.74 to 0.78).

Conclusions

Cardiovascular risk prediction models are associated with cognitive changes over time and risk of dementia. Such models are easily obtainable in clinical and research settings and may be useful for identifying individuals at high risk of future cognitive decline and dementia.

Development and validation of a brief dementia screening indicator for primary care

BACKGROUND

Detection of "any cognitive impairment" is mandated as part of the Medicare annual wellness visit, but screening all patients may result in excessive false positives.

METHODS

We developed and validated a brief Dementia Screening Indicator using data from four large, ongoing cohort studies (the Cardiovascular Health Study [CHS]; the Framingham Heart Study [FHS]; the Health and Retirement Study [HRS]; the Sacramento Area Latino Study on Aging [SALSA]) to help clinicians identify a subgroup of high-risk patients to target for cognitive screening.

RESULTS

The final Dementia Screening Indicator included age (1 point/year; ages, 65-79 years), less than 12 years of education (9 points), stroke (6 points), diabetes mellitus (3 points), body mass index less than 18.5 kg/m(2) (8 points), requiring assistance with money or medications (10 points), and depressive symptoms (6 points). Accuracy was good across the cohorts (Harrell's C statistic: CHS, 0.68; FHS, 0.77; HRS, 0.76; SALSA, 0.78).

CONCLUSIONS

The Dementia Screening Indicator is a simple tool that may be useful in primary care settings to identify high-risk patients to target for cognitive screening.

Frailty Markers Predicting Emergency Department Visits in a Community-Dwelling Sample of Vulnerable Seniors in Montreal

La fragilité met les individus à un risque accru de mauvaise santé. Les personnes âgées consomment une quantité disproportionnée des ressources du service des urgence [SU]. Afin d’étudier la relation entre les marqueurs de fragilité et l’effet sur l’utilisation des services des urgence par les personnes âgées vivant dans les communautés, nous avons mené une analyse secondaire d’un essai prospectif randomisé contrôlé de 22 mois à Montreal, au Canada, en utilisant la base de données du Système de services intégrés pour personnes âgées en perte d’autonomie (SIPA). Nous avons evalué un échantillon de 565 individus, avec cinq marqueurs de fragilité : l’activité physique, la force, la cognition, l’énérgie et la mobilité. Une régression logistique univariée et multivariée a été réalisée afin d’évaluer la relation potentielle entre les marqueurs de fragilité et les visites aux urgences. Les résultats ont révelé que 70 pour cent des participants avaient au moins trois marqueurs de fragilité. Cependant, aucune relation n’a été trouvée entre les marqueurs de fragilité et les visites aux urgences. Ces résultats suggèrent, donc, que parmi les personnes âgées fonctionellement sévèrement handicapés au sein des communautés, la présence de marqueurs de fragilité ne semble pas prévoir les visites aux urgences.

Occurrence of medical co-morbidity in mild cognitive impairment: implications for generalisation of MCI research

BACKGROUND

diagnosis of mild cognitive impairment (MCI) typically excludes individuals with medical co-morbidity. Interest in MCI screening raises the questions of what are the best criteria to identify a representative sample and what factors are associated with MCI progression to dementia.

OBJECTIVES

to compare the pattern of disease co-morbidity across different cognitive groups and to examine the role of health co-morbidity as a risk factor for dementia progression from MCI.

METHODS

individuals from the MRC Cognitive Function and Ageing Study were classified as having no cognitive impairment (NCI), MCI, other cognitive impairment no dementia (OCIND) or dementia. At 2 years dementia status was assessed.

FINDINGS

over 50% of individuals in each group reported one or more medical condition. The pattern of disease prevalence was similar in the NCI, MCI and OCIND groups. Anaemia was the only health factor associated with an increased risk of dementia progression from MCI.

CONCLUSION

classification of MCI using medical exclusions would exclude the majority of the population from a MCI diagnosis. This has implications for treatment decisions and clinical trial recruitment. This could not only make recruitment more difficult but also limit the generalisability of trial results. Medical co-morbidity does not help to distinguish progressive from non-progressive MCI.

Modelling cognitive decline in the Hypertension in the Very Elderly Trial [HYVET] and proposed risk tables for population use

Introduction

Although, on average, cognition declines with age, cognition in older adults is a dynamic process. Hypertension is associated with greater decline in cognition with age, but whether treatment of hypertension affects this is uncertain. Here, we modelled dynamics of cognition in relation to the treatment of hypertension, to see if treatment effects might better be discerned by a model that included baseline measures of cognition and consequent mortality

Methodology/Principal Findings

This is a secondary analysis of the Hypertension in the Very Elderly Trial (HYVET), a double blind, placebo controlled trial of indapamide, with or without perindopril, in people aged 80+ years at enrollment. Cognitive states were defined in relation to errors on the Mini-Mental State Examination, with more errors signifying worse cognition. Change in cognitive state was evaluated using a dynamic model of cognitive transition. In the model, the probabilities of transitions between cognitive states is represented by a Poisson distribution, with the Poisson mean dependent on the baseline cognitive state.

The dynamic model of cognitive transition was good (R² = 0.74) both for those on placebo and (0.86) for those on active treatment. The probability of maintaining cognitive function, based on baseline function, was slightly higher in the actively treated group (e.g., for those with the fewest baseline errors, the chance of staying in that state was 63% for those on treatment, compared with 60% for those on placebo). Outcomes at two and four years could be predicted based on the initial state and treatment.

Conclusions/Significance

A dynamic model of cognition that allows all outcomes (cognitive worsening, stability improvement or death) to be categorized simultaneously detected small but consistent differences between treatment and control groups (in favour of treatment) amongst very elderly people treated for hypertension. The model showed good fit, and suggests that most change in cognition in very elderly people is small, and depends on their baseline state and on treatment. Additional work is needed to understand whether this modelling approach is well suited to the valuation of small effects, especially in the face of mortality differences between treatment groups.

Trial Registration

ClinicalTrials.gov NCT0012281

Dementia risk prediction in the population: are screening models accurate?

Early identification of individuals at risk of dementia will become crucial when effective preventative strategies for this condition are developed. Various dementia prediction models have been proposed, including clinic-based criteria for mild cognitive impairment, and more-broadly constructed algorithms, which synthesize information from known dementia risk factors, such as poor cognition and health. Knowledge of the predictive accuracy of such models will be important if they are to be used in daily clinical practice or to screen the entire older population (individuals aged >or=65 years). This article presents an overview of recent progress in the development of dementia prediction models for use in population screening. In total, 25 articles relating to dementia risk screening met our inclusion criteria for review. Our evaluation of the predictive accuracy of each model shows that most are poor at discriminating at-risk individuals from not-at-risk cases. The best models incorporate diverse sources of information across multiple risk factors. Typically, poor accuracy is associated with single-factor models, long follow-up intervals and the outcome measure of all-cause dementia. A parsimonious and cost-effective consensus model needs to be developed that accurately identifies individuals with a high risk of future dementia.