Abbreviations:
ECG (Electrocardiogram)Let's begin with our thanks to Dr. Braillon for reading our article
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and generating his perceptive comments. We appreciate his point of view and partially agree with him. Bayesian statistics show that, in low-risk populations, testing generates more false positives than true positives, raising the question of the necessity of screening a population with a low risk of disease. To this, we have several responses.First, the senior author's professional experiences—including screening pilots in the US Air Force—led to a great deal of empathy for individuals who were excluded from activities important to them. On the other hand, those who have been involved with athletics are aware of the palpable fear of sudden cardiac death generated by the public presentation of such an event during athletic competition. Just recently, the collapse of Damar Hamlin on live television during a professional football match stoked much concern and fear. We now know that an underlying abnormality did not contribute to his collapse, but it was consistently part of the conversation in the early days surrounding the event. Add to this the strong emotions of family members of young athletes who have actually died playing sports and we can understand how these forces motivate efforts to engage modern medical tools to diagnose underlying pathology to prevent sudden cardiac death. Attempting to use biostatistics to moderate these forces is nearly impossible, so at Stanford, we took another approach.
When the Stanford Athletic Department mandated electrocardiograms (ECGs) for all athletes in 2010, we decided not to disagree but to see that it was done “correctly.” We collected thousands of digital ECGs to confirm that there are “abnormalities” in the ECGs of athletes due to physiological adaptations.
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We applied data to reduce the false positive rate from over 20% to <5%.3
We nearly perfected an inexpensive computer-based ECG system that includes factors like athletic status, symptoms, and cardiac risk factors to appear on the ECG tracing.4
This system was so efficient that ECGs were available quickly and properly read. It was “too successful” and became the standard of care, lauded by parents and appreciated by our sports medicine colleagues.Although our approach became successful clinically, our main goal has been to improve the ECG as a screening tool by enhancing the criteria used to diagnose abnormalities through evidence-based research.
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The currently applied national and international criteria are largely qualitative and empirical.6
“Guide to the Female Student Athlete ECG” is our first attempt to use digital quantitative techniques to improve the overall discriminative characteristics of the ECG, and even improve sensitivity.1
We do not suggest that our findings are ready for “prime time,” but require validation. We dream of a future where a simple smartphone attachment with minimal ECG leads, and a digital app that can be read by trainers, flashes green, yellow, or red for the need for a 12-lead ECG. This democratization of the ECG would make it available to all, not just the “worried wealthy-well” as Dr. Braillon points out.References
- Guide to the female student athlete ECG: a comprehensive study of 3466 young, racially diverse athletes.Am J Med. 2022; 135: 1478-1487.e4
- Adding an electrocardiogram to the pre-participation examination in competitive athletes: a systematic review.Curr Probl Cardiol. 2009; 34: 586-662
- Interpretation of the electrocardiogram of young athletes.Circulation. 2011; 124: 746-757
- Limitations of current AHA guidelines and proposal of new guidelines for the preparticipation examination of athletes.Clin J Sport Med. 2015; 25: 472-477
- Limitations of electrocardiography for detecting left ventricular hypertrophy or concentric remodeling in athletes.Am J Med. 2020; 133: 123-132.e8
- International recommendations for electrocardiographic interpretation in athletes.Eur Heart J. 2018; 39: 1466-1480
Article info
Publication history
Accepted:
January 24,
2023
Received:
January 24,
2023
Footnotes
Funding: The authors have not declared a specific grant for this research from any funding agency in the public, commercial, or not-for-profit sectors.
Conflicts of Interests: The authors report no conflicts of interest except for VFF, who participated in the algorithms for ECG analysis and was part owner of the company manufacturing the ECG recorders.
Authorship: All authors had access to the data and played a role in writing/revising the text.
Identification
Copyright
© 2023 Elsevier Inc. All rights reserved.
