In a groundbreaking study between Rambam Health Care Campus and the Mayo Clinic in Rochester, Minnesota, USA, researchers have ascertained the possibility of employing artificial intelligence to predict the chances of developing heart failure in patients suffering from inflammatory muscle diseases.
Results of a new, groundbreaking, collaborative study carried out by researchers at Rambam Health Care Campus (Rambam HCC), Haifa, and the Mayo Clinic, USA, show that by employing standard equipment available in many medical centers, it is possible to predict the chances of patients with inflammatory muscle diseases, developing heart failure, and the risk of dying from the disease.
This study involved comparing a group of 89 people who had a condition called immune myopathy and had undergone multiple electrocardiograms (ECGs) before or after the onset of their symptoms to a group of 113 people who did not have immune myopathy but were matched for age, sex, and risk for a type of heart disease called atherosclerotic cardiovascular disease (ASCVD). The ECGs from both groups were analyzed using an artificial intelligence (AI) algorithm, which calculated the probability of left ventricular dysfunction (LVD), or a problem with the left lower chamber of the heart. The researchers used the AI-ECG algorithm to see if it could accurately predict abnormalities in the heart’s function, as seen on an echocardiogram, in people with immune myopathy. They also looked at whether the AI-ECG algorithm could predict whether someone with immune myopathy would have problems with their heart and whether they were at higher risk for dying.
The results showed that the AI-ECG algorithm was able to accurately predict abnormalities in heart function in people with immune myopathy. They also found that people with immune myopathy who had a probability of dysfunction greater than 1% were 5 times more likely to have cardiac involvement, and 7 times more likely to die during follow-up.
The researchers conclude that the AI-ECG algorithm is a useful, low-cost tool for detecting and monitoring cardiac dysfunction and mortality in people with immune myopathy, and it may also have applications in other neuromuscular cardiomyopathies (conditions that affect the heart and muscles that control breathing).
Dr. Shahar Shelly, Head of the Neuromuscular Disease Clinic, and Clinical Electrophysiology at the Department of Neurology, Rambam HCC, led the study and maintains that it is a breakthrough and at the forefront of scientific research and provides a knowledge base for the early identification of patients at risk for heart failure. Shelly explains: “Ultimately, the use of this model will enable the provision of appropriate treatments at an early stage, even before the patient’s medical condition deteriorates—effectively preventing serious illness and even death.”
From a research point of view, according to Dr. Shelly, “Artificial intelligence-enhanced electrocardiography is a fast and accurate research tool that saves time and cost. Our research method opens the door to other hospital studies using electrocardiography as a research tool where echocardiography is not available to every patient.
“AI technology has accelerated dramatic changes in areas such as drug development and early identification of patients at high risk for intervention. This Rambam-Mayo Clinic research collaboration is ongoing, with many more projects in the pipeline.”