This systematic review employed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to ensure a transparent and replicable methodology. The objective was to collect and evaluate peer-reviewed studies published between 2015 and 2025 that investigated ECG changes in athletes across various sports. Inclusion criteria encompassed observational studies focusing on endurance, strength, and mixed sports in adolescent and adult athletes. Studies not reporting ECG findings, involving athletes with cardiac comorbidities, or classified as editorials, commentaries, or review papers were excluded.

PubMed/Medline was used as the primary electronic database for article retrieval. Other databases included Cochrane Reviews, PEDro, and the Google Scholar search engine. The search itself involved the use of a combination of Medical Subject Headings (MeSH) terms and/or keywords in the Title and abstracts, that were related to ECG, athletes, and sport types. The search strategy is presented in Table 1 while the PubMed search outcomes can be seen in Appendix Table 4.

Duplicates were removed using Zotero. Two reviewers independently screened the titles and abstracts, with a third reviewer consulted to resolve any discrepancies. Data extraction included information on athlete demographics, sport type, training level, and ECG findings, organized in Microsoft Excel. The quality of the study was assessed using the Newcastle-Ottawa Scale, without consideration of a bias risk. Since the data was publicly available, ethical approval was not required.

From all 20 studies [13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32] found, we noticed recurrent themes (Fig. 1). These included common ECG changes along with their reversibility, consistent gender, and age differences in ECG findings, sports-specific adaptations, as well as risk factors.

The common ECG changes noted included QRS amplitude and T-wave inversions (TWI) which were often associated with left ventricular hypertrophy. Sinus bradycardia was consistently reported in most athletes. In endurance athletes, early repolarization patterns were frequently observed. Most interestingly certain studies reported prolongation of QT interval, but this was reversed following ‘de-training’ (Table 2, Ref. [13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32]).

Amongst the gender and age differences, there were several salient findings. Most studies showed males as having higher QRS voltages as well as longer QRS durations and higher PR intervals. In comparison, females had higher resting heart rates but longer QTc intervals. The incidence of abnormal ECG findings, however, was more often reported in males. Regarding age, adolescents who were regular in sports showed a lower prevalence of abnormal ECG findings compared to adult athletes. However, when the abnormalities were detected, they often manifested as increased QRS voltage or TWI. Additionally, adolescents engaged in high-intensity training beyond typical levels for their age group, showed cardiac changes such as right atrial enlargement, which were also indicated by an increase in P-wave duration (Table 2).

When considering sport-specific adaptations, athletes involved in endurance sports, such as marathon running and cycling, displayed a higher prevalence of sinus bradycardia, early repolarization, and right atrial enlargement. Strength athletes, such as those who lifted weights, were more likely to exhibit signs of LVH and increased QRS voltage. Athletes participating in mixed sports like soccer or basketball, displayed a combination of endurance and strength-related ECG changes, including both increased QRS voltage and sinus bradycardia (Table 2).

One of the most clinically significant findings, was that detraining effectively reversed certain ECG changes, such as prolonged QT interval and T-wave abnormalities. In some cases, these changes returned to baseline upon retraining. Moreover, a study reported a high false-positive rate when using standard ECG criteria to screen patients [19]. Notably, we found only one study that identified new ECG changes in athletes after COVID-19 infection, which included T-wave inversions and ST-segment depression (Table 2).

The included studies highlighted that youth athletes frequently exhibited ECG abnormalities, such as TWI, bradycardia, and prolonged QT intervals, with increased incidence during the COVID-19 pandemic due to the risk of myocarditis. Furthermore, exercise-induced acquired long QT syndrome (LQTS) was also noted, with ECG abnormalities resolving after detraining but recurring with high-intensity training. These findings highlight the necessity of comprehensive cardiac screening and monitoring in young athletes.

Extensive diagnostic evaluations—including cardiac imaging, Holter monitoring, and genetic testing—proved essential in identifying complex arrhythmias and distinguishing between congenital and acquired cardiac conditions across all studies, not just youth athletes. Studies also acknowledged the financial burden of ECG-inclusive screening programs but emphasized their vital role in preventing sudden cardiac death [13, 33].

Overall, the results indicate that ECG alterations, such as left ventricular hypertrophy, QT prolongation, and other cardiac changes, are frequently observed in athletes. These alterations generally revert to baseline after periods of detraining, while youth athletes exhibit vulnerability to COVID-19-related myocarditis and training-induced cardiac adaptations.

This review was only partially successful in addressing all research questions. While the influence of specific sports on ECG changes and the impact of age differences were evident, only one study identified a particular risk factor unrelated to the type of sport. Nevertheless, the findings presented in this review provide valuable insights into the subject matter.

Accurately distinguishing between physiological adaptations and pathological conditions when interpreting ECG findings in athletes is paramount. Athletes frequently exhibit ECG changes as a direct consequence of cardiac adaptations to the increased physiological demands imposed by intense physical training. Common adaptations such as increased QRS voltage, sinus bradycardia, and early repolarization patterns are typically benign and reflect normal cardiac remodeling. However, more pronounced changes, particularly in athletes engaged in endurance or strength-based sports, such as LVH, present a greater challenge. LVH, characterized by elevated QRS amplitude and TWI, results from the heart’s adaptive response to meet the heightened oxygen demands of skeletal muscles by increasing left ventricular dimensions to maintain adequate cardiac output [6, 7].

The necessity of this differentiation extends beyond clinical relevance to financial implications. Misinterpreting physiological adaptations as pathological abnormalities can lead to significant financial burdens on healthcare systems, sports organizations, and athletes. Avoiding unwarranted diagnostic evaluations is essential to prevent escalating costs while ensuring that genuine pathological conditions are identified and managed appropriately. Therefore, accurate interpretation of ECG findings is critical not only for safeguarding athlete health but also for minimizing the economic strain associated with excessive medical examinations. Previous cost analyses of athlete ECG screening have not adequately considered various policies and practices across different countries and federations. Until all stakeholders convene to establish a unified approach that prioritizes athlete well-being, it remains challenging to draw definitive conclusions on the cost-effectiveness of widespread ECG screening. While it is impossible to assign a price to an athlete’s life, implementing a sport-specific risk stratification system, potentially integrated with predictive modeling, could enhance screening precision, reduce unnecessary tests, and help forecast the future risk of SCD through simulation-based technologies.

The distinction between HCM and arrhythmogenic right ventricular cardiomyopathy (ARVC) remains one of the most challenging aspects of ECG interpretation in athletes when TWI is present in the anterior leads. While these findings may indicate underlying cardiomyopathy, they can also represent benign physiological adaptations to intensive training. Similarly, prolonged QT intervals may be a hallmark of LQTS, a potentially life-threatening condition. Accurate differentiation is imperative, as misclassification can lead to unnecessary investigations or missed diagnoses that increase the risk of SCD [9, 10, 11]. The reversibility of many ECG changes following detraining as documented in several studies, supports the notion that numerous adaptations are physiological rather than pathological. Nevertheless, clinicians must remain vigilant, particularly when faced with deep TWI in multiple leads or markedly prolonged QT intervals, as these findings warrant further investigation to exclude underlying pathology [17, 34].

In this context, recent guidelines from the Italian Society of Sports Cardiology (SICSPORT) [35] offer essential insights into the interpretation of TWI in athletes. Recognizing the diagnostic challenge posed by TWI, these guidelines provide a framework for distinguishing between benign adaptations and serious cardiac pathologies, emphasizing the importance of TWI localization, clinical features, and demographic factors. The document highlights the need for comprehensive assessments and regular follow-ups, ensuring athlete safety while avoiding unnecessary restrictions and minimizing financial burdens associated with over-examination. African and Afro-Caribbean athletes show a higher prevalence of repolarization anomalies, such as TWI, especially in the anterior and inferior leads. Notably, black athletes are 2.5 times more likely to present with ECG abnormalities compared to white athletes, which are often misinterpreted as pathological. This increased prevalence of TWI in black athletes is typically a normal ethnic variant linked to the athlete’s heart but can lead to unnecessary testing and interventions if not correctly identified. A more nuanced approach to ECG interpretation in these populations is critical to prevent over-investigation and reduce the associated clinical and financial burden [36].

The cardiovascular adaptations induced by different sports reflect the unique hemodynamic and physiological demands on the athlete’s heart. This is particularly evident in endurance sports, where athletes such as marathon runners, cyclists, and swimmers experience significant volume overload due to prolonged aerobic activity. Consequently, the heart experiences structural remodeling, characterized by an increase in left ventricular cavity and wall thickness to enhance cardiac output and efficiency during sustained exercise. Endurance athletes commonly exhibit sinus bradycardia and early repolarization patterns on ECG, findings that were consistently reported across multiple studies [7, 8].

In contrast, strength-based sports such as weightlifting impose a predominant pressure overload on the cardiovascular system due to short but intense bursts of isometric activity. However, recent evidence suggests that even elite weightlifters typically do not develop significant myocardial hypertrophy under physiological training conditions. Echocardiographic data from Olympic athletes revealed that all weightlifters demonstrated normal left ventricular (LV) geometry, without signs of concentric or eccentric remodeling, despite high training volumes [37]. According to the 2023 Italian Cardiological Guidelines (COCIS) cardiology protocols for pre-participation evaluation, the diagnostic threshold for HCM is an LV wall thickness $\ge$15 mm, while the “grey zone” (13–15 mm) occurs in fewer than 3–5% of Caucasian male athletes but may be present in up to 18–20% of athletes of African descent. For Caucasian females, LV wall thickness typically does not exceed 12 mm, while in African females, the threshold is 13 mm. When wall thickness measurements exceed these physiological ranges, clinicians must consider the possibility of pathological hypertrophy (e.g., HCM) or non-physiological influences such as anabolic-androgenic steroid use [9, 36, 38]. Chronic use of anabolic substances has been linked to disproportionate increases in LV mass, impaired diastolic function, and the development of a proarrhythmic myocardial substrate, thereby mimicking or amplifying features of HCM [39]. Therefore, any finding of increased LV wall thickness in strength athletes warrants a comprehensive differential diagnosis that integrates ethnicity, training load, hypertrophy pattern, reversibility upon detraining, and a comprehensive assessment of potential doping history [40, 41].

Mixed sports exhibit a combination of cardiovascular adaptations associated with endurance and strength training, though to a lesser extent than specialized sports. For instance, football players may not sustain prolonged exertion comparable to marathon runners nor generate the intense pressure loads seen in weightlifters. Nonetheless, ECG findings in football players frequently demonstrate increased QRS voltage, indicative of strength-related adaptations, alongside sinus bradycardia, reflecting endurance training effects [4].

The classification of sports disciplines based on acute physiological responses and long-term cardiac remodeling further underscores the variability in cardiovascular adaptations across different athletic activities, as highlighted by the European Association of Preventive Cardiology (EAPC) [42]. Mixed sports, such as football, rugby, and basketball, are characterized by alternating phases of dynamic and static exertion, resulting in moderate cardiac remodeling marked by an increase in left ventricular cavity size with modest changes in wall thickness. This aligns with the observed ECG findings of increased QRS voltage and sinus bradycardia, reflecting the combined influence of endurance and strength demands.

The sport-specific nature of ECG changes necessitates interpretation criteria that account for the physiological demands of different sports. The latest International Criteria for Electrocardiographic Interpretation in Athletes [11] provides a robust framework for distinguishing physiological adaptations from pathological findings, though further refinement is required to accommodate the unique cardiovascular responses observed across diverse sports. Additionally, the influence of factors such as ethnicity and gender on ECG patterns warrants further investigation to enhance the accuracy and reliability of athlete screening.

Several studies have explored the impact of gender differences on ECG findings in athletes. It is well established that male athletes typically have greater muscle mass, both in skeletal muscles and in the myocardium. This increased myocardial mass contributes to enhanced electrical activity on ECG, as evidenced by higher QRS voltages and longer QRS durations observed in male athletes, a finding consistently reported in various studies [15, 23]. Furthermore, the greater overall muscle mass in male athletes increases circulatory demands during intense physical training, prompting further cardiac adaptations. In contrast, female athletes demonstrate higher resting heart rates and prolonged QTc intervals, which cannot be solely attributed to smaller myocardial mass. Hormonal factors, particularly the effects of estrogen on cardiac repolarization, alongside differences in autonomic tone—specifically lower vagal tone in females—also contribute to these gender-specific ECG variations.

The findings of this review highlight the unique challenges associated with cardiac screening in youth athletes. ECG abnormalities such as T-wave inversions, bradycardia, and prolonged QT intervals, were frequently observed, particularly during the COVID-19 pandemic, where potential myocarditis ECG changes were noted due to post-COVID syndrome. Although these changes are less prevalent in athletes, abnormalities such as TWI and ST-segment changes have been documented, indicating possible myocardial inflammation, especially myocarditis, which, while rare, presents an arrhythmogenic risk. To ensure proper diagnosis and mitigate potential risks, including SCD, ECG findings should be followed by more specific tests like cardiac magnetic resonance (CMR) [43]. The reversible nature of exercise-induced acquired LQTS, which resolves after detraining but recurs with high-intensity training, highlights the critical need for comprehensive cardiac monitoring in this population.

Pediatric athletes present challenges due to ongoing growth and maturation influencing cardiac adaptation. Ragazzoni et al. [12] emphasize the need for tailored ECG interpretation in young athletes and propose an algorithm to differentiate physiological adaptations from pathology, stressing age-specific guidelines for early detection of conditions like myocarditis and channelopathies to prevent SCD.

The review emphasizes the importance of balancing early detection of life-threatening conditions against the risk of overdiagnosis and unnecessary exclusion from sports. This is a call for further research and tailored recommendations for pediatric athletes.

The primary challenge in athlete screening lies in balancing the accurate detection of cardiac abnormalities with the financial and logistical burdens of widespread ECG use. The high false-positive rate often leads to unnecessary investigations, increased healthcare costs, and psychological stress for athletes. The European Society of Cardiology (ESC) and the Italian Society of Sports Cardiology have made significant contributions to refining ECG interpretation guidelines for athletes, promoting evidence-based standards to enhance diagnostic accuracy. Their efforts aim to address sport-specific, gender-specific, and age-related ECG variations, ensuring more reliable assessments and reducing false-positive rates. The EFSMA has also advocated for a standardized PPE protocol across Europe, including mandatory 12-lead ECGs, to provide equitable and comprehensive cardiac screening for all athletes. Notably, recreational athletes often train at intensities comparable to professionals, further underscoring the need for uniform screening standards. While comprehensive screening is often accessible to elite athletes through well-funded organizations, ensuring affordable PPE for all individuals participating in regular sports is essential. The financial burden of ECG screening can be prohibitive [13], especially in resource-limited settings, necessitating cost-effective solutions and specialized training for healthcare providers [34].

This review offers valuable insights into ECG screening in athletes; however, several limitations must be acknowledged. The literature search was restricted to English-language studies published in the past decade, potentially excluding significant findings from non-English sources, particularly those from Eastern countries. The inclusion of only observational studies, due to a lack of randomized controlled trials, limits the strength of the evidence presented. Case reports were also excluded, as many involved athletes with pre-existing or newly developed cardiac conditions, which conflicted with the review’s inclusion criteria. Statistical analysis was hindered by the heterogeneity of study outcomes and methodologies, with some studies focusing on elite athletes and others on amateurs. Notably, the included studies varied widely in population demographics (age, sex, ethnicity), athletic level (elite vs. amateur), and sport type (e.g., endurance vs. strength). Furthermore, ECG interpretation criteria were not uniform—some studies employed the Seattle criteria or the 2017 International Recommendations—introducing variability in the classification and reporting of ECG abnormalities. Differences in study design (cross-sectional vs. longitudinal) and inconsistent follow-up durations further limit the comparability of findings and the ability to conclude long-term outcomes. Despite these limitations, the risk of bias was generally low across the included studies, although some were constrained by small sample sizes (Table 3, Ref. [13, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32]).