Diagnostic & Healthcare Policy

This article outlines a proposed agenda from the Latin American and Caribbean Consortium on Dementia to deliver a Knowledge to Action Framework. The authors summarize evidence‐based strategies (epidemiology, genetics, biomarkers, clinical trials, nonpharmacological interventions, networking, and translational research) and align them to current global strategies to translate regional knowledge into transformative actions.

Predicting dementia is a major goal of many researchers. To do this teams use studies where there are lots of people without dementia at the start and where there is follow up data where some members of the study have developed dementia. The scientists will then use lots of information about participants to build a model that can predict who is in the dementia group at follow up and who is in the no dementia group. Ultimately these models can then be used in dementia free groups to predict who is at the highest risk of developing dementia in the future. These models have typically been developed in high income countries. However we know the majority of people who live with dementia are actually in low- and middle- income countries. This study looked at whether the models developed in the high-income countries worked in a set of low- and middle-income countries. Data from low- and middle-income countries was gathered from China, Cuba, the Dominican Republic, Mexico, Peru, Puerto Rico and Venezuela. The team tested 5 models developed in high-income countries, all known by acronyms listed below:

• CAIDE
• AgeCoDe
• ANU-ADRI
• BDSI
• BDRM

The CAIDE and the AgeCoDe models were not good at predicting who had dementia when they were tested in the low- and middle-income countries. The ANU-ADI, BDSI and BDRM models were able to predict dementia as well as they can in the country they were developed. The models worked best in Peru and worst in the Dominican Republic and China. The paper concludes that models developed in high income countries will not necessarily work in low- and middle-income countries. More work is needed to work out which data is particularly good at predicting dementia in these countries. However, the three models that worked well could be used immediately to start research into reducing risk in those predicted to develop dementia in low- and middle- income countries.

Nowadays, research studies are often conducted in collaboration with NHS services. This means that research staff are more likely to present from a range of professional backgrounds. Accordingly, it is important to develop a standardised guide to roles and responsibilities so that all research staff, regardless of background, are appropriately skilled and competent. This guide is termed a ‘competency framework’. Having a competency framework in place promotes high quality research and ensures that participants are safe and appropriately cared for.

Gowie and colleagues took two steps prior to developing a competency framework for clinical research workers in the NHS. First, the authors reviewed current competency frameworks. Second, they ran a focus session to collect research staff perspectives on their roles and the most valuable skills associated with their job. Three main themes were identified from the focus session that were incorporated into the proposed competency framework:

1) attributes clinical research staff should possess

2) career definition and development 

3) the structure of the competency framework.

The competency framework proposed by this study considered the skills of non-registered staff, as opposed to only the research nurse role. The study identified a gap in current frameworks in the consideration of interpersonal skills as a competency. For example, staff in the focus group identified that clinical research staff require good communication skills and to be a good listener. Steps to build on this study in the future may include testing the proposed framework amongst different research sites, and seeking feedback

This study examines cognition and everyday functioning in patients with Functional Cognitive Disorder (FCD) compared to patients with Mild Cognitive Impairment (MCI), with the aim of drawing attention to the similarities in presentation between the two and the resulting challenge in diagnosing FCD.

The current consensus of FCD describes it as a condition of subjective cognitive impairment with inconsistent performance on objective cognitive testing and everyday functioning, whereas MCI consists of both consistently poor cognition and poor functional performance. The study finds that both groups perform similarly on objective cognitive testing and in tests of ‘everyday’ functioning, highlighting the challenge that faces the current consensus on FCD. Individual cases are described and recommendations are laid out for further research, and toward clarifying FCD itself and its diagnosis. 

The elderly population in Ghana is expected to rise rapidly in the near future yet there is only one reported study on dementia from the region. A lack of research may undermine health provision preparation and preventative strategies. Nyame and colleagues conduct a review of the literature from sub-Saharan African regions as well as report data from the Kintampo Dementia Initiative study, in order to identify dementia –related research needs. The authors identify key themes for future research including the need for epidemiological data, prevention of dementia, and strategies to improve quality of life. They also provide directions for further dementia-related research in the Ghanian population.

Around two thirds of people living with dementia live in low and middle income countries (LMIC). With no drugs yet that can cure dementia we know that we need to look at preventing or slowing down the diseases that cause dementia. Some risk factors such as our genetic make-up cannot be changed, but other risk factors such as diet, weight and activity levels can be changed and if those at risk made these lifestyle changes, it could delay the onset of disease. If we could delay the onset of the dementia by five years then half as many people at one time would be living with dementia. We have good data for this in high-income countries. However, Danso and colleagues argue that we need to estimate how many people in LMIC countries have these risk factors and develop a way of monitoring these risk factors so that people in LMIC can implement dementia prevention strategies too.

People living in LMIC do not have access to as many expensive resources as high-income countries, such as brain scanners. So it may be more difficult to track disease progress. Although, there may be other ways to do this. More and more people in LMIC do have access to mobile phones, so using the information from these, such as GPS monitoring, you may be able to tell if someone is getting lost more often, or language analysis of text messages and speech could tell us if their language style is changing. Using this data, and crunching it along with data generated across the world, we could be able to see patterns emerging and use this in LMIC to get a better picture of dementia risk and possible prevention interventions.