(Ivanhoe Newswire) -- Your heart is calling for help, and doctors may finally be able to answer. Approximately one million Americans have a heart attack each year. Now, subtle markers of heart damage have been found; hidden in plain sight.

According to a new study published in the September 28 edition of Science Translational Medicine, these markers could help doctors identify which heart attack patients have a high risk of dying soon.

Researchers from the University of Michigan, MIT, Harvard Medical School, and Brigham and Women's Hospital in Boston, found that the electrocardiogram (EKG) signals from many patients, who later suffered cardiovascular death, contained similar errant patterns. Until now, they were dismissed as noise or simply undetectable.

"There's information buried in the noise, and it's almost invisible because of the sheer volume of the data. But by using sophisticated computational techniques, we can separate what is truly noise from what is actually abnormal behavior that tells us how unstable the heart is," Zeeshan Syed, first author of the study and assistant professor in the University of Michigan Department of Electrical Engineering and Computer Science, was quoted as saying.

Typically, physicians only look at data from EKGs in seconds-long snapshots. "You can't ask a physician to look at 72-hours worth of EKG data, so people have focused on the things you can learn by looking at tiny pieces of it," John Guttag, professor of MIT's Computer Science and Artificial Intelligence Laboratory, was quoted as saying.

After his father suffered a heart attack, Syed worked with colleagues to develop new ways to search through the data using markers called "computational biomarkers". There are three different biomarkers; morphological variability, heart rate motifs and symbolic mismatch.

First, morphological variability is the amount of subtle variability in the shape of apparently normal-looking heartbeats over long periods of times. The second, heart rate motifs, refer to specific changes in the heart rate that reflect whether the heart is responding to nervous system signals as it should. Finally, symbolic mismatch measures how different a patient's long-term EKG signal is compared with those of other patients with similar clinical histories.

The findings could help match tens of thousands of cardiac patients with life-saving treatment in time.

During the months after a heart attack, patients are particularly vulnerable to sudden death due to irregular heart rhythms. According to the American Heart Association, more than a quarter of those who survive the initial attack, in certain age groups, end up dying of complications within a year.

These deaths could be prevented with medication or implantable defibrillators which can shock the heart back into rhythm. However, it's difficult to determine who needs them before it's too late, said Benjamin Scirica, a cardiologist at Brigham and Women's Hospital who was also involved in the study.

"Today's methods for determining which heart attack victims need the most aggressive treatments can identify some groups of patients at a high risk of complications. But they miss most of the deaths -- up to 70 percent of them," Syed was quoted as saying.

Results of the study showed that patients with at least one of the abnormalities were between two and three times more likely to die within 12 months. Adding all three techniques to doctor's current assessment tools allowed for prediction of 50 percent more deaths, with fewer false positives.

The new techniques use data that is already routinely collected during hospital visits, so putting them into practice would not raise costs.

SOURCE: Science Translational Medicine