Key result
Collegiate athletes show ECG changes, yet ~83% fall within normal ranges derived from non-athletes.
Why the study?
Existing athlete ECG consensus criteria are not based on established correlation with disease states, and comparative data between athletes and non-athlete controls are lacking.
Does Z-score-based analysis of ECG variables improve the identification of true cardiac abnormalities compared to traditional criteria in young athletes?
Observational (n=7,206)
Yes
Does Z-score-based analysis of ECG variables improve the identification of true cardiac abnormalities compared to traditional criteria in young athletes?
Using Z-scores derived from a normal population for ECG screening in young athletes may reduce false-positive LVH diagnoses and unnecessary secondary testing compared to traditional criteria.
May reduce false-positive LVH calls in athletes; leaves open whether Z-scores outperform traditional criteria for abnormality detection.
BACKGROUND: Electrocardiograms (ECGs) in athletes commonly reveal findings related to physiologic adaptations to exercise, that may be difficult to discern from true underlying cardiovascular abnormalities. North American and European societies have published consensus statements for normal, borderline, and abnormal ECG findings for athletes, but these criteria are not based on established correlation with disease states. Additionally, data comparing ECG findings in athletes to non-athlete control subjects are lacking. Our objective was to compare the ECGs of collegiate athletes and non-athlete controls using Z-scores for digital ECG variables to better identify significant differences between the groups and to evaluate the ECG variables in athletes falling outside the normal range. METHODS: Values for 102 digital ECG variables on 7206 subjects aged 17-22 years, including 672 athletes, from Hawaii Pacific Health, University of Hawaii, and Rady Children's Hospital San Diego were obtained through retrospective review. Age and sex-specific Z-scores for ECG variables were derived from normal subjects and used to assess the range of values for specific ECG variables in young athletes. Athletes with abnormal ECGs were referred to cardiology consultation and/or echocardiogram. RESULTS: Athletes had slower heart rate, longer PR interval, more rightward QRS axis, longer QRS duration but shorter QTc duration, larger amplitude and area of T waves, prevalent R' waves in V1, and higher values of variables traditionally associated with left ventricular hypertrophy (LVH): amplitudes of S waves (leads V1-V2), Q waves (V6, III) and R waves (II, V5, V6). Z-scores of these ECG variables in 558 (83%) of the athletes fell within - 2.5 and 2.5 range derived from the normal population dataset, and 60 (8.9%) athletes had a Z-score outside the - 3 to 3 range. While 191 (28.4%) athletes met traditional voltage criteria for diagnosis of LVH on ECG, only 53 athletes (7.9%) had Z-scores outside the range of -2.5 to 2.5 for both S amplitude in leads V1-V2 and R amplitude in leads V5-6. Only one athlete was diagnosed with hypertrophic cardiomyopathy with a Z-score of R wave in V6 of 2.34 and T wave in V6 of -5.94. CONCLUSION: The use of Z-scores derived from a normal population may provide more precise screening to define cardiac abnormalities in young athletes and reduce unnecessary secondary testing, restrictions and concern.
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Park et al. (2024) conducted an observational in Cardiovascular screening in athletes (n=7,206). Collegiate athlete status vs. Non-athlete controls was evaluated on Proportion of athletes with ECG variable Z-scores within the normal range (-2.5 to 2.5) derived from non-athlete controls. Collegiate athlete status was associated with significant ECG changes, yet 83% of athletes had Z-scores within the normal range (-2.5 to 2.5) derived from non-athletes.
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