The Athlete’s ECG

Riess Jan¹, Alba Schmidt Elisa¹, Niederseer David^1,2,3
1 Hochgebirgsklinik, Medicine Campus Davos, Davos, Switzerland
2 Center of Translational and Experimental Cardiology (CTEC), Department of Cardiology, University Heart Center Zurich, ­University Hospital Zurich, University of Zurich, Zurich, Switzerland
3 Christine Kühne-Center for Allergy Research and Education (CK-CARE), Medicine Campus Davos, Davos, Switzerland

Introduction

Sudden cardiac death (SCD) is the leading non-traumatic cause of mortality in athletes under the age of 35 [1,2]. The most common underlying causes are cardiomyopathies and primary electrical disorders, which often remain clinically silent until a fatal event occurs [3]. Accordingly, symptom-based diagnostic strategies are inadequate for prevention. Preparticipation screening programs in both professional and amateur sports aim to detect athletes at-risk before the onset of clinical manifestations. In this setting, the 12-lead resting electrocardiogram (ECG) has emerged as a cost-effective, portable, and widely accessible screening tool. Historically, however, the ECG was viewed with scepticism due to concerns about its limited specificity. Critics pointed to high false-positive rates, unnecessary downstream testing, psychological stress, and unwarranted disqualification from competition. These concerns resulted in part out of a lack of standardized interpretation criteria and the fact that ECGs were often assessed by general cardiologists or sports physicians unfamiliar with the physiological adaptations seen in athletes, relying instead on criteria designed for the general population. A paradigm shift occurred with data from the Veneto region of Italy, where a systematic, ECG-based screening program of over 33,000 athletes conducted over 25 years led to a 90% reduction in SCD incidence – from 3.6 to 0.4 per 100,000 athletes per year [4]. These findings support the premise that early, asymptomatic stages of inherited cardiomyopathies and arrhythmogenic disorders often produce characteristic ECG abnormalities – well before the onset of clinical symptoms. For example, abnormal ECG findings are seen in approximately 95% of individuals with hypertrophic cardiomyopathy (HCM) and in 80% of those with arrhythmogenic cardiomyopathy (ACM; previously referred to as arrhythmogenic right ventricular cardiomyopathy, ARVC) [5,6]. Despite its demonstrated value, ECG interpretation in athletes remains complex. Approximately half of all healthy athletes exhibit ECG changes that reflect physiological cardiac remodeling or autonomic adaptation to regular training, typically defined as more than 4 hours per week [7]. These changes vary according to age, sex, ethnicity, training load, and the type of sport practiced. Moreover, distinct sport-specific ECG patterns have been described. Endurance sports such as cycling, rowing, or long-distance running are more often associated with bradycardia, increased QRS voltages, and repolarization changes due to volume loading and vagal tone [8]. In contrast, athletes engaged in static or high-intensity sports (e.g., weightlifting, sprinting) may exhibit different ECG profiles reflecting pressure overload and sympathetic predominance. This article aims to provide a concise and clinically applicable overview to support accurate ECG interpretation in athletes, based on the latest international consensus criteria.

International Criteria

Efforts to standardize ECG interpretation in athletes evolved significantly over the past two decades. The European Society of Cardiology (ESC) published its first consensus statement on cardiovascular screening in young athletes in 2005 [9]. Central to these recommendations was a list of ECG findings considered potentially pathological intended to guide clinicians in deciding which athletes required further diagnostic evaluation. However, real-world application soon revealed substantial limitations: as many as 50% of athlete ECGs were classified as abnormal, leading to unnecessary investigations and undermining the efficiency of screening programs. To improve specificity while accounting for ethnic variation and cost-effectiveness, the criteria were revised in 2010 and again in 2013 with the introduction of the “Seattle Criteria” [10,11]. These refinements markedly reduced false-positive rates, particularly among Black athletes. For example, specificity improved from 40.3% to 82.4% in Black athletes, and from 73.8% to 94.1% in White athletes, without compromising sensitivity for detecting serious cardiac conditions [12]. A further milestone was reached in 2017 with the publication of the “International Recommendations for ECG Interpretation in Athletes,” developed through transatlantic collaboration [13]. These guidelines introduced a simplified color-coded classification system, green (physiological), yellow (borderline), and red (pathological), to help clinicians quickly distinguish benign from concerning findings (Figure 1). Notably, a “juvenile pattern” was also defined for athletes under 16 years of age to avoid overinterpretation in this age group. The implementation of the International Criteria has led to a measurable improvement in screening accuracy [14]. In a validation study involving over 11,000 adolescent football players, the proportion of ECGs flagged as pathological decreased by 57% compared to the Seattle Criteria (from 4.3% to 1.9%) [15]. T-wave inversions emerged as the most common abnormal finding, accounting for nearly half of 1.3%, reflecting greater diagnostic precision. In the following sections, physiological, borderline, and pathological ECG changes will be presented according to the 2017 international recommendations, which remain the most current and widely accepted criteria for athlete ECG interpretation.

Physiological ECG Findings in Athletes

Common benign findings include sinus bradycardia, often with resting heart rates as low as 30 beats per minute, and sinus arrhythmia, both reflecting enhanced vagal tone. Junctional or ectopic atrial rhythms may also occur intermittently in well-trained individuals without pathological significance. Notably, junctional rhythms can present with atrioventricular (AV) dissociation when the sinus rate is slower than the junctional focus. This phenomenon should not be misinterpreted as complete AV block. Mild physical exertion typically results in an increased sinus rate, restoring AV synchrony and resolving the dissociation. Mild conduction delays such as first-degree AV block or Mobitz type I second-degree AV block are frequently observed and do not typically warrant further investigation.
Similarly, an incomplete right bundle branch block is considered a normal adaptation related to increased right ventricular size and wall stress. Isolated voltage criteria for left or right ventricular hypertrophy, in the absence of associated pathological findings, are attributed to physiological enlargement of the cardiac chambers and myocardial mass and are not independently indicative of structural heart disease. A notched QRS complex in lead V1 is not uncommon and generally reflects benign conduction heterogeneity in trained hearts. Age and ethnicity also influence repolarization patterns.
While T-wave inversions are generally considered normal in leads aVR, III, and V1, they may also appear in leads V1 to V3 in younger athletes (Figure 2). An age threshold of 16 years is commonly used to define this so-called “juvenile pattern”. In this context, such repolarization changes are typically considered benign and do not necessarily suggest underlying cardiac pathology. In Black athletes, T-wave inversions in leads V1 to V4, particularly when accompanied by J-point elevation and convex ST-segment elevation, are also considered a normal repolarization variant. This pattern, present in up to 12%, is typically benign and may normalize with detraining.
Early repolarization, defined by J-point elevation with concave ST-segment elevation and a peaked T wave, is a common ECG finding in athletes. It is present in up to 45% of Caucasian athletes and in 63% to 91% of Black athletes of African-Caribbean descent. This pattern typically appears in the lateral leads V5 and V6 and is more prevalent in males and in those with ECG criteria for left ventricular hypertrophy. Awareness of these physiological ECG features, and their variation by age, sex, ethnicity, and training status, is crucial to avoid overdiagnosis and to ensure the accuracy of athlete-specific screening.

Borderline ECG Findings in Athletes

Certain ECG findings are classified as borderline – that is, neither clearly physiological nor definitively pathological. According to current criteria, these findings merit further evaluation only when two or more appear in combination. This threshold has significantly reduced false-positive classifications in validation studies. Borderline findings include:

• Marked axis deviation, such as a leftward QRS axis beyond –30° (exaggerated leftward axis) or a right axis >120°
• Electrical signs of atrial enlargement, including right, left, or biatrial patterns
• Complete right bundle branch block (QRS duration
  ≥120 ms)

The presence of any one of these findings in isolation, even if accompanied by otherwise physiological ECG changes related to training, does not warrant further investigation in an asymptomatic athlete without a family history of premature cardiac disease or sudden cardiac death. In such cases, these patterns are typically interpreted as benign variants within the spectrum of exercise-induced electrical adaptation. If more than one borderline finding is present, a further cardiological work-up is recommended.

Abnormal ECG Findings Suggestive of Pathology

In contrast to physiological and borderline ECG variants, certain electrical abnormalities are considered clearly pathological and should prompt further diagnostic work-up to exclude underlying structural or electrical heart disease, particularly in athletes with suggestive symptoms or a positive family history of premature SCD. A detailed medical history is essential. Previous episodes of syncope or seizures deserve special attention, particularly if exertional or postpartum in timing, as well as to family history of exertional syncope, epilepsy of unclear cause, unexplained motor vehicle accidents or drowning, and sudden death before the age of 50.
Before addressing abnormalities within the individual ECG segments (Figure 3), it is important to briefly consider bradycardic and tachycardic rhythms. Sinus bradycardia with a resting heart rate below 30 beats per minute (bpm) should prompt further evaluation. Likewise, first-degree AV block with a PR interval ≥ 400 ms, Mobitz type II AV block, and third-degree AV block are considered pathological and must be assessed accordingly. Sinus tachycardia with heart rates exceeding 120 bpm should initially be interpreted with caution, as it may result from anxiety or recent exertion. In such cases, repeating the ECG under more controlled, resting conditions is recommended. However, in the presence of other forms of tachycardia, including supraventricular or ventricular tachyarrhythmias, comprehensive cardiological evaluation is always indicated.

Similarly, the presence of more than one premature ventricular contraction (PVC) on a resting ECG is considered abnormal. In 24-hour Holter monitoring, a PVC burden of ≥ 2000 per day, or an increase in ectopy during exercise, should prompt a detailed work-up, including cardiac magnetic resonance imaging (MRI) with late gadolinium enhancement and, if indicated, invasive electrophysiological testing. Studies have shown that up to 30% of athletes with frequent ventricular ectopy have an underlying structural cardiac abnormality (16).
Pathological Q waves are defined as having a Q/R ratio ≥ 0.25 or a Q-wave duration ≥ 40 ms in two or more contiguous leads. As a reminder, small Q waves in the left lateral leads (I and aVL) are considered normal, as septal depolarization typically originates from the left bundle branch. Pathological Q waves findings should raise suspicion for previous myocardial injury or cardiomyopathy and prompt imaging with echocardiography. It is important to note that Q waves in leads V1-V2 mimicking a septal infarct pattern, may result from incorrect lead placement, and the ECG might be repeated with proper electrode positioning before drawing conclusions.
Complete left bundle branch block and general intraventricular conduction delay with a QRS duration ≥ 140 ms are abnormal and require comprehensive assessment, including echocardiography and cardiac MRI with tissue characterization. Signs of ventricular pre-excitation, such as a delta wave and short PR interval, require structured risk stratification, even in asymptomatic athletes. Non-invasive testing should begin with an exercise ECG; abrupt loss of pre-excitation at higher heart rates suggests a low-risk accessory pathway. Intermittent pre-excitation during sinus rhythm on a resting ECG is also generally considered a low-risk feature. In all other cases, further evaluation with echocardiography and, if indicated, electrophysiological testing is recommended. However, according to the 2024 Heart Rhythm Society consensus statement, a general restriction from sports is not required, as available evidence does not support a clearly elevated risk of life-threatening arrhythmias during exercise [17].
ST-segment depression greater than 0.05 mV (0.5 mm) in two or more contiguous leads is never a physiological finding of training adaptation and always warrants further evaluation. T-wave inversions (TWI) are of particular concern when present in the lateral leads (I, aVL, V5–V6), irrespective of ethnicity, as they may indicate underlying cardiomyopathy. Deep TWI ≥ 1 mm in two or more contiguous leads, excluding aVR, lead III, and V1, are considered abnormal when located in the anterior, lateral, inferolateral, or inferior territories. In such cases, cardiac MRI should be considered the standard of care to rule out apical forms of hypertrophic cardiomyopathy, which may not be reliably detected by trans­thoracic echocardiography. TWI extending beyond lead V2 in athletes aged 16 years or older, especially if not accompanied by ST-segment elevation or if associated with ST-segment depression, may indicate ACM. Additional ECG features supporting this diagnosis include low limb-lead voltages, a delayed upstroke of the S wave, frequent ventricular ectopy, and the presence of an epsilon wave. A positive T wave in lead aVR in combination with T-wave inversion in V5–V6 is also suggestive of apical pathology of the left ventricle.
A prolonged corrected QT interval (QTc) is another key abnormal finding. A QTc ≥ 470 ms in male athletes and ≥ 480 ms in female athletes, measured using Bazett’s formula in leads II and V5, excluding low-amplitude U waves, should trigger further evaluation, even in the absence of symptoms or family history. Since Bazett’s formula tends to underestimate QTc at low heart rates (< 50 bpm) and overestimate it at high heart rates (> 90 bpm), a repeat ECG after light aerobic activity or prolonged rest, respectively, may help obtain a more accurate baseline. Alternatively, the Fridericia formula might be used to calculate QTc.
Finally, the Brugada ECG pattern must be carefully distinguished. A type 1 Brugada pattern, defined by coved ST-segment elevation ≥ 2 mm, an rSr’ pattern, and T-wave inversion in leads V1–V3, is considered abnormal and requires further evaluation. In contrast, a type 2 Brugada pattern is non-specific; if identified, the ECG should be repeated with leads V1 and V2 placed in higher intercostal spaces. If a type 1 pattern does not emerge and no suggestive clinical history is present, no further testing is typically required.

Practical Implications

There is no doubt that current ECG interpretation criteria reflect the best available evidence to date, but they also remain a work in progress. Numerous unresolved questions persist and will require ongoing investigation. From a clinical perspective, key considerations are particularly relevant in daily practice: In athletes aged 30 and above, coronary artery disease is now the most common cause of SCD [18]. Although the resting ECG has limited sensitivity for detecting ischemic heart disease, findings such as T-wave inversion, pathological Q waves, ST-segment depression, bundle branch blocks, abnormal R-wave progression, left anterior hemiblock, and atrial fibrillation should prompt targeted ischemia testing.
Attention should be paid to T-wave inversions, especially in the inferolateral leads (Figure 4). When present, further diagnostic testing, such as cardiac MRI, exercise ECG, and Holter monitoring, is warranted. This is particularly important in athletes with borderline left ventricular hypertrophy, such as men with a maximal wall thickness between 13 and 16 mm and no evidence of late gadolinium enhancement, where the diagnosis of HCM may remain uncertain. In these cases, the presence of ventricular arrhythmias during exertion or on Holter monitoring may provide additional diagnostic clues and assist in risk stratification. A similar approach applies to anterior T-wave inversions. In non-Black athletes aged 16 years or older, T-wave inversion beyond lead V2 should prompt further evaluation due to the possibility of overlap with ACM. In this context, associated features such as J-point elevation, convex ST-segment elevation, or biphasic T waves may support a physiological training effect. In contrast, the absence of J-point elevation or the presence of concurrent ST-segment depression should heighten concern for underlying pathology. Crucially, in many inherited cardiomyopathies, including HCM, ACM, and dilated cardiomyopathy, electrocardiographic abnormalities may precede overt structural changes or the onset of heart failure. In athletes with suspicious ECG changes but initially negative imaging and testing, annual follow-up is strongly recommended, even after retirement from competitive sport.

Limitations

Several limitations of current athlete ECG interpretation criteria must be acknowledged. First, the international recommendations date back to 2017 and are now nearly a decade old. Although still widely applied, they do not incorporate recent advances in computational analysis or novel data sources. Artificial intelligence and machine learning, despite their increasing relevance in cardiovascular diagnostics, have yet to be systematically integrated into athlete ECG interpretation. Future and currently ongoing revisions will need to address this gap and evaluate how artificial intelligence might improve both diagnostic accuracy and workflow efficiency. Furthermore, current ECG-based screening relies almost exclusively on electrocardiographic findings, with limited integration of additional biomarkers or imaging parameters. A more comprehensive, multimodal approach could further enhance risk stratification.
The dichotomous categorization of athletes into “White” and “Black” remains a major conceptual limitation. It fails to capture the complex and heterogeneous nature of global athletic populations, including individuals of mixed-race or multiethnic backgrounds. Moreover, recent data suggest that repolarization variants differ significantly even within broad ethnic labels, for example, between athletes of West, Central, or East African descent [19,20]. As such, the current binary model must be viewed as a transitional framework rather than a final classification strategy.
One of the most debated areas remains the interpretation of anterior TWI, particularly in Black athletes. While lateral TWI (in leads I, aVL, V5–V6) is widely accepted as a red flag, the clinical significance of TWI in leads V1–V4 remains challenging. The high prevalence of anterior TWI in Black athletes must be balanced against the goal of early detection of ACM. The current criteria accept anterior TWI in V1–V4 as a normal variant in asymptomatic Black athletes, acknowledging a trade-off between sensitivity and specificity in a low-prevalence population. Similarly, anterior TWI in athletes under the age of 16 is considered part of the “juvenile pattern.” However, this age cutoff is a pragmatic simplification. Repolarization normalization during adolescence is a gradual process and correlates more closely with biological than chronological age. Thus, the 16-year threshold should be understood as a general orientation rather than a strict diagnostic boundary. Recent evidence suggests that PVC morphology, complexity (e.g., couplets, triplets, non-sustained VT), and response to exercise may be more informative than absolute numbers alone [17,21]. Morphologic patterns in particular may help identify underlying structural disease and should be more systematically assessed in future protocols.

Conclusion

Resting ECG screening will not identify all athletes at risk of SCD. This is particularly true for those with congenital coronary anomalies or, later in life, with coronary artery disease. In athletes over the age of 35, the sensitivity of ECG-based screening is markedly limited. Nonetheless, when applied critically and in awareness of its strengths and limitations, the 12-lead ECG remains a cost-effective, widely accessible, and validated tool to detect relevant cardiac pathology in young athletes, contributing meaningfully to the prevention of SCD in sports. The next update of the international ECG criteria is expected in 2026 and is awaited with interest.

Copyright notice for the ECG tracings

MSc Course in sportscardiology, St. George University, London, UK

Corresponding author

PD Dr. med. David Niederseer
Hochgebirgsklinik Davos
Herman-Burchard-Strasse 1
CH-7265 Davos Wolfgang
david.niederseer@hgk.ch

References

1. Wasfy MM., Hutter AM., Weiner RB. Sudden Cardiac Death in Athletes. Methodist Debakey Cardiovasc J 2016;12(2):76. Doi: 10.14797/MDCJ-12-2-76.
2. Harmon KG., Asif IM., Klossner D., Drezner JA. Incidence of sudden cardiac death in national collegiate athletic association athletes. Circulation 2011;123(15):1594–600. Doi: 10.1161/CIRCULATIONAHA.110.004622/ASSET/520E3ACF-5E65-4FAC-B06B-1F1A9700602B/ASSETS/GRAPHIC/ZHC0151193640001.JPEG.
3. Finocchiaro G., Westaby J., Sheppard MN., Papadakis M., Sharma S. Sudden Cardiac Death in Young Athletes: JACC State-of-the-Art Review. J Am Coll Cardiol 2024;83(2):350–70. Doi: 10.1016/J.JACC.2023.10.032.
4. Corrado D., Basso C., Pavei A., Michieli P., Schiavon M., Thiene G. Trends in Sudden Cardiovascular Death in Young Competitive Athletes After Implementation of a Preparticipation Screening Program. JAMA 2006;296(13):1593–601. Doi: 10.1001/JAMA.296.13.1593.
5. Maron BJ. Hypertrophic Cardiomyopathy: A Systematic Review. JAMA 2002;287(10):1308–20. Doi: 10.1001/JAMA.287.10.1308.
6. Nasir K., Bomma C., Tandri H., et al. Electrocardiographic features of arrhythmogenic right ventricular dysplasia/cardiomyopathy according to disease severity: A need to broaden diagnostic criteria. Circulation 2004;110(12):1527–34. Doi: 10.1161/01.CIR.0000142293. 60725.18/ASSET/686F96C8-7029-4EC3-9177-989CF15D6A3A/
   ASSETS/GRAPHIC/5FF3.JPEG.
7. Pelliccia A., Maron BJ., Culasso F., et al. Clinical significance of abnormal electrocardiographic patterns in trained athletes. Circulation 2000;102(3):278–84. Doi: 10.1161/01.CIR.102.3.278/ASSET/989FB5D8-D4D6-473A-ADC8-FC91E8E4D39F/ASSETS/GRAPHIC/HC2804137004.JPEG.
8. Nechita LC., Tutunaru D., Nechita A., et al. A Resting ECG Screening Protocol Improved with Artificial Intelligence for the Early Detection of Cardiovascular Risk in Athletes. Diagnostics 2025;15(4):477. Doi: 10.3390/DIAGNOSTICS15040477.
9. Corrado D., Pelliccia A., Bjørnstad HH., et al. Cardiovascular pre-participation screening of young competitive athletes for prevention of sudden death: proposal for a common European protocol: Consensus Statement of the Study Group of Sport Cardiology of the Working Group of Cardiac Rehabilitation and Exercise Physiology and the Working Group of Myocardial and Pericardial Diseases of the European Society of Cardiology. Eur Heart J 2005;26(5):516–24. Doi: 10.1093/EURHEARTJ/EHI108.
10. Corrado D., Pelliccia A., Heidbuchel H., et al. Recommendations for interpretation of 12-lead electrocardiogram in the athlete. Eur Heart J 2010;31(2):243–59. Doi: 10.1093/EURHEARTJ/EHP473.
11. Drezner JA., Ackerman MJ., Anderson J., et al. Electrocardiographic interpretation in athletes: the ‘Seattle Criteria.’ Br J Sports Med 2013;47(3):122–4. Doi: 10.1136/BJSPORTS-2012-092067.
12. Sheikh N., Papadakis M., Ghani S., et al. Comparison of electrocardiographic criteria for the detection of cardiac abnormalities in elite black and white athletes. Circulation 2014;129(16):1637–49. Doi: 10.1161/CIRCULATIONAHA.113.006179/ASSET/CEC95DD3-B654-4BD6-9C10-8D5EE34A188D/ASSETS/GRAPHIC/1637FIG07.JPEG.
13. Sharma S., Drezner JA., Baggish A., et al. International Recommendations for Electrocardiographic Interpretation in Athletes. J Am Coll Cardiol 2017;69(8):1057–75. Doi: 10.1016/J.JACC.2017.01.015.
14. Hyde N., Prutkin JM., Drezner JA. Electrocardiogram interpretation in NCAA athletes: Comparison of the ‘Seattle’ and ‘International’ criteria. J Electrocardiol 2019;56:81–4. Doi: 10.1016/J.JELECTROCARD.2019.07.001.
15. Malhotra A., Dhutia H., Yeo TJ., et al. Accuracy of the 2017 international recommendations for clinicians who interpret adolescent athletes’ ECGs: a cohort study of 11 168 British white and black soccer players. Br J Sports Med 2020;54(12):739–45. Doi: 10.1136/BJSPORTS-2017-098528.
16. Biffi A., Pelliccia A., Verdile L., et al. Long-term clinical significance of frequent and complex ventricular tachyarrhythmias in trained athletes. J Am Coll Cardiol 2002;40(3):446–52. Doi: 10.1016/S0735-1097(02)01977-0.
17. Lampert R., Chung EH., Ackerman MJ., et al. 2024 HRS expert consensus statement on arrhythmias in the athlete: Evaluation, treatment, and return to play. Heart Rhythm 2024;21(10):e151–252. Doi: 10.1016/J.HRTHM.2024.05.018.
18. Marijon E., Uy-Evanado A., Reinier K., et al. Sudden cardiac arrest during sports activity in middle age. Circulation 2015;131(16):
    1384–91. Doi: 10.1161/CIRCULATIONAHA.114.011988/ASSET/F4B7C952-379A-47DB-B34B-3605C1E0C608/ASSETS/GRAPHIC/1384FIG02.JPEG.
19. Riding NR., Sharma S., McClean G., Adamuz C., Watt V., Wilson MG. Impact of geographical origin upon the electrical and structural manifestations of the black athlete’s heart. Eur Heart J 2019;40(1):50–8. Doi: 10.1093/EURHEARTJ/EHY521.
20. Malhotra A., Rao P., Dhutia H., et al. THE MIXED RACE ATHLETE’S ECG: NOT SO BLACK AND WHITE. J Am Coll Cardiol 2017;69(11):1416. Doi: 10.1016/S0735-1097(17)34805-2.
21. Duijvenboden S Van., Ramírez J., Orini M., et al. Prognostic Significance of Different Ventricular Ectopic Burdens During Submaximal Exercise in Asymptomatic UK Biobank Subjects. Circulation 2023;148(24):1932–44. Doi: 10.1161/CIRCULATIONAHA.
    123.064633/SUPPL_FILE/CIRC_CIRCULATIONAHA-2023-064633_SUPP2.XLSX.