Individuals in the general population with high levels of silent coronary atherosclerosis can be successfully identified with a simple questionnaire that they can complete themselves at home, a new study suggests.
The Swedish CardioPulmonary BioImage Study (SCAPIS) found that 40% of middle-aged adults without known heart disease had evidence of coronary atherosclerosis on coronary CT angiography (CCTA), and 13% had extensive atherosclerotic disease.
The authors found that the screening questionnaire could identify individuals who had extensive coronary atherosclerosis with a reasonably high predictive value.
Initial results from the study were presented today at the virtual American Heart Association (AHA) Scientific Sessions 2020.
“Our study is looking to see if we can estimate how many people in the general population have significant coronary atherosclerosis and therefore could benefit from preventative treatment,” lead author, Göran Bergström, MD, explained to Medscape Medical News.
Bergström, who is professor and lead physician at Sahlgrenska Academy, Gothenburg University, Gothenburg, Sweden, said there are no good data on this as yet. “There are studies of atherosclerosis burden in patients who have had a cardiovascular event, but our study was conducted in a random selection of the middle-aged general population who did not have symptoms of heart disease.”
“Our study also suggests that in future we may be able to identify these people with an online questionnaire, and those that reached a certain score could be referred for an imaging test,” he added.
SCAPIS included more than 30,000 men and women, age 50 to 64 years, who had no history of cardiovascular events or cardiac intervention. They were asked questions about sex, age, lifestyle, smoking, body measurements, cholesterol medication, and blood pressure to predict their risk for coronary artery disease.
Researchers then used CCTA images to examine patients’ arteries for the presence of plaque. More than 25,000 individuals from the original sample were successfully imaged.
Results showed that 40% of the middle-aged population had some coronary atherosclerosis and 5% had severe atherosclerosis, defined as the presence of a stenosis blocking 50% or more of blood flow in one of the coronary arteries.
A second aim of the study was to use data from the questionnaire to develop a prediction model to identify people with widespread atherosclerosis — those with any type of stenosis in four different segments of their coronary arteries, who made up 13% of the population.
The questionnaire included data on 120 different variables. Of these variables, around 100 could be assessed by the patients themselves and another 20 measurements could be performed in the clinic, such as blood pressure and cholesterol levels.
The researchers then used artificial intelligence to assess which variables were associated with widespread atherosclerosis. This had an area under the curve (AUC, a measure of the predictive value) of 0.8.
“An AUC of 1.0 would show a perfect prediction, and a value of 0.5 shows no value. A result of 0.8 shows reasonable predictive potential. This is an encouraging result and suggests this strategy could work,” Bergström said.
“We know silent atherosclerosis is a big problem and causes sudden cardiac events in people who have not shown symptoms,” he said.