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Algorithm Predicts Risk of Deadly Heart Condition

Combining a wealth of information derived from previous studies with data from more than 500 patients, an international team led by researchers from Johns Hopkins has developed a computer-based set of rules that more accurately predicts when patients with a rare heart condition might benefit—or not—from lifesaving implanted defibrillators.

The new research, published in the European Heart Journal, provides physicians with a risk prediction tool that will identify patients most likely to benefit from the protection provided by an implantable defibrillator while preventing one-fifth from receiving unnecessary—and potentially risky—surgery to place the devices.

An estimated one in 5,000 people has arrhythmogenic right ventricular cardiomyopathy (ARVC), a complex, multigene, inherited disease of the lower heart chambers that can cause deadly arrhythmias, or irregular heartbeats. Although rare, it’s a very frequent cause of sudden death in young adults, according to the new study’s leaders. The average age of diagnosis is 31, although it can emerge from adolescence through middle age.

ARVC can be effectively managed in many cases with an implantable cardioverter-defibrillator (ICD). But these devices come with risks and side effects, according to co-lead investigator Cynthia James, a certified genetic counselor.

The devices may deliver inappropriate shocks when patients aren’t experiencing life-threatening arrhythmias. And the ICD itself or pacemaker leads may fail over time, necessitating replacement with surgery. Infections brought on by these devices—and even just wearing out the device’s battery with time—also require replacement, hospitalizations and expense, she adds. “Because patients develop this condition at such a young age, they typically need several ICD replacements over the course of their lives,” says James. “For ARVC patients, getting an ICD is a big decision with serious consequences.”

“If someone is at risk of sudden cardiac death, you don’t want to miss the chance of putting in a lifesaving device. But you also don’t want to put it in if that risk is not worth taking,” says Johns Hopkins cardiologist Hugh Calkins.

The new algorithm was developed, the researchers say, because while physicians are generally in agreement that patients who experience a life-threatening arrhythmia qualify for an ICD, it’s been unclear whether patients who haven’t yet experienced this event should get one for prevention.

When the researchers compared their prediction accuracy rates with outcomes using a current consensus-based ICD placement algorithm, they found that about 20.6 percent of recommended ICD placements would have likely been unnecessary.

“This new model can help doctors and patients decide better if an ICD is warranted on a case-by-case basis,” says Calkins. The team has also developed a free app that will allow doctors and patients to rapidly input medical data to calculate personal risk, easing the decision-making process.