Electrocardiographic Changes in Juvenile Athletes in Relation to Sex, Age, and Sport Category

Abstract

Regular physical activity in young athletes leads to significant cardiovascular adaptations, often reflected in changes observed on electrocardiograms (ECG). The aim of this study was to relate ECG changes to age, sex, and sport category to provide a more in-depth understanding of physiologic adaptations to training. This retrospective study included 600 healthy Caucasian children (5–17 years) undergoing preparticipation evaluation (PPE) in 2023–2024 consisting of thorough medical and family history, physical exam, and resting ECG. The study found that the most common adaptive ECG changes in young athletes were sinus bradycardia < 60/min (24.2%), incomplete right bundle branch block (iRBBB) (15.5%), and sinus arrhythmia (SA) (11.8%). More significant bradycardia < 50/min was found in 3.5% of athletes. Borderline or abnormal ECG findings were found in 3.5% of participants, but later studies confirmed the presence of a high-risk condition in only two athletes with pre-excitation pattern (0.33%). Sinus bradycardia was independently predicted by age, sex, and sport category, iRBBB and early repolarization pattern by sex and age, LVH only by sex and SA, and T-wave inversion in V1–V3 only by age. This study highlights that while adaptive ECG changes are common in young athletes, particularly in males and with increased age and training, the prevalence of high-risk conditions is low. Knowledge about the factors affecting adaptive ECG changes should help in clinical decision-making in juvenile athletes.

Introduction

Adaptive changes in the electrocardiogram observed in young athletes may result from both direct structural modifications of the heart and indirect effects on the autonomic nervous system [1]. Regular aerobic training induces numerous beneficial changes in the structure and function of the cardiovascular system. The most observed adaptations include balanced enlargement of the heart chambers and mild myocardial hypertrophy, referred to as exercise-induced cardiac remodeling. These changes enhance the efficiency of the heart, increasing the contractile strength of the myocardium [2]. Depending on the criteria used, up to 30% of healthy athletes may have left ventricular dimensions exceeding the upper limits of the norm [1]. Athletes typically experience a 10–20% increase in left ventricular wall thickness and a 10–15% increase in both left and right ventricular cavity size compared to individuals of similar age and size. They also have improved cardiac filling during diastole, higher stroke volume even at high heart rates, greater oxidative capacity, and capillary conductance in skeletal muscles, leading to higher oxygen consumption during exercise [3].

Studies show that adaptive changes in the hearts of young athletes, especially those aged 12–18 years, differ by gender. Men experience more significant changes, particularly in left ventricular end-diastolic volume and left ventricular mass, although cardiac function remains normal. These changes often exceed reference values. Therefore, age, gender, and training history are key to distinguishing between normal adaptations and potential cardiac problems in youth athletes, emphasizing the importance of careful monitoring [4]. Additional, adaptive changes in young athletes may also include atrial enlargement [5]. Endurance training increases vagal tone leading to early repolarization of the heart ventricles and slightly prolonged QT interval with a slower heart rate (HR). Increased vagal tone is also responsible for characteristic changes in the athlete’s ECG, such as sinus bradycardia, sinus arrhythmia, first-degree atrioventricular block, and Mobitz type I block [1].

Although exercise has significant health benefits, including improved cardiovascular health, excessive, or vigorous exercise in athletes with congenital or acquired heart diseases can pose a risk of life-threatening events [3]. It is crucial to correctly differentiate between adaptive changes within normal limits and changes that may manifest heart disease. This distinction is essential to prevent severe outcomes, including sudden cardiac death (SCD), which occurs at a rate of approximately 0.6–3.6 per 100,000 individuals annually in young athletes under 35 years of age [6]. The most common causes of SCD in this group include sudden arrhythmic death syndrome, hypertrophic cardiomyopathy and other cardiomyopathies, coronary artery anomalyies, and myocarditis. In elite athletes, the incidence of SCD is highest, and men are at greater risk [7].

Incorporating the standard 12-lead ECG to thorough physical examination and history-taking enhances the ability to identify potentially dangerous cardiovascular pathologies [8]. It is recommended to use athlete-specific criteria for ECG interpretation to reduce false positive results and their consequences. Currently, there are two proposed diagnostic criteria for juvenile athletes. One, generally accepted and endorsed by scientific societies but unifying junior and adult athletes and second one local, proposed by a group of experts, dedicated to children [9, 10]. For older teenagers, application of International criteria seems more justified, but they seem less applicable in young children. Therefore, many uncertainties remain, and further research is needed on ECG criteria and their application across different athlete populations [11].

The aim of this study is to analyze and discuss the adaptive changes in the electrocardiogram resulting from physical activity in young athletes. The study involved children aged 5–17, actively practicing various sports disciplines, to identify differences depending on age, gender, and sport category and to provide a comprehensive understanding of these adaptations.

Materials and Methods

This retrospective study included healthy 600 Caucasian children of both sexes, up to the age of 17 years, undergoing mandatory by Polish law annual preparticipation evaluation (PPE) related to trainings in sport clubs and/or taking part in sport competitions [12]. The examinations were done in two sport clinics in Warsaw, Poland between the beginning of 2023 and the end of 2024. Only the first PPE was analyzed for those participants who had undergone more than one screening in that period.

Analyzed parameters included medical and family history, presence of symptoms, sport category, training duration, physical examination including anthropometric data, body mass index (BMI) calculation, heart auscultation, pulse, and blood pressure measurement, and finally resting electrocardiogram (ECG). Subjects with previous medical history or symptoms were excluded from the analysis. All the athletes included in the analysis had to train for at least 1 year and represented various disciplines described in Fig. 1.

Fig. 1.

Sport disciplines practiced by study participants

For the purpose of this study, the disciplines were divided into the following groups: (1) skill sports (badminton, carting, diving, equestrian, fencing, sailing, shooting, table tennis), (2) strength sports (acrobatics, alpine skiing, ice hockey, indoor climbing, martial arts, sprints), and (3) mixed and endurance sports (American football, athletics other than sprints, attendance to sport classes, basketball, cycling, football, handball, ice and speed skating, rowing, squash, swimming, tennis, volleyball, windsurfing) [13]. Endurance sports were not analyzed separately from mixed sports due to a low number of juvenile athletes engaged in pure endurance sports.

All participants were also divided into groups according to the age category (young children and pre-adolescents—5–11 years, young adolescents—12–14 years, and older adolescents—15–17 years).

Electrocardiograms were analyzed together by trained cardiologist and sport cardiologist with over 20 years of experience in the field and two sports medicine specialists, until a consensus was reached. We used the definitions and interpretations proposed in the document by Ragazzoni et al. with classification of findings into normal, borderline, and abnormal [10]. Sinus bradycardia was defined as a HR below 60 beats per minute (bpm) on resting ECG and more significant bradycardia as HR below 50 bpm. For BMI and blood pressure in children, normal values according to the growth charts for Poland based on WHO criteria were applied [14].

Statistical Analysis

All results for categorical variables were presented as a number and a percentage. Continuous variables were expressed as mean and standard deviation (SD) or median and interquartile range (IQR) based on presence or lack of normality of distribution assessed with means of the Shapiro–Wilk test. To analyze the differences between categorical variables a chi-square or Fisher’s exact test were used, were appropriate. The Student t test or the Mann–Whitney test for unpaired samples was applied to compare one continuous variable between two category groups, depending on the normality of distribution. One-way ANOVA or Kruskal–Wallis test was applied to compare one continuous variable (with normal distribution or without normal distribution, respectively) between three or more category groups. Correlation between two continuous variables was assessed with means of Pearson or Spearman test, as appropriate. Finally, a logistic regression has been performed to establish independent markers of the most common adaptive ECG changes in juvenile athletes. All tests were two-sided with the significance level of p < 0.05. Statistical analyses were performed with MedCalc statistical software 10.0.2.0 (Ostend, Belgium).

The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board (or Ethics Committee) of the University of Physical Education in Warsaw (no. 004/2024, 26th Nov 2024).

Results

Baseline Characteristics

Baseline characteristics of the studied group are presented in Table 1. Median age was 12 years, age range 5–17 years, interquartile range 10–14 years, and 408 children (68%) were males. All participants had normal BMI and systolic and diastolic blood pressure (SBP/DBP) at rest. None of the subjects had any significant prior cardiologic medical history or symptoms. Physical examination did not reveal any cardiovascular abnormalities.

Table 1.

Baseline characteristics of the studied group

Parameter
Age, years (IQR)	12 (10–14)
Age categories, n (%)
5–11	257 (43)
12–14	200 (33)
15–17	143 (24)
Male sex, n (%)	408 (68)
Weight, kg (IQR)	46 (35–60)
Height, cm (IQR)	158 (143–173)
BMI, kg/m2 (IQR)	18.3 (16.4–20.7)
SBP, mmHg (IQR)	110 (103–120)
DBP, mmHg (IQR)	70 (65–75)
Years of training (IQR)	6 (4–9)
Sport group, n (%)
Skill sports	63 (10)
Strength sports	70 (12)
Mixed and endurance sports	467 (78)

BMI body mass index, DBP diastolic blood pressure, IQR interquartile range, SBP systolic blood pressure, SD standard deviation

Main ECG Findings

Median resting HR in the whole group was 67 bpm (IQR 60–76). Sinus bradycardia was present in 145 athletes (24.2%), with HR < 55 bpm in 64 subjects (10.7%) and HR < 50 bpm in 21 of them (3.5%). None of the athletes had resting HR < 40 bpm and resting HR range was between 40 and 112 bpm.

Other normal findings considered as adaptational changes to sport training are presented in Fig. 2 in descending frequency order. The most common changes included iRBBB present in 93 athletes (15.5%), sinus arrhythmia in 71 (11.8%), and amplitude signs of left ventricular hypertrophy (LVH) in 60 of them (10%). Less common adaptational changes were ERP present in 47 subjects (7.8%), T-wave inversion (TWI) in leads V1–V3 present in 38 (6.3%), and mild atrioventricular block (AVB) with PR interval between 204 and 256 ms in ten athletes (1.7%). All cases of TWI in V1–V3 were found in athletes before 16 years of age. TWI limited to V1–V2 was observed in 28 children (4.7%) and exceeding to V4 in 3 of them (0.5%). Right axis deviation (RAD) was observed in 21 athletes (3.5%) and left axis deviation (LAD) in 6 (1.0%). Seven subjects (1.2%) had ectopic atrial rhythm (non-sinus rhythm—non-SR) and additional one presented resting ventricular escape rhythm.

Fig. 2.

Frequency of observed normal adaptational ECG changes in studied juvenile athletes. AVB atrioventricular block, ERP early repolarization pattern, iRBBB incomplete right bundle branch block, LVH amplitude left ventricular hypertrophy, SA sinus arrhythmia, SR sinus rhythm, TWI T-wave inversion

Borderline findings including coexistence of iRBBB with LAD or RAD were found in nine subjects (1.5%, six with RAD and three with LAD). Abnormal ECG findings were detected in 12 athletes (2.0%) and are presented in Fig. 3. Those included three cases of TWI in inferior leads (one in II and aVF, two in III and aVF) and one case of TWI in infero-lateral leads (II, aVF, I, V5–V6), two cases of common ventricular extrasystolic beats (one with LBBB/inferior axis morphology and one with RBBB and narrow QRS morphology), two cases of pre-excitation pattern (PR below 90 ms and a presence of delta wave), two ECGs showing long QTc (463 and 465 ms), one case of complete right bundle branch block (RBBB), and one case of supraventricular extrasystolic beats.

Fig. 3.

Abnormal ECG findings in the studied group. Inf inferior, inf-lat infero-lateral, LQT long QT, RBBB right bundle branch block, sVEBs supraventricular extrasystole beats, TWI T-wave inversion, VEBs ventricular extrasystolic beats

All 21 patients (3.5%) with borderline or abnormal findings were referred for further testing. Conditions at high risk of competitive sport participation were confirmed in only two patients (0.33%), both with pre-excitation pattern and both of them underwent successful ablation procedure and were eventually able to return to sport. In other patients, further testing including transthoracic echocardiogram/cardiac magnetic resonance, Holter ECG monitoring, and exercise testing were available did not disclose a disease, but those patients were scheduled for future close monitoring.

Relation Between ECG Changes and Sex

There was no difference in terms of age and years of training between girls and boys. However, girls were more likely to practice skill sports and boys were more likely to engage in mixed or endurance sports, particularly football (Table 2). Adaptive ECG changes more common in males included sinus bradycardia, but not profound sinus bradycardia (< 50 bpm), iRBBB, LVH and the presence of ERP. There was also no difference between sexes in terms of borderline or abnormal ECG findings.

Table 2.

Relation between most common ECG changes and sex

Parameter	Female sex n = 192 (32%)	Male sex n = 408 (68%)	p
Age, years (IQR)	12 (10–14)	12 (10–15)	0.21
Years of training (IQR)	6 (3–9)	6.5 (4–9)	0.70
Sport category, n (%)			< 0.0001
Skill sports	47 (25)	16 (4)
Strength sports	21 (11)	49 (12)
Mixed and endurance sports	124 (64)	343 (84)
Sinus bradycardia, n (%)	27 (14)	118 (29)	0.0001
HR < 55 bpm	11 (6)	53 (13)	0.01
HR < 50 bpm	4 (2)	17 (4)	0.24
iRBBB, n (%)	14 (7)	79 (19)	0.002
SA, n (%)	27 (14)	44 (11)	0.31
LVH, n (%)	3 (2)	57 (14)	< 0.0001
ERP, n (%)	5 (3)	42 (10)	0.002
TWI V1–V3, n (%)	14 (7)	24 (6)	0.63
Borderline changes, n (%)	1 (0.5)	8 (2)	0.28
Abnormal changes, n (%)	4 (2)	8 (2)	1.00

AVB atrioventricular block, ERP early repolarization pattern, iRBBB incomplete right bundle branch block, LVH amplitude left ventricular hypertrophy, SA sinus arrhythmia, SR sinus rhythm, TWI T-wave inversion

Relation Between ECG Changes and Age Category/Years of Training

There was no difference in terms of sex between age groups. As expected, increasing age was strongly related to more years of training and therefore those two factors were analyzed together (rho = 0.82, 95% CI 0.77–0.89, p < 0.0001). ECG adaptive change continuously increasing with age category/years of training was sinus bradycardia up to profound sinus bradycardia (< 50 bpm) (Table 3). On the other hand, there was a continuous decrease with age in the presence of SA and TWI V1–V3. Other changes such as iRBBB and ERP were more common in adolescents than in young children and pre-adolescents, but their frequency did not increase further from younger to older adolescents. Also here, there were no differences between age category and the frequency of borderline or abnormal findings.

Table 3.

Relation between ECG changes and age category/years of training

Parameter	Age 5–11 years n = 257 (43%)	Age 12–14 years n = 200 (33%)	Age 15–17 years n = 143 (24%)	p
Male sex, n (%)	174 (68)	124 (62)	110 (77)	0.14
Years of training, IQR	4 (3–5)	6 (4–8)	9 (7–10)	< 0.0001
Sport category, n (%)				0.37
Skill sports	21 (8)	28 (14)	14 (10)
Strength sports	32 (12)	21 (10.5)	17 (12)
Mixed and endurance sports	204 (80)	151 (75.5)	112 (78)
Sinus bradycardia, n (%)	35 (14)	46 (23)	64 (45)	< 0.0001
HR < 55 bpm	14 (5)	20 (10)	30 (21)	< 0.0001
HR < 50 bpm	5 (2)	5 (2.5)	11 (8)	0.01
iRBBB, n (%)	27 (11)	38 (19)	28 (20)	0.01
SA, n (%)	37 (14)	23 (11.5)	11 (8)	0.04
LVH, n (%)	21 (8)	29 (14.5)	10 (7)	0.95
ERP, n (%)	11 (4)	22 (11)	14 (10)	0.02
TWI V1–V3, n (%)	26 (10)	11 (5.5)	1 (1)	0.0002
Borderline changes, n (%)	3 (1)	2 (1)	4 (3)	0.34
Abnormal changes, n (%)	3 (1)	4 (2)	5 (3.5)	0.28

Abbreviations as in Table 2

Relation Between ECG Changes and Sport Category

There was no difference in terms of age between different sport categories. However, there were sex differences as described earlier (Table 4). ECG adaptive changes showing increasing gradient from skill sports through strength to mixed or endurance sport included sinus bradycardia (but not profound sinus bradycardia < 50 bpm), LVH, and ERP. Also here, there were no differences between sport category and the frequency of borderline or abnormal findings.

Table 4.

Relation between ECG changes and sport category

Parameter	Skill sports n = 63 (10%)	Strength sports n = 70 (12%)	Mixed and endurance sports n = 467 (78%)	p
Age, years (IQR)	13 (10–15)	12 (10–14)	12 (10–14)	0.62
Male sex, n (%)	16 (25)	49 (70)	343 (73)	< 0.0001
Years of training, (IQR)	5 (5–7)	4 (3–7)	6 (4–9)	0.17
Sinus bradycardia, n (%)	6 (10)	14 (20)	125 (27)	0.002
HR < 55 bpm	3 (5)	5 (7)	56 (12)	0.04
HR < 50 bpm	1 (2)	2 (3)	18 (4)	0.33
iRBBB, n (%)	5 (8)	18 (26)	70 (15)	0.68
SA, n (%)	6 (10)	6 (9)	59 (13)	0.32
LVH, n (%)	4 (6)	2 (3)	54 (12)	0.04
ERP, n (%)	1 (2)	3 (4)	43 (9)	0.02
TWI V1–V3, n (%)	7 (11)	4 (6)	27 (6)	0.15
Borderline changes, n (%)	0 (0)	2 (3)	6 (1)	0.35
Abnormal changes, n (%)	3 (5)	2 (3)	7 (1)	0.19

Abbreviations as in Table 2

Independent Factors Affecting Most Common Adaptive Changes in Juvenile ECG

Logistic regression applied for those ECG adaptive changes that were related to more than one analyzed factor in univariate analysis (sinus bradycardia, LVH, ERP, and iRBBB) found that independent factors predicting sinus bradycardia were increasing age/years of training (OR 1.27, 95% CI 1.18–1.36, p < 0.0001), male sex (OR 2.02, 95% CI 1.24–3.28, p = 0.005) and sport category from skill through strength to mixed/endurance sports (OR 1.61, 95% CI 1.10–2.36, p = 0.01). iRBBB was predicted by increasing age/years of training (OR 1.13, 95% CI 1.05–1.22 per year, p = 0.002) and male sex (OR 2.95, 95% CI 1.62–5.38, p = 0.0005) and ERP by increasing age/years of training (OR 1.11, 95% CI 1.01–1.24, p = 0.03) and male sex (OR 3.40, 95% CI 1.31–8.84, p = 0.01). LVH was predicted only by sex (OR for male sex 10.23, 95% CI 3.16–33.1, p = 0.0001). Table 5 and Fig. 4 summarize the logistic regression findings. It presents the relation of the most observed adaptive ECG changes present in juvenile athletes to sex, age, and sport category.

Table 5.

Independent factors affecting most common adaptive changes in juvenile ECG

	Sinus bradycardia		iRBBB		LVH		ERP
	Univariate OR, 95% CI, p	Multivariate OR, 95% CI, p	Univariate OR, 95% CI, p	Multivariate OR, 95% CI, p	Univariate OR, 95% CI, p	Multivariate OR, 95% CI, p	Univariate OR, 95% CI, p	Multivariate OR, 95% CI, p
Age/years of training	1.27, 1.18–1.36, < 0.0001	1.27, 1.18–1.36, < 0.0001	1.14, 1.06–1.23, 0.001	1.13, 1.05–1.22, 0.002	1.04, 0.95–1.14, 0.40		1.13, 1.02–1.26, 0.02	1.11, 1.01–1.24, 0.03
Male sex	2.49, 1.57–3.94, 0.0001	2.02, 1.24–3.28, 0.005	3.05, 1.68–5.55, 0.0002	2.95, 1.62–5.38, 0.0005	10.23, 3.16–33.11, 0.0001	10.23, 3.16–33.1, 0.0001	4.29, 1.67–11.03, 0.002	3.40, 1.31–8.84, 0.01
Sport categorya	1.72, 1.21–2.48, 0.002	1.61, 1.10–2.36, 0.01	0.93, 0.66–1.32, 0.68		0.58, 0.34–1.01, 0.05		0.42, 0.19–0.90, 0.03

Abbreviations as in Table 2

^aFrom skill through strength to mixed/endurance sports

Fig. 4.

Relation between most frequently observed adaptive ECG changes and sex, age, or sport category

Discussion

The heart of young athlete undergoes significant adaptive changes both before and during puberty. Active children show more frequent ECG changes, both training related and independent, compared to their inactive peers [5]. After cessation of training, most of these changes such as lower resting HR and higher QRS amplitude disappear, except for the T-wave axis, which remains more negative than in individuals who never participated in regular sports training [15].

The main finding of our study was a relation of most common adaptational changes in juvenile athletes to age/years of training, sex, and sport category. We found that sinus bradycardia is related to all those factors, iRBBB and ERP to sex and age, while sinus arrhythmia and TWI in V1–V3 was only related to age and LVH to sex. These findings should be taken into consideration when assessing ECG of juvenile athletes and may help in the interpretation of their ECG by putting the observed changes in the right context.

In the analyzed group, the median resting HR was 67 beats per minute, with sinus bradycardia observed in almost a fourth of athletes. This finding aligns with previous studies that highlight the frequent occurrence of bradycardia in young athletes, which increases with training intensity and may be considered as a marker of cardiovascular adaptations to regular training [15–20]. Our results confirmed that with age and more years of training, there is an increase in the occurrence of sinus bradycardia [16].

Its mechanisms are likely to have a complex, multifactorial origin and have not yet been fully understood considering current knowledge. Possible causes of bradycardia in athletes include increased sympathetic and parasympathetic tone, orthosympathetic hypotonia, vagal hypertonia, structural heart adaptations (cardiac remodeling), modifications within the sinus node itself, and the influence of intense physical activity on nerve function [1, 20, 21]. The study by Subramanian et al., which compared school-going athletes and non-athlete boys aged 10–19, revealed that while HR was similar in both groups, athletes demonstrated higher HR variability. This suggests that regular athletic training may positively influence autonomic regulation of the cardiovascular system [22]. In summary, bradycardia up to 40 bpm should be considered as physiological and do not require intervention in the absence of other abnormalities, symptoms, or family history suggesting potential inherited cardiac disease. Our study has shown that bradycardia, and especially profound bradycardia, should be justified by older age/higher number of training years, male sex, and mixed endurance sport category. Nonetheless, detailed clinical evaluation remains crucial to ensure the safety of young athletes.

Our study confirms that iRBBB is commonly seen in athletes making it one of the most common ECG findings in pediatric athletes and supporting its interpretation as a benign, adaptive change associated with growth and athletic training [23, 24]. We have demonstrated that it is also more common in male juvenile athletes. iRBBB is more common in young athletes than in non-athletic children [5]. Therefore, it generally should not warrant further investigations particularly in asymptomatic juvenile athletes without family history of heart conditions. However, there is some data suggesting that percentile outliers detection within ‘normal’ population ranges may help differentiate normal from abnormal [25]. It is also important to differentiate iRBBB from pathologic ECG patterns, such as Brugada pattern or Wolff–Parkinson–White syndrome, and to consider a split second heart sound as a potential sign of an ostium secundum atrial septal defect [23]. Athletes with RBBB and iRBBB exhibited enlarged dimensions of the right ventricle, including an increased basal end-diastolic diameter and end-diastolic area of the right ventricle [26]. In young individuals aged 14–35 years, RBBB is a rare finding (0.1%), observed more frequently in males and athletes, with an increased risk of associated pathologies in cases of non-isolated RBBB and prolonged QRS duration (≥ 130 ms) [27]. The presence of RBBB, although rare, warrants thorough evaluation to exclude underlying cardiac pathology, particularly in symptomatic individuals [24]. A possible mechanism for the occurrence of iRBBB in young athletes could be delayed intraventricular conduction due to right ventricular enlargement caused by years of regular physical activity; however, this does not explain all cases, suggesting the need for further research into other factors influencing this change [24].

In line with previous studies our results also suggest that TWI in leads V1–V3 may be a normal developmental feature in young athletes, resulting from the reduced workload of the right ventricle in children. With age, the prevalence of TWI in precordial leads decreases [5, 15, 28, 29]. It typically becomes positive by the age of 14 years [29]. However, McGlean et al. showed that pediatric athletes aged 14 years and older were up to 16 times more likely to exhibit TWI in infero-lateral leads (requiring further investigation) compared to athletes younger than 14 years [5]. Calò et al. demonstrated that TWI in infero-lateral leads is more strongly associated with serious heart conditions, such as hypertrophic cardiomyopathy and left ventricular hypertrophy, as significant abnormalities on echocardiography were found in 60% of cases. In contrast, TWI in anterior leads is primarily linked to benign changes, with cardiac complications occurring less frequently, in only 4.8% of cases [30]. Inferolateral TWI should not be considered a physiologic change related to age, development, or training. Children with TWI in these leads should be closely monitored clinically and undergo further diagnostic testing to rule out potential heart diseases [29].

Age increases left ventricular dimensions, interventricular septal thickness, and left ventricular mass, and these parameters remain greater in pediatric athletes than in inactive individuals, even after controlling for age [5, 31]. Our study demonstrated that amplitude signs of LVH occurred significantly more frequently in men. A proposed explanation for this may be hormonal differences, such as lower testosterone levels in women; however, the exact causes of this difference are still not fully understood [5].

Another finding was ERP. ERP is defined as an elevation of the QRS–ST junction by at least 0.1 mV from the baseline in the inferior or lateral leads, appearing as QRS slurring or notching [32]. In our study ERP was significantly more common in young men than in young women. A similar trend has also been observed in other studies [33, 34]. We have also demonstrated that its presence is less likely in youngest children and pre-adolescents than in adolescents. The physiologic basis for sex differences in ERP has been also attributed to the influence of sex hormones, such as testosterone and the variability in voltage gradient [33]. Among athletes with ERP, 80.3% retained this pattern during the 4.2-year follow-up [35]. Athletes with ERP were older, had a lower resting HR, and exhibited higher R-wave amplitude [35]. The impact of ERP on health in young athletes remains unclear. ERP is considered as a marker of normal ECG variation and a marker of good health. It was previously linked to a higher risk of dangerous arrhythmias, including ventricular and atrial fibrillation, as well as sudden cardiac arrest in the absence of structural heart disease, which has raised concerns among heart specialists, but large studies in athletes did not confirm this relation [33–35]. The study by Halasz et al. reported no cases of cardiomyopathy or SCD were observed during the 4.2-year follow-up, suggesting that ERP in this group may be considered a harmless training-related adaptation with potentially variable characteristics [35]. However, there remains limited information regarding ERP in pediatric athletes.

Although borderline and abnormal ECG findings were present in few percent of the screened juvenile athletes, after additional examinations conditions at risk of serious cardiovascular events were found in only a minority of them. This is in line with previous studies demonstrating that a life-threatening condition is found only in < 0.5% of screened athletes [36, 37]. The reason for low positive predictive value (PPV) of our ECG abnormal and borderline findings (9.5%) may come from two facts. Firstly, in children ECG findings may occur before the onset of symptoms or other signs of cardiomyopathy, which was demonstrated in several studies [38, 39]. Otherwise, some ECG findings might disappear after acute disease cessation (such as TWI or PVCs after acute myocarditis) and therefore, there might have not be any visible changes on echocardiogram if it is done a few weeks from ECG. Secondly, we used Ragazzoni’s and not International criteria in our study. According to the International criteria only six patients would have abnormal findings instead of nine. RBBB and QTc between 460 and 470 ms would have not been classified as abnormal in both studied juvenile female athletes. None of the children would be classified as having borderline findings. We have not reported left or right atrial enlargement, but iRBBB is not one of the borderline finding in children according to the International criteria. In that case PPV of our findings would rise to 33%. It shows that International criteria applied to children may have a higher PPV than Ragazzoni’s criteria. Considering this calculation and high prevalence of iRBBB in juvenile athletes as well as a physiologic nature of axis deviation in this age group qualification of coexisting LAD/RAD with iRBBB as a borderline finding seems questionable. Finally, we have not confirmed that borderline or abnormal findings were more common in older children as some researchers observed, also suggesting potential limitation of screening to children 12 years of age or older [37].

Limitations

Our study has some limitations. First, we limited our analysis to single ECG, while other studies demonstrated that annually repeated ECG detects more abnormalities in juvenile athletes [36]. Also, we were unable to collect full clinical follow-up, but none of the major cardiovascular incidents were noted in the sport clinic’s electronic systems. Therefore, we were unable to analyze the negative predictive value of the borderline and abnormal findings. We did not perform echocardiographic examinations for all athletes, which could shed new light on our ECG findings. Finally, the most practiced sport in our study group was football, which might have influenced the results.

Conclusion

In summary, we have demonstrated a high prevalence of adaptive, physiologic changes in ECGs of the juvenile athletes and related the most frequent changes to sex, age, and sport category. This information should be considered when assessing a juvenile athlete’s ECG during preparticipation screening. Only a minority of ECGs demonstrated potentially pathologic changes with pre-excitation pattern as the main finding.

Author Contributions

Conceptualization: Łukasz A. Małek Methodology: Łukasz A. Małek, Mariusz Dotka, Kinga Brzezińska Analysis: Łukasz A. Małek, Piotr Pyndryk, Maciej Materkowski Investigation: Łukasz A. Małek, Piotr Pyndryk, Maciej Materkowski Writing—original draft preparation: Łukasz A. Małek, Mariusz Dotka, Kinga Brzezińska Writing—review and editing: Piotr Pyndryk, Maciej Materkowski, Szczepan Wiecha Visualization: Łukasz A. Małek Supervision: Łukasz A. Małek, Szczepan Wiecha.

Data Availability

No datasets were generated or analysed during the current study.

Declarations

Conflict of Interest

The authors declare no competing interests.