Smartphone App To Find Heart Attack

A new smartphone application has been developed by scientists that predicts patients heart attack. This application is used mainly to identify the patients who are at a risk of dying from the heart attack. This application helps the doctors to identify if a cardiac patient could suffer a heart attack within the next three years and they can also know the severity of the patient’s condition.

The application was developed by Edinburgh University and Massachusetts University. Depends upon the patient’s condition, the application also tells which treatments are most suitable for the patient. It analyses a patient’s heart rate, Kidney function, Blood pressure and history of heart failures and produces an accurate result of potential risk of repeat heart attack and the kind of treatment that is required for the patient.

 

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Professor Keith fox, British heart foundation professor of Cardiology at Edinburgh University said that “before we developed this application, this kind of medical diagnosis is done only in a hospital. But now, with the help of this application, any paramedic (i.e.) any health care professional who works in emergency medical situation can do it outside a hospital”.

A survey says that one in five patients die due to heart attack within five years of their initial heart attack. So this application will be very useful to identify the patients at a risk of repeat heart attack. And also the patients can get better treatments and they can prevent themselves from the further attacks.

The application gets the data from Global Registry of Coronary Events (GRACE). It contains the details of more than 100,000 heart attack patients in 14 countries over ten years which includes the patients in Scotland and Belgium.  A paper called “Smartphone application to predict Heart attack risk” was released by the European Society of Cardiology Congress in Amsterdam.

The main intention for the development of this application is to minimize the residue and make the patient feel lesser risk