A new tool for predicting risk of cardiovascular event or death in patients who have suffered a heart attack
Translational Research Project Grant – Prof Mamas A Mamas, University of Manchester
Summary: People with cardiovascular disease (CVD) have a higher risk of developing a future cardiovascular event such as stroke or heart attack, but there are no tools available to predict the risk in this group of patients. This project will use medical data to develop a tool that predicts the risk of a future cardiovascular event or death, in people who have already had a heart attack with the aim of improving care of patients with CVD.
In the UK, around 7 million people live with cardiovascular disease (CVD) and it is responsible for one in four deaths. People with CVD are at higher risk of ill health and hospital admissions. For example, they are up to five times more likely to have a stroke, six times more likely to die compared to those without, and up to half of them suffer a second heart attack. Several tools are available to predict the risk of developing future cardiovascular events, such as a stroke or heart attack, or death in people without CVD. However, there are no such tools for people who already have CVD. With nearly 1 million people alive in the UK who have survived a heart attack, there is an urgent need for such tools to help assess the risk of future cardiovascular events and deaths in patients who already have CVD.
Professor Mamas and his team will use anonymised medical data routinely collected during GP visits between 2006 and 2019 to develop a tool that predicts the risks of developing a future cardiovascular event or death, in people who had a heart attack between 2006 and 2014 in England. Using analytic methods, they will look at the impact of how long ago the heart attack happened on predicting future events within one and five years. The effects of other important factors, such as age, smoking, blood pressure and cholesterol levels, and other health conditions, will be also considered.
The development of a modern prediction tool would improve the quality of care for patients with CVD by helping GPs to identify patients at higher risk of future cardiovascular events and death, so that lifestyle changes can be made or appropriate medical treatment given to reduce their risk.