Incorporating an electrocardiogram (ECG) during pre-participation screening for athletes has demonstrated a reduction in incidence of sudden cardiac death (SCD); however, it remains controversial in the United States due to minimal usage and high false-positive readings. New research presented this week suggests this is due to the challenges in the accuracy and reliability of physicians' ability to read ECGs.
Francis G. O'Connor MD, MPH, Medical Director, Consortium for Health And Military Performance (CHAMP) and Professor of Military and Emergency Medicine, Uniformed Services University of the Health Sciences, will present research entitled, "Reliability and validity of clinician electrocardiogram interpretation using the European Society of Cardiology criteria for pre-participation screening" on Friday, April 19, 2013 at the American Medical Society for Sports Medicine's 22nd Annual Meeting in San Diego, Ca. The study was conducted in conjunction with AMSSM member Charles Magee, MD, MPH, and other researchers of the Uniformed Services University of the Health Sciences.
Both cardiologists and primary care physicians, including primary care sports medicine physicians, were asked to interpret 85 different ECGs using the European Society of Cardiology (ESC) guidelines. Notably, 30 percent of the ECGs showed abnormal common disorders that cause sudden cardiac death. Agreement among physicians was moderate, demonstrating that interpretation of ECGs in a population representative of athletes by board certified primary care and cardiology specialists is limited.
Currently, ECGs are not a required component of mass pre-participation screenings for athletes; however, adding this screening to the pre-participation exams could potentially help identify predictors of sudden cardiac death, the number one killer of athletes. Dr. O'Connor stated that "improvement in diagnostic accuracy of ECG interpretation is warranted before considering the recommendation of routine ECG screening in athletes." Dr. O'Connor added, "Until then, we need to recognize that identifying abnormal from normal is not as easy as it may seem."