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New method to reveal heart attack risk

New method to reveal heart attack risk

London : Researchers have developed a new method to calculate your 10-year risk for heart attack with greater precision than traditional risk factors alone.

Levels of cholesterol and triglycerides, body mass index (BMI), smoking habits and blood pressure are considered as traditional risk factors for cardiovascular disease.

There are several risk prediction calculators available.

However, the use of risk prediction calculators has declined in the primary care setting because the currently available calculators only explain a modest proportion of the incidence.

For myocardial infarction or heart attack, it is estimated that 15-20 per cent of the patients had none of the traditional risk factors and would be classified as “low risk”.

“Our study showed that by measuring a combination of five different micro RNAs and adding this information to the traditional risk factors for cardiovascular disease, we could identify those that were going to experience a myocardial infarction with considerably improved precision”, said study first author Anja Bye from Norwegian University of Science and Technology (NTNU).

The study was published in Journal of Molecular and Cellular Cardiology.
The researchers designed this study to explore the possibility of a new type of bio marker called circulating micro RNAs, to predict 10-year risk for myocardial infarction.

They included 212 participants (40-70 years) from the Nord-Trondelag Health Study 2 (HUNT2, blood collected in 1996) who either died from heart attack within 10 years or remained healthy at the time of HUNT3 (2006).

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supriya kashyap

supriya kashyap

Supriya Kashyap Joined Medical Dialogue as Reporter in 2015 . she covers all the medical specialty news in different medical categories. She also covers the Medical guidelines, Medical Journals, rare medical surgeries as well as all the updates in medical filed. She is a graduate from Delhi University. She can be contacted at Contact no. 011-43720751
Source: self

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