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Risk of heart disease prediction needs updating

According to researchers at the Mayo Clinic, the present risk of prognosis methods in heart disease need to take account of more factors if they are

According to researchers at the Mayo Clinic, the present risk of prognosis methods in heart disease need to take account of more factors if they are to be useful in assessing a patient's future health. When someone has a heart attack or is at risk of having one what they want to know most of all is what the future might hold. Doctors can use the prediction tools and use to counsel them.

The team compared two commonly used heart disease prediction models - one is called TIMI, and it's based upon clinical trial data. The other, known as PREDICT, comes from whole population data. The researchers compared these in a group of people from Olmsted County, recording 1134 heart attacks over a 12 year period.

Put simply, PREDICT was more accurate in predicting future survival for those who'd had a heart attack. The researchers believe this is because it is based upon data from the general population and includes co-existing problems like hypertension and diabetes. They also find that adding information on the patient's ejection fraction - a measure of heart muscle strength - made the models even more accurate. The study should help doctors give heart patients better information about their future health, which will guide treatment and lifestyle decisions.


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