The AI ​​algorithm helps in the early detection of the low ejection fraction


An artificial intelligence (AI) algorithm that uses electrocardiography data may help increase the diagnosis of low ejection fraction (EF), according to a study published online May 6 in Nature medicine.

Xiaoxi Yao, Ph.D., of the Mayo Clinic in Rochester, Minnesota, and colleagues randomly assigned 120 primary care teams, including 358 clinicians, to (access to AI outcomes with positive outcomes indicating a high probability of low EF; 181 clinicians) or control (regular care; 177 clinicians) in a pragmatic trial at 45 clinics and hospitals. A total of 22,641 with echocardiography performed as part of routine care (11,573 in the intervention group; 11,068 controls).

The researchers found positive AI results in 6.0 percent of patients in both arms. Clinicians in the intervention group obtained more echocardiograms for patients with positive outcomes (49.6 versus 38.1 percent), but the use of echocardiograms was similar in the overall cohort (19.2 versus 18.2 percent). He low EF increased with intervention in the overall cohort (2.1 versus 1.6 percent; odds ratio, 1.32) and among patients with positive outcomes (19.5 versus 14.5 percent; odds ratio, 1.43).

“AI intervention increased the diagnosis of low ejection fraction by 32% relative to usual care. Among patients with a positive AI result, the relative increase in diagnosis was 43%. % “Yao said in a statement. “To put it in absolute terms, for every 1,000 patients selected, the detection of AI gave five new diagnoses of low ejection fraction compared to usual care.”

Mayo Clinic has licensed the AI-ECG algorithm to EKO, a manufacturer of digital stethoscopes with embedded ECG electrodes.

The trial demonstrates the early detection of AI-guided heart disease in routine practice

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Citation: AI Algorithm Helps Early Detection of Low Ejection Fraction (2021, May 28) Retrieved May 28, 2021 at aids-early-ejection.html

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