Dr. Craig Basman discusses new life-saving technology and the variables that can predict sudden cardiac events. Half of those who suffer cardiac arrest experience a telling symptom 24 hours before the incident, according to a study recently published in The Lancet Digital Health journal. This warning symptom was different in men and in women, researchers from Smidt Heart Institute found; the institute is located in the Cedars Sinai Medical Center in Los Angeles. For women, shortness of breath was the symptom that preceded an impending cardiac arrest, while for men, chest pain was the prominent complaint. SKIPPING THE SALT CAN REDUCE HEART DISEASE RISK BY ALMOST 20%, STUDY FINDS: 'KNOW WHAT YOU ARE CONSUMING' Sweating and seizure-like activity occurred in smaller subgroups of both genders, the researchers noted.

A new artificial intelligence-based approach can predict, significantly more accurately than a doctor, if and when a patient could die of cardiac arrest. The technology, built on raw images of patient's diseased hearts and patient backgrounds, stands to revolutionize clinical decision making and increase survival from sudden and lethal cardiac arrhythmias, one of medicine's deadliest and most puzzling conditions. The work, led by Johns Hopkins University researchers, is detailed on April 7, 2022, in Nature Cardiovascular Research. "Sudden cardiac death caused by arrhythmia accounts for as many as 20 percent of all deaths worldwide and we know little about why it's happening or how to tell who's at risk," said senior author Natalia Trayanova, the Murray B. Sachs professor of Biomedical Engineering and Medicine. "There are patients who may be at low risk of sudden cardiac death getting defibrillators that they might not need and then there are high-risk patients that aren't getting the treatment they need and could die in the prime of their life. What our algorithm can do is determine who is at risk for cardiac death and when it will occur, allowing doctors to decide exactly what needs to be done."