02:58 GMT26 January 2021
Listen Live
    Get short URL
    0 63

    A group of researchers from Johns Hopkins University developed a 3D virtual heart model to help doctors find out whether a patient faces the risk of life-threatening arrhythmia and needs an invasive defibrillator implant.

    Cardiac arrhythmia is known as a condition, when the heartbeat is irregular, too fast or too slow. While most types of arrhythmia are not serious, some could be a signal of complications such as stroke, heart failure and even a cardiac arrest.

    To save the life of a patient at risk, doctors implant a small defibrillator to set the heart back to a normal rhythm. Most physicians use imprecise blood pumping measurements to decide which patients truly need an implant, which is, by the way, expensive and has its own health risks.

    The researchers from Johns Hopkins University found more accurate technology to make predictions on patients' hearts health.

    "Our virtual heart test significantly outperformed several existing clinical metrics in predicting future arrhythmic events," said Natalia Trayanova, the Murray B. Sachs professor of biomedical engineering. "This non-invasive and personalized virtual heart-risk assessment could help prevent sudden cardiac deaths and allow patients who are not at risk to avoid unnecessary defibrillator implantations," she explained.

    The study involved data from 41 patients who had previously survived a heart attack and received the implants after traditional tests. Using computer-modeling techniques, the researchers brought to life the geometrical replica of each patient's heart. In some cases, the virtual heart developed arrhythmia and in others it did not.

    The new tool, called a virtual-heart arrhythmia risk predictor (VARP), predicted arrhythmia occurrences in patients four-to-five times better than other existing clinical risk predictors, both non-invasive and invasive. In addition to eliminating unnecessary device implantations, Trayanova noted that this new risk prediction methodology can also be applied to patients who had prior heart damage but whose risk was not detected by old methods.

    "We demonstrated that VARP is better than any other arrhythmia prediction method that is out there," Trayanova said. Thus, VARP has the potential to save the lives of a much larger number of patients at risk.

    Heart Disease, risk, technology, health, US
    Community standardsDiscussion