Article Type: Heart Health
Researchers at the University of Virginia School of Medicine have created an online metabolic calculator to predict a person's risk of heart disease and diabetes.
A study of the online metabolic calculator suggests it is more accurate at predicting the risk of developing heart disease and diabetes than traditional methods.
The standard approach to predicting the risk of cardiovascular disease, type 2 diabetes and stroke look at the five factors of metabolic syndrome -- obesity, high blood pressure, high fasting triglycerides, low HDL cholesterol and high fasting blood sugar -- all of which can increase a person's risk for all three conditions.
A person is considered to have metabolic syndrome if they have any three or more of the five factors and is at an increased risk of having a heart attack, diabetes or stroke in the future.
The standard approach to assessing risk also does not take into account race, ethnicity or gender, which may leave patients with the conditions go undetected.
The online metabolic calculator weights the traditional risk factors but also accounts for race, gender and ethnicity to create an easy-to-understand metabolic severity score.
"This boils it down to telling a patient, 'On the risk spectrum, you are here, and you're in a position where we're worried you're going to have a cardiovascular event in the next 10 years,'" Dr. Mark DeBoer, of the UVA Medical School and UVA Children's Hospital, said in a press release. "My hypothesis is that the more specific information you can give to individuals at risk, the more they will understand it and be motivated to make some changes."
DeBoer and Matthew Gurka, a researcher at the University of Florida, developed the online metabolic calculator, which weights the traditional risk factors but also accounts for race, gender and ethnicity to create and easy-to-understand metabolic severity score.
The study of more than 13,000 people showed the online metabolic calculator was a better risk predictor than individual risk factors alone.
"This would suggest that when somebody has this congregation of metabolic syndrome findings, there probably is some underlying process that is producing those findings, and that those underlying processes are also contributing to future risk," DeBoer said. "The hope is that a scoring system like this could be incorporated in the electronic medical record to calculate someone's risk and that information could be provided both to the physician, who then realized there is an elevated risk, and to the patient, who hopefully can start taking some preventative steps."
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