AI Screening Tool Speeds Heart Failure Diagnosis

Mayo Clinic researchers looking into heart failure diagnostic solutions have discovered that incorporating an AI-enabled screening tool was of great help to healthcare providers in their diagnosis of low left ventricular ejection fraction. In fact, a study found that clinics with high adoption levels of the tech had correctly diagnosed the condition on a more frequent basis than those opting out of using the tool.

Causing the amount of blood pumped out by the heart to drop off considerably, low left ventricular ejection fraction is triggered by weakening heart muscles, valve issues, inconsistent blood pressure levels, and/or residual damage from a heart attack. The condition is a major contributor to the startling statistic from the CDC that cites an annual heart failure rate of 6.2 million for U.S. adults. With early diagnosis being the main factor in an individual’s chance of survival and recovery, the AI tool in question is a recommended priority for heart care facilitators.

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"AI decision support tools have the potential to be very effective in aiding the diagnosis of serious health conditions before the onset of usual clinical symptoms, and may outperform traditional diagnostic approaches," said Dr. David Rushlow, MD, a Mayo Clinic physician and chair of family medicine for Mayo Clinic in the Midwest.

The Mayo Clinic’s study brought in clinicians from 48 different primary care practices. A group of 358 physicians as well as nurse practitioners and physician assistants, around half of whom ended up in the AI arm of the study through random selection, was amassed for the research.

The ECG results of some 22,641 patients from mid-2019 through early 2020 were the basis for the report’s findings.