Study: Online ‘Crystal Ball’ Better At Predicting Heart Disease, Diabetes Risk Than Doctor
CHARLOTTESVILLE, Va. — Traditional methods for predicting heart disease and diabetes risks involve a physician evaluating five health traits of a given patient for warnings signs. A new study finds, however, that an online metabolic calculator can more accurately determine one’s risk than the conventional method because it takes more specific factors about a patient into consideration.
The free tool, referred to as the “metabolic crystal ball,” was developed by Dr. Mark DeBoer from the University of Virginia School of Medicine, and his research partner at the University of Florida, Matthew Gurka. The pair hopes the calculator will lead more individuals to adjust their lifestyles in order lessen the risk for the two potentially fatal diseases.
“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,'” says DeBoer in a university news 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.”
The new tool looks at the same traditional factors physicians look at when evaluating a patient, but also takes gender, race, and ethnicity into account. Traditional factors include obesity, high blood pressure, high fasting triglycerides, low levels of HDL or “good” cholesterol, and high fasting blood sugar. When a patient matches three of the five factors, doctors typically diagnose them with “metabolic syndrome” and warn them that they’re more likely to suffer a major health condition.
But DeBoer says that method isn’t as strong. He points to African American men as an example, claiming they’re less likely to be diagnosed with metabolic syndrome, yet they’re still at a high risk of suffering from heart disease or diabetes.
“As is true in most processes in life, the reality is that this risk exists on a spectrum,” he says. “Someone who has values in each of these individual risk factors that are just below the cutoff still has more risk for future disease than somebody who has very low values.”
DeBoer, Gurka and a team of researchers looked at 13,000 people and using their calculator, determined that it was a better risk predictor than the individual risk factors by themselves. The release did not explain any details about the participants. An earlier study that examined fewer participants determined that the calculator’s predictions were on point with real cases of the three ailments discussed.
“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,” says DeBoer. “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 realizes there is an elevated risk, and to the patient, who hopefully can start taking some preventative steps.”
The research team hopes to publish exact cut-off values related to particular jumps in risk.
Click here to access the metabolic syndrome severity calculator.
The findings of the team’s study were published in the Journal of the American College of Cardiology.