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BackgroundAccurate 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.MethodsOur 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.FindingsIn 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.InterpretationThere 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.

BackgroundStroke is associated with an increased risk of dementia; however, the impact of stroke on cognition has been found to be variable, such that stroke survivors can show decline, remain stable, or revert to baseline cognitive functioning. Knowing the natural history of cognitive impairment after stroke is important for intervention. The aim of this systematic review is to investigate the longitudinal course of cognitive function in stroke survivors.Methods and ResultsThree electronic databases (Medline, Embase, PsycINFO) were searched using OvidSP from inception to July 15, 2016. Longitudinal studies with ≥2 time points of cognitive assessment after stroke were included. In total, 5952 articles were retrieved and 14 were included. There was a trend toward significant deterioration in cognitive test scores in stroke survivors (8 studies). Cognitive stability (3 studies) and improvement (3 studies) were also demonstrated, although follow‐up time tended to be shorter in these studies. Variables associated with impairment included age, ethnicity, premorbid cognitive performance, depression, stroke location, and history of previous stroke. Associations with APOE*E4 (apolipoprotein E with the E4 allele) allele status and sex were mixed.ConclusionsStroke is associated with an increased risk of cognitive decline, but cognitive decline is not a consequence. Factors associated with decline, such as sociodemographic status, health‐related comorbidity, stroke history, and clinical features could be used in models to predict future risk of dementia after stroke. A risk model approach could identify patients at greatest risk for timely intervention to reduce the frequency or delay the onset of poststroke cognitive impairment and dementia.

Background: Time trends for dementia prevalence and incidence rates have been reported over the past seven decades in different countries and some have reported a decline. Objective: To undertake a systematic review to critically appraise and provide an evidence-based summary of the magnitude and direction of the global changes in dementia prevalence and incidence across time. Methods: Medline, EMBASE, and PsychINFO were searched for studies focused on secular trends in dementia prevalence and/or incidence until 18 December 2017. In total, 10,992 articles were identified and 43 retained. Results: Overall, prevalence rates are largely increasing (evidence primarily from record-based surveys and cohort studies in Japan, Canada, and France) or have remained stable (evidence primarily from cohort studies in Sweden, Spain and China). A significant decline in prevalence has however been reported in more recent studies (i.e., from 2010 onwards) from Europe (e.g., UK and Sweden) and the USA. Incidence rates have generally remained stable or decreased in

BackgroundCardiovascular 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.ObjectiveThe 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 MethodsMedline, PsychINFO, and Embase were searched from inception to March 28, 2014. From 3,413 records initially screened, 21 were included.ResultsThe 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).ConclusionsCardiovascular 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.