Now a software that “predicts” sudden cardiac death
Sunday 22 October, 2017
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Now a software that “predicts” sudden cardiac death

Published On: Tue, Dec 23rd, 2014 | Cardiovascular / Cardiology | By BioNews

At Galway Hospital, in Ireland, a device is currently used to “predict” cardiac events in people at risk of sudden cardiacdeath. This technology was developed by a Mexican, and the city’s University patented it looking to sell it to specialized companies.

In 2013, the hospital cardiologists used this technology to diagnose and test its accuracy. The software is in the process of prototype and marketing.

In Ireland there are six million inhabitants and eight thousand of them are Mexicans. The researcher Antonio Aguilar is one of them, he went to that European country to visit family and learn English, and decided to stay to complete an engineering degree in electronics and continue with postgraduate studies. Four months ago he founded his own company of medical software for hospitals.

The company’s history begins with his PhD research: Method to diagnose patients at high risk of sudden cardiac death. “I decided to focus on sudden cardiac death because it is a condition that kills many people and is very difficult to predict.”

Through a scholarship obtained in a research institute of Galway, the electronics engineer began developing the algorithm that, by testing the patient, makes an electrocardiogram and record 15 minutes of the patient’s heartbeat. The algorithm processes this information, and analyzes through a statistical model if the patient is at risk of arrhythmia, which is the sign of sudden cardiac death.

“When there is less variability in the heartbeat of a patient, this indicates a problem. We have studied the electrocardiogram of many patients with diabetes and other cardiovascular diseases and heart rate variability is very different between ill and healthy people. A patient before suffering an arrhythmia has certain patterns which can be detected and the variability in heartbeat is lower. With this algorithm we can “predict” whether the patient will have an arrhythmia hours before it happens. ”

He used a database of 400 patients to “prove” the algorithm and diagnose patients at risk for arrhythmias.

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