Internet crystal ball can predict heart disease, diabetes risk

Scientists have developed an internet crystal ball - a metabolic calculator that can predict a patients' risk of developing heart disease and diabetes more accurately than traditional methods.
The tool will prompt patients to make lifestyle changes that would spare them the suffering and expense of avoidable illnesses, researchers said.
"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,'" said Mark DeBoer, from University of Virginia in the US.
"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," said DeBoer.

Doctors usually predict risk for cardiovascular disease, type 2 diabetes and stroke by looking for five factors: obesity, high fasting triglycerides, high blood pressure, low HDL (good) cholesterol and high fasting blood sugar.
Patients with abnormalities in at least three of these are diagnosed as having metabolic syndrome and told that they are at elevated risk for future health problems.

The problem with that approach is that it is black-and-white, DeBoer said.
"As is true in most processes in life, the reality is that this risk exists on a spectrum. 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," he said.

The traditional approach also fails to consider variables such as race, ethnicity and gender.
On the other hand, the metabolic crystal ball, developed by DeBoer and Matthew Gurka from the University of Florida in the US, weights the traditional risk factors and also takes into account race, gender and ethnicity to produce an easy-to-understand metabolic severity score.
A small study previously found that the online calculator's predictions lined up well with actual cases of cardiovascular disease and diabetes, and the new study further bears that out.
The study looked, retroactively, at outcomes in more than 13,000 people and found that the tool was a better risk predictor than the 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 realizes there is an elevated risk, and to the patient, who hopefully can start taking some preventative steps," he said.