Background: Aortic stenosis affects 1 in 50 adults over age 65 and is associated with significant morbidity and mortality. Machine learning has identified an association between right sided precordial U waves and moderate to severe aortic stenosis. No study has explored the role of ECG screening by primary care physicians for patients with unknown aortic stenosis status. Methods: A retrospective single center cohort analysis performed by non cardiologists identified right-sided precordial U waves on ECGs in fifty adults ages 65 to 89. Following identification, reviewers were unblinded to echocardiograms to determine whether there was an association between right sided precordial U waves and aortic stenosis severity. Fifty age and gender matched patients without right-sided precordial U waves comprised the control group. Results: Chi squared analysis revealed a significant association between right sided precordial U waves and severity of aortic stenosis (X = 16.77, df = 3, p < 0.001). Multinomial logistic regressions demonstrated no relationship between categorical SBP (< 125, 126 to 145, > 145) and aortic stenosis (p = 0.35), but increasing categorical age (65 to 73, 74 to 81, 82 to 89) was associated with moderate to severe aortic stenosis (p = 0.002). Conclusions: Our data highlights right sided precordial U wave identification by non cardiologists as a novel objective adjunct to the physical examination in detection of a medical condition which portends significant morbidity and mortality if left untreated. These findings motivate a prospective randomized clinical trial in the utility of right sided precordial U waves in screening for aortic stenosis in primary care settings.

The authors have declared no competing interest.

No funding was accessed or obtained in the execution of this study.

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Ethics committee/IRB of University of Southern California gave ethical approval for this work

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