Credit: Mayo Clinic
A new artificial intelligence (AI) algorithm that identifies a cardiac dysfunction from a single-lead ECG can also predict long-term patient survival after heart surgery, according to new research from the Mayo Clinic.
The study, published in Mayo Clinic Proceedings, finds that an algorithm that has previously shown that it can detect patients with reduced left ventricular ejection fraction can also predict long-term mortality after cardiac surgery, making it a potentially valuable tool for assessing risk as patients and their healthcare professionals are considering surgery.
“Our study finds that there is a clear link between long-term mortality and a positive AI ECG screen for reduced ejection fraction among patients without apparent severe cardiomyopathy,” said Mohamad Alkhouli, MD, a Mayo Clinic cardiologist and senior study author. “This association was consistent among patients undergoing valve, coronary bypass or valve and coronary bypass surgery.”
The retrospective study involved reviews of 20,627 patients at the Mayo Clinic in Rochester from 1993 to 2019. Patients underwent coronary artery bypass grafting, valve surgery, or both, and had a left ventricular ejection fraction of more than 35%. Of these patients, 17,125 had a normal AI ECG monitor and 3,502 had an abnormal monitor. Patients with an abnormal screen tended to be older with multiple comorbidities.
The algorithm was applied to the most recent ECG patients had within 30 days before surgery. Baseline characteristics as well as hospital, 30-day, and long-term mortality data were extracted from the Mayo Clinic database for cardiac surgery.
The probability of survival after five years was 86.2% for patients with a normal screen versus 71.4% for those with an abnormal screen. The 10-year probability of survival was 68.2% and 45.1% for the two groups, respectively.
“Our study documented the prognostic value of the algorithm to predict long-term mortality from all causes after cardiac surgery,” says Dr. Alcohol. “The analysis showed that an abnormal AI screen was associated with a 30% increase in long-term mortality after valve or coronary bypass surgery. For clinicians, this may help with risk stratification of patients referred for surgery and facilitate co-decision.”
The study is believed to be the first large-scale research exploring the usefulness of single-ECG algorithms to better predict the results of cardiac surgery. Because the algorithm uses a routine and relatively inexpensive test, it can be widely used after validation.
Further research is underway to determine if the information from the algorithms can improve diagnosis, decision making and clinical outcomes. The use of AI-based testing in cardiology is becoming more common in academic health centers, and the results of this study may encourage more providers to consider their clinical significance.
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Abdulah A. Mahayni et al., Electrocardiography-based artificial intelligence algorithm helps predict long-term mortality after cardiac surgery, Mayo Clinic Proceedings (2021). DOI: 10.1016 / j.mayocp.2021.06.024
Citation: AI Algorithm Can Predict Long-Term Patient Survival After Cardiac Surgery, Study Findings (2021, December 1) Retrieved December 1, 2021 from https://ift.tt/3lqgC4H .html
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