Abstract
Background
Children and adolescents represent a challenging population due to their incomplete physical development, and lack of specific criteria for interpreting electrocardiography (ECG) in children and adolescent athletes. We aimed to investigate the prevalence and clinical significance of short PR interval in pediatric and adolescent athletes undergoing pre-participation cardiac screening.
Methods
This is a cross-sectional study, where a total of 1310 athletes (age range: 7–18 years) underwent a comprehensive screening including medical history, physical examination, 12-lead ECG, echocardiography, and exercise testing under stress at Exercise and Sports Medicine Unit, University of Molise, Campobasso Italy between January 2023 and June 2024. Short PR interval prevalence and clinical significance were evaluated by frequency analysis and association with cardiac symptoms, respectively.
Results
Short PR interval (< 120 ms) was present in 26.9% of athletes, while using a z-score threshold of − 2 as the age- and sex-adjusted lower limit of normal, 3.82% of the athletes met criteria for a short PR interval. No significant associations were found between short PR interval and cardiac symptoms: syncope, palpitations, chest pain, exercise-induced arrhythmias, or need for additional diagnostic testing beyond standard screening (p > 0.05).
Conclusions
Isolated short PR interval was not associated with adverse cardiac findings among children and adolescent athletes following pre-participation screening, supporting its interpretation as a benign age-dependent variant. However, long-term outcome data are needed to confirm these observations.
Keywords: Short PR interval, Pre-participation screening, Electrocardiography, Sports cardiology, Adolescent athletes
Background
Participation in sports during childhood and adolescence is crucial for establishing lifelong physical activity habits and improving health outcomes. Current World Health Organization (WHO) guidelines recommend at least 60 min of moderate-to-vigorous intensity physical activity daily for children and adolescents [1]. The prevalence of youth sports participation varies considerably by country, age, and sex. In the United States, approximately 54–55% of children aged 6–17 years participate in organized sports [2], while European data show considerable variation across countries, with overall organized sport participation ranging from 20 to 80% depending on the region and method of assessment [3]. Males participate at significantly higher rates than females across all age groups, and participation typically peaks around ages 10–13 years [2, 3].
Sports pre-participation screening (SPPS) aims to identify medical conditions and risk factors that predispose individuals to exercise-induced adverse events thus promoting safe participation in sports and physical activity. It generally includes a medical history, physical examination electrocardiogram (ECG) at rest, and spirometry and exercise test under stress for competitive sport participation [4]. Furthermore, specific diagnostic tests such as echocardiography, Holter ECG monitoring, cardiac magnetic resonance imaging (MRI), coronary computed tomography (CT), and electrophysiological examinations may be necessary based on the clinical findings [5]. Children and adolescents represent a challenging population for SPPS, due to their incomplete physical development, transition of ECG pattern from pediatric to adult and lack of specific criteria for interpreting ECG in children and adolescent athletes [6]. The PR interval on the electrocardiogram reflects atrial depolarization and conduction through the atrioventricular node. It is physiologically shorter in young children than in adolescents, with gradual prolongation occurring during adolescence [7]. Isolated short PR interval, which refers to short PR interval in the absence of ventricular pre-excitation, is a relatively frequent finding in approximately 15% of adolescents, with higher prevalence among females and sedentary individuals [8]. However, data regarding the prevalence and clinical significance of short PR interval in pediatric and adolescent athletes remain very limited.
Therefore, in this study we aimed to investigate the following: (a) the prevalence of short PR interval in a pediatric and adolescent athletic population; (b) the correlation between isolated short PR interval and demographic and clinical characteristics; and (c) the role of isolated short PR interval in determining the need for additional cardiac evaluation prior to sports eligibility clearance.
Material and Methods
Study Population
This is a cross-sectional study, where one thousand, three hundred and fifty children and adolescents were initially referred for sports eligibility certificate to the Exercise and Sports Medicine Unit “'Antonio Cardarelli Hospital,” Department of Medicine and Health Sciences, University of Molise, Campobasso Italy between January 2023 and June 2024. Those participating in this study were selected based on the following inclusion criteria: (a) age ≥ 7 and ≤ 18 years; (b) participation in competitive (training regularly for > 10 h per week and participating in official sports competition) or recreational sports (recreational training for > 4 h per week but not participating in official competitions) [9]; and (c) written permission from the parents for anonymous data collection. Data from athletes with physical and or cognitive disabilities, those using a wheelchair, those with known pre-existing cardiac disease, and those with incomplete anamnestic or clinical data were not included in this analysis. Forty athletes were excluded: 10 due to physical and/or cognitive disabilities or use of a wheelchair, 1 with a known diagnosis of hypertrophic cardiomyopathy, 2 with pulmonary stenosis, 1 with known bicuspid aortic valve and moderate insufficiency, and 26 with incomplete anamnestic or clinical data. The final study population consisted of 1310 athletes who met all inclusion criteria and were included in the analysis.
All procedures were approved by the Institutional Review Board of Department of Medicine and Health Sciences, University of Molise, and conducted in accordance with the declaration of Helsinki for studies on humans. Parents of participants provided informed written consent for anonymous data collection prior to the study.
Sports Pre-participation Screening
According to the Italian law n. 158 2012, athletes interested in participating in competitive sports as indicated by Italian National Sport Federation should undergo annual or biannual medical screening as indicated by National Guidelines [4]. The medical screening includes the following: family and personal medical history, physical examination, blood pressure measurements, resting and stress testing electrocardiogram, visual acuity test blood pressure monitoring, and urine examination. For the recreational, non-competitive level sport participation, resting electrocardiogram is mandatory. In addition, echocardiography examination was also performed for each participant.
For the proposes of this study, the presence of familiarity for cardiovascular risk factors and cardiovascular diseases, and medical history regarding syncope, palpitations, and chest pain were recorded for each participant. Family history was defined broadly, encompassing any cardiovascular disease or risk factor including hypertension, diabetes mellitus, and dyslipidemia in first- or second-degree relatives. The sports practiced were classified into four categories according to the European Society of Cardiology recommendations [10]: skill, power, endurance, and mixed and data regarding hours of training per week were also collected. Data regarding further examinations required in case of abnormal findings at first line screening protocol were registered. Abnormal findings included advanced atrial-ventricular blocks, ventricular arrhythmias, sustained supraventricular tachycardia, T-wave inversion in lateral leads on resting ECG, prolonged QTc interval or Brugada-like pattern on resting ECG, ST-segment changes or T-wave modifications during exercise stress testing, echocardiographic findings suggestive of hypertrophic patterns, complicated bicuspid aortic valve, or moderate-to-severe valvular insufficiency.
Echocardiography
Trans-thoracic echocardiography was performed using the Alpinion XCUBE ultrasound system with a cardiac sector transducer sampling at 1–5 MHz according to the current International Guidelines [11–13]. Left Ventricular (LV) size, end-diastolic and end-systolic diameter, volume, and wall thickness were measured. Simpson's biplane method was used for the evaluation of the left ventricular Ejection Fraction (EF), four- and two-chamber views. Right atrial area and left atrial volume were also measured. Interpretation of measurements was performed as indicated by European Association of Cardiovascular Imaging, European Society of Cardiology and the Association for European Pediatric and Congenital Cardiology [13].
Resting ECG and Exercise Stress Testing
Resting 12-lead ECG was acquired in the supine position with the limb leads placed at the wrists and ankles at a standard speed of 25 mm/s and a gain of 1 mV/cm. Filters were set at 0.05 and 150 Hz. Electrocardiographic recordings were acquired using Quark Cosmed 2019. PR interval measurements were obtained using the automated digital output of the ECG recorder and subsequently verified by manual measurement by physicians. Interpretation of ECG was performed according to the 2017 International Recommendations for ECG interpretation in athletes [6]. Short PR interval was defined as PR < 120 ms, while first degree atrial-ventricular block as PR > 200 ms. The cut-off of < 120 ms was selected in accordance with current international criteria for ECG interpretation in athletic populations [6, 14], and was chosen deliberately to reflect the operationally relevant definition used in real-world pre-participation screening [4].
All participants participating in competitive sports underwent exercise testing under stress using the Modified Bruce Protocol. The test consisted of stages 1 to 3, each lasting 2 min, followed by 3-min exercise stages, a cooldown period, and a 4-min recovery phase. Participants were encouraged to continue the exercise testing until they reached a rate of perceived exertion of 17 out of 20 points and achieved a target heart rate (HR) of at least 85% of the maximal predicted heart rate for their age. This target HR had to be maintained for one minute or until the end of stage [15]. A 12-lead ECG was monitored before the test, continuously during the exercise, and for at least 4 min during recovery. Blood pressure (BP) was measured before the exercise stress testing, at the end of each exercise stage, immediately after recovery, and every 2 min during recovery. The presence of premature ventricular beats (PVB) and premature supraventricular beats (PSVB) was recorded. Treadmill Cosmed T150med and Omnia-Quark Cosmed 2019 analysis system were used for exercise testing.
Statistical Analysis
Missing data were excluded prior to analysis and all statistical analysis were performed on the final complete population. Continuous variables are expressed as means and standard deviations (SD), and categorical variables as numbers and percentages. Normal distribution of all continuous variables was examined using the Shapiro–Wilk test. The study sample was divided into two subgroups based on the presence of short PR interval (< 120 ms) or PR interval (≥ 120 ms). Differences between the two groups were evaluated using chi-square and Fisher's exact test for categorical variables, and Student's t-test and Mann–Whitney U test for continuous variables, as appropriate. The distribution of short PR interval was also expressed as a percentage across age quartiles.
Univariate and multivariate binary logistic regression analyses were performed to test the association of short PR interval with clinical and demographic characteristics, and odds ratios (OR) with 95% confidence intervals (CI) were calculated. Binary logistic regression models adjusted for potential confounders, including age, sex, and exercise stress testing characteristics, were used to evaluate the relationship between short PR interval and the need for further examinations, premature ventricular beats (PVBs), and premature supraventricular beats (PSVBs). To address the potential impact of applying a fixed PR interval threshold across a wide pediatric age range, a sensitivity analysis was performed using age- and sex-specific PR interval z-scores, using reference standards derived from Bratincsák et al. [16]. A z-score below − 2 was used as the age- and sex-adjusted lower limit of normal to define short PR interval. Univariate and multivariate analysis were repeated also for the sensitivity analysis. To further characterize the relationship between resting heart rate and PR interval across age groups, Spearman correlation analyses were performed within each age quartile using both the fixed binary definition (short PR < 120 ms) and the continuously distributed age- and sex-corrected PR interval Z-score.
All analyses were performed with a type I error threshold of 0.05 using STATA 16.1 SE software (Stata Corp. LP, College Station, TX, USA).
Results
Baseline Characteristics
The study sample included 1310 athletes aged 7–18 years, of whom 1161 practiced competitive sports and 149 recreational sports. Athletes were classified into four categories based on the predominant physiological demands of their sport: skill sports (12.98% of total population), power sports (15.27%), mixed sports (52.98%), and endurance sports (18.78%). Short PR interval (< 120 ms) was identified in 353 athletes (26.9%), while 957 athletes (73.1%) had PR interval (≥ 120 ms). Athletes with short PR interval were significantly younger (12.23 ± 2.69 vs. 13.84 ± 2.91 years, < 0.001) and more likely to be female (50.14% vs. 38.98%, < 0.001) compared to those with normal PR interval (Table 1).
Table 1.
Population characteristics stratified by PR interval
| Characteristics | All Population n = 1310 |
PR interval < 120 ms n = 353 |
PR interval ≥ 120 ms n = 957 |
p-value |
|---|---|---|---|---|
| Demographic characteristics | ||||
| Age, mean, SD | 13.41 ± 2.94 | 12.23 ± 2.69 | 13.84 ± 2.91 | < 0.001 |
| Female n (%) | 550 (41.98) | 177 (50.14) | 373 (38.98) | < 0.001 |
| BMI kg/m2, mean SD | 20.55 ± 3.74 | 19.65 ± 3.47 | 20.87 ± 3.47 | < 0.001 |
| Skill n (%) | 170 (12.98) | 51 (14.45) | 119 (12.43) | 0.35 |
| Power n (%) | 200 (15.27) | 46 (13.03) | 154 (16.09) | 0.19 |
| Mixed n (%) | 694 (52.98) | 192 (54.39) | 502 (52.46) | 0.57 |
| Endurance n (%) | 246 (18.78) | 64 (18.13) | 182 (19.02) | 0.75 |
| Training h/week, mean SD | 7.1 ± 2.54 | 6.97 ± 2.29 | 7.14 ± 2.63 | 0.26 |
| Family History positive for CVD n (%) | 1175 (90.52) | 318 (90.6) | 857 (90.50) | 0.36 |
| Chest pain | 50 (3.83) | 13 (3.69) | 37 (3.88) | 0.87 |
| Syncope | 129 (9.87) | 37 (10.51) | 92 (9.63) | 0.67 |
| Palpitations | 37 (2.83) | 8 (2.27) | 29 (3.04) | 0.57 |
| Echocardiography | ||||
| LVEDd cm | 4.32 ± 1.67 | 4.10 ± 0.45 | 4.40 ± 1.93 | 0.004 |
| IVSt cm | 0.72 ± 0. 11 | 0.68 ± 0.10 | 0.73 ± 0.11 | < 0.001 |
| PWt cm | 0.70 ± 0.11 | 0.66 ± 0.10 | 0.72 ± 0.11 | < 0.001 |
| EF | 60.85 ± 4.79 | 61.29 ± 4.86 | 60.69 ± 4.76 | 0.04 |
| RVd | 2.68 ± 0.66 | 2.56 ± 0.34 | 2.72 ± 0.74 | 0.003 |
| LA ml | 18.35 ± 3.20 | 16.90 ± 2.66 | 18.88 ± 3.29 | < 0.001 |
| RA cm2 | 10.83 ± 3.20 | 9.82 ± 2.66 | 11.20 ± 3.29 | < 0.001 |
| Baseline electrocardiogram and exercise stress testing | ||||
| PR interval, mean SD | 130.80 ± 20.53 | 107.69 ± 8.30 | 139.33 ± 16.79 | < 0.001 |
|
I degree a-v block n (%) |
19 (1.45) | 0 | 19 (1.99) | 0.003 |
| WPW n (%) | 2 (0.15) | 1 (0.28) | 1 (0.10) | 0.46 |
| QRS ms, mean SD | 89.94 ± 14.20 | 86.44 ± 9.92 | 91.07 ± 15.15 | < 0.001 |
| QRS axis, mean SD | 75.64 ± 27.31 | 73.24 ± 27.76 | 76.04 ± 27.13 | 0.08 |
| QTc ms, mean SD | 421.57 ± 29.04 | 422.97 ± 23.10 | 421.13 ± 30.68 | < 0.001 |
| HRrest mean SD | 74.83 ± 13.34 | 77.79 ± 13.35 | 73.74 ± 13.39 | < 0.001 |
| HRpeak, mean SD | 174.42 ± 8.53 | 173.99 ± 8.26 | 174.57 ± 8.63 | 0.30 |
| METS mean, SD | 16.56 ± 3.73 | 15.12 ± 3.73 | 17.07 ± 3.53 | < 0.001 |
| Time of exercise, mean SD | 12.56 ± 1.05 | 11.82 ± 1.09 | 12.81 ± 1.01 | < 0.001 |
| PVB ≥ 1 n (%) | 71 (6.31) | 16 (5.32) | 55 (6.67) | 0.48 |
| PSVB ≥ 1 n (%) | 94 (8.36) | 20 (6.64) | 74 (8.98) | 0.22 |
|
T-wave inversion n (%) |
67 (5.11) | 20 (5.66) | 47 (4.91) | 0.43 |
SD standard Deviation, CVD Cardiovascular diseases, HR heart rate, LVEDd Left Ventricular End-Diastolic Diameter, IVSt Intraventricular Septal thickness, PWt Posterior Wall thickness, EF Ejection Fraction, RVd Right Ventricular diameter, LA Left Atrium, RA Right Atrium, PVB premature ventricular beats, PSVB premature supraventricular beats, WPW Wolff Parkinson White
No significant differences were observed between groups regarding sport discipline distribution (skill, power, mixed, or endurance sports) or weekly training hours (6.97 ± 2.29 vs. 7.14 ± 2.63 h, p = 0.26).
Age-Related Distribution of Short PR Interval
The prevalence of short PR interval decreased significantly with age (χ2 test for trend, p < 0.001) (Fig. 1). Among athletes aged 7–10 years (first quartile), 40.5% exhibited short PR interval, decreasing progressively to 32.7% in those aged 11–12 years (second quartile), 22.5% in the 13–15 years group (third quartile), and 9.8% in athletes aged 16–18 years (fourth quartile).
Fig. 1.
Distribution of PR interval categories across age quartiles
Short PR interval (< 120 ms, red) was present in 40.5% of athletes aged 7–10 years, decreasing to 32.7%, 22.5%, and 9.8% in subsequent quartiles (χ2 test for trend, p < 0.001). Normal PR interval (≥ 120 ms) is shown in green.
Echocardiography
Athletes with short PR interval demonstrated significantly smaller cardiac dimensions across multiple parameter: left ventricular telediastolic diameter, interventricular septum thickness and posterior wall thickness, left atrial volume, and right atrial area (p < 0.001). All the above-mentioned echocardiographic values in both groups remained within age-appropriate normal limits. Ejection fraction was slightly higher in the short PR group (61.29 ± 4.86% vs. 60.69 ± 4.76%, p = 0.04), though both values remained within normal range (Table 1).
Electrocardiographic and Exercise Testing Findings
Only 2 cases of Wolff–Parkinson–White were identified. QRS duration was shorter in athletes with short PR interval (86.44 ± 9.92 vs. 91.07 ± 15.15 ms, p < 0.001), while resting heart rate was significantly higher in those with short PR (77.79 ± 13.35 vs. 73.74 ± 13.39 bpm, p < 0.001), though peak heart rate during exercise was similar between participants with and without short PR interval (173.99 ± 8.26 vs. 174.57 ± 8.63 bpm, p = 0.30). The prevalence of PVB (5.32% vs. 6.67%, p = 0.48), PVBs (6.64% vs. 8.98%, p = 0.22), and T-wave inversion (5.66% vs. 4.91%, p = 0.43) did not differ significantly between groups (Table 1).
Determinants of Short PR Interval
In multivariable logistic regression analysis adjusted for age, sex, BMI, resting heart rate, and training volume (Table 2), age remained the strongest independent predictor of short PR interval (OR 0.85, 95% CI 0.81–0.91, p < 0.001). Smaller right atrial area was independently associated with short PR interval (OR 0.93, 95% CI 0.87–0.99, p = 0.025). Female sex, BMI, resting heart rate, training volume, and endurance sport participation were not independently associated with short PR interval after multivariable adjustment.
Table 2.
The association between short PR interval, demographic, resting HR, and right atrial dimension
| Univariate | Multivariate | |||||
|---|---|---|---|---|---|---|
| OR | 95% CI | p-value | OR | 95% CI | p-value | |
| Age | 0.82 | 0.79- 0.86 | 0.0001 | 0.85 | 0.81–0.91 | < 0.001 |
| Gender (F) | 1.57 | 1.23–2.01 | 0.0001 | 1.25 | 0.95–1.65 | 0.11 |
| BMI | 0.93 | 0.90–0.96 | 0.0001 | 1.0 | 0.96–1.03 | 0.96 |
| HR rest | 1.02 | 1.01–1.03 | 0.0001 | 1.01 | 0.99–1.01 | 0.39 |
| Training | 0.97 | 0.92–1.02 | 0.26 | 1.02 | 0.97–1.08 | 0.31 |
| RAA | 0.84 | 0.81–0.89 | 0.0001 | 0.93 | 0.87–0.99 | 0.025 |
| Endurance | 0.94 | 0.68–1.29 | 0.71 | 0.72 | 0.50–1.02 | 0.07 |
OR odds Ratio, 95% CI 95% Confidence Interval, BMI Body Mass Index, HR Heart Rate, RAA Right Atrial Area
Multivariable model adjusted for age, sex, BMI, resting heart rate, training volume, right atrial area, and endurance sport participation.
Clinical Outcomes
Abnormal findings from clinical examination, anamnesis, ECG, exercise stress test, and echocardiography necessitated additional diagnostic procedures in 42 participants (3.2%). These included Holter ECG monitoring in 35 athletes (2.67%), 24-h ambulatory blood pressure monitoring in 5 athletes (0.38%), cardiac magnetic resonance imaging in 3 athletes (0.22%), coronary computed tomography in 2 athletes (0.15%), and electrophysiological study in 2 athletes (0.15%). Supplementary material Fig. 1 summarizes study flowchart.
After multivariable adjustment for demographic and training characteristics (Table 3), short PR interval showed no significant independent association with syncope (OR 1.46, 95% CI 0.95–2.25, p = 0.08), palpitations (OR 0.85, 95% CI 0.37–1.95, p = 0.71), premature ventricular beats (OR 1.27, 95% CI 0.69–2.34, p = 0.43), or premature supraventricular beats (OR 1.05, 95% CI 0.62–1.81, p = 0.83) during exercise testing.
Table 3.
The role of short PR interval on PVB, PSVB, and necessity to require further examinations for sports eligibility
| Univariate | Multivariate | |||||
|---|---|---|---|---|---|---|
| OR | 95% CI | p-value | OR | 95% CI | p-value | |
| Syncope | ||||||
| Short PR interval | 1.10 | 0.74–1.64 | 0.63 | 1.46a | 0.95–2.25 | 0.08 |
| Palpitations | ||||||
| Short PR interval | 0.74 | 0.33–1.63 | 0.46 | 0.85b | 0.37–1.95 | 0.71 |
| PVB | ||||||
| Short PR interval | 0.78 | 0.44–1.39 | 0.41 | 1.27c | 0.69–2.34 | 0.43 |
| PSVB | ||||||
| Short PR interval | 0.72 | 0.43–1.20 | 0.21 | 1.05d | 0.62–1.81 | 0.83 |
| Further examinations | ||||||
| Short PR interval | 1.08 | 0.54–2.14 | 0.81 | 1.55e | 0.68–3.55 | 0.28 |
OR odds Ratio, 95% CI 95% Confidence Interval, PVB Premature ventricular beats, PSVB Premature Supraventricular beats
a and b: multivariable model adjusted for: age, sex, total training, heart rate at rest.
c and d: multivariable model adjusted for: age, sex, total training, heart rate at rest.
e: multivariable model adjusted for: age, sex, total training, premature ventricular beats, T-wave inversion.
Short PR interval was not independently associated with the need for further examinations for sports eligibility determination (OR 1.55, 95% CI 0.68–3.55, p = 0.28) after adjustment for age, sex, training volume, premature ventricular beats, and T-wave inversion.
Sensitivity Analysis Using Age- and Sex-Adjusted Z-Score Thresholds
Using a z-score threshold of − 2 as the age- and sex-adjusted lower limit of normal, 3.82% of the athletes met criteria for a short PR interval. The prevalence of short PR interval was uniformly low across all age quartiles: 2.13% in athletes aged 7–10 years, 5.50% in those aged 11–12 years, 4.45% in those aged 13–15 years, and 2.93% in those aged 16–18 years (p = 0.679). Resting hear rate resulted significantly associated with z-score defined short PR interval (p = 0.013). No significant association was found between z-score-defined short PR interval and any clinical outcome, including syncope (OR 1.63 95% CI 0.71–3.71, p = 0.24), palpitations (OR 1.41, 95% CI 0.32–6.07, p = 0.64), PVB beats (OR 1.43, 95% CI 0.49–4.11, p = 0.50), PSVB (OR 0.78, 95% CI 0.23–2.55, p = 0.67), or need for additional examinations (OR 1.50, 95% CI 0.20–11.18, p = 0.69). The results of this sensitivity analysis are presented in Supplementary Table 1.
Age-Stratified Correlations between PR Interval and Resting Heart Rate
Using the fixed threshold, the correlation between short PR interval and resting HR was non-significant in the three younger quartiles (Q1: r = 0.091, p = 0.101; Q2: r = 0.027, p = 0.634; Q3: r = − 0.008, p = 0.875 Supplementary Material Table 2), with only a significant association in the oldest quartile (Q4: r = 0.129, p = 0.034). Using the age- and sex-corrected PR interval z-score, the correlation with resting HR was absent in the youngest quartile (Q1: r = 0.004, p = 0.940) and progressively strengthened with advancing age (Q2: r = 0.101, p = 0.068; Q3: r = 0.100, p = 0.052; Q4: r = 0.195, p = 0.001).
Discussion
In a comprehensive cohort of 1310 young athletes aged 7–18 years undergoing sports pre-participation screening, the prevalence of short PR interval in young athletes resulted as 26.9% when a fixed cut-off is applied and only 3.82% using age and sex-adjusted z-score criteria. Importantly, isolated short PR interval with both criteria was not associated with cardiac symptoms, exercise-induced arrhythmias, or the need for additional cardiac evaluation prior to sports eligibility clearance.
The prevalence of short PR interval in previous studies has been reported to range between 0.6 and 15% [8, 17]. In our study the high prevalence rate found by a fixed cut-off may be attributed to the inclusion of a broader age range children in whom short PR intervals are physiologically more common. Fixed cut-off is more inclusive than lower limits of normality derived from a pediatric ECG normative dataset [16] and may capture a broad physiological spectrum in the context of screening. In addition, when the z-score-based definition was applied, the prevalence of short PR interval was uniformly lower across all age quartiles, differently from the progressive decline observed using the fixed < 120 ms threshold. This finding suggests that the age-related variation in PR interval prevalence may reflect normal cardiac developmental physiology.
Furthermore, resting heart rate resulted significantly associated with short PR interval and this association was more pronounced with advancing age. It has been reported that the PR interval during resting 12 lead ECGs in children varies mainly in relation to heart rate and in infants with heart rate of approximately 100–150 beats/min, the PR interval is expected to range between 80 and 110 ms [7]. A previous study showed a linear increase in sympathetic activity and a non‐linear pattern for parasympathetic activity with an exponential increase from infancy to childhood, followed by a decrease to adolescence [18], and in most of the studies ECG parameters demonstrated consistent age-dependent developmental patterns [19–21]. Our findings support the interpretation that resting heart rate functions as a partial mediator rather than a confounder in the relationship between age and PR interval. In younger children, PR interval is predominantly determined by age-related physiological factors such as autonomic maturation, cardiac structural growth, and AV nodal electrophysiological development [22, 23]. In older adolescents, where age-related developmental changes are less pronounced, the independent contribution of resting heart rate to PR interval duration becomes more apparent. Age leads to autonomic maturation, baseline heart rate reduction, and consequently PR interval prolongation, with heart rate representing a possible mediator through which age influences AV nodal conduction.
The observed differences in cardiac dimensions between athletes with and without short PR interval are attributable to the significantly younger age and smaller body habitus of athletes with short PR interval, rather than reflecting intrinsic cardiac morphological abnormalities [13]. Similarly, the lower exercise capacity observed in the short PR group reflected by lower METs and shorter exercise duration is most plausibly explained by the younger age of these athletes, given the well-established relationship between somatic growth and cardiorespiratory fitness in the pediatric population [24].
The observation that training volume and sport discipline did not independently predict PR interval duration deserves comment. While athletic training induces well-documented cardiac adaptations, including increased vagal tone and structural remodeling, these effects appear to be more pronounced in adult athletes with longer training histories [25–27]. It should be mentioned that PR interval duration is influenced also by the genetic background which may vary across ethnic and geographic populations. A large community‐based cohort showed prominent race differences in PR interval and other ECG characteristics [28]. Genetic variations, associated with ion channel regulation may be more prevalent in specific racial groups, impacting AV conduction and ECG waveforms [29, 30]. Geographic populations often differ in lifestyle habits, physical activity, and also different access to healthcare and preventive services [31].
The 2017 International Criteria for ECG Interpretation in Athletes and the 2018 updated recommendations [6, 14] do not mandate additional workup for isolated short PR interval in the absence of a delta wave or symptoms, but were developed primarily in adult and older adolescent populations. Our findings extend this framework to a younger age spectrum, providing the pediatric-specific evidence that was previously understudies and reinforcing the core principle that not all ECG deviations from adult norms require further investigation. In this regard, our results are consistent with Abela et al. [8] and Velasquez-Rodriguez et al. [17], prior studies addressing short PR interval specifically in young athletes, while adding substantially greater sample size, a wider age range, and a dual-threshold methodology incorporating age- and sex-adjusted z-scores.
A key finding of our study with clinical relevance is that isolated short PR interval was not associated with cardiac symptoms, exercise-induced arrhythmias, or the need for additional cardiac examinations prior to sports eligibility clearance, suggesting that it may not warrant automatic referral for further evaluation in asymptomatic young athletes within the context of pre-participation screening. These findings remained consistent after multivariable adjustment for potential confounders including age, sex, training volume, and heart rate. Overall, only 3.2% of athletes in our cohort required additional diagnostic procedures beyond the standard pre-participation screening protocol. The distribution of additional testing was similar between athletes with short and normal PR intervals, suggesting that isolated short PR interval should not automatically prompt additional costly and time-consuming diagnostic testing in asymptomatic young athletes.
It should be mentioned that the clinical approach to short PR interval must distinguish between benign findings and pathological conditions. It is crucial to emphasize that our conclusions apply specifically to short PR interval without ventricular pre-excitation. Two cases of WPW pattern were identified in our screening program, representing 0.15% of the total cohort. Athletes with documented WPW pattern require careful risk stratification, typically including electrophysiological study to assess accessory pathway properties, and may need prophylactic catheter ablation [32, 33].
From a healthcare economics perspective, our findings suggest that recognizing isolated short PR interval as a normal variant could substantially reduce unnecessary diagnostic testing in pediatric sports screening programs. With millions of young athletes undergoing pre-participation evaluation annually worldwide, avoiding unnecessary Holter monitoring, advanced imaging, or electrophysiological studies in athletes with isolated short PR intervals could contribute to more resource-efficient screening programs without compromising safety [34]. Of note, the integration of artificial intelligence technologies may enable a more accurate risk stratification and complement the expertise of physicians, allowing for a balanced approach that optimizes patient care and outcomes [35, 36].
Several limitations should be acknowledged. First, the design of our study is cross-sectional and precludes longitudinal assessment of PR interval changes within individual athletes over time. Prospective studies following young athletes through adolescence would provide valuable insights into individual trajectories of PR interval evolution. Second, our cohort consisted exclusively of Italian athletes, from a single regional center represents a potential limitation to the ethnic and geographic generalizability of our findings. The applicability of our conclusions to screening programs in populations of different ethnic backgrounds or geographic regions should be considered with caution until confirmed by multicenter studies enrolling more diverse athletic cohorts. Additionally, the need for further testing outcome is inherently embedded within the screening process itself, raising the possibility of incorporation bias. Moreover, the low number of participants requiring additional examinations limits the statistical power of this analysis and should be interpreted with appropriate caution. Furthermore, although multivariable models were adjusted for age, the wide age range of our cohort means that residual age-related confounding cannot be entirely excluded. Many of the observed between-group differences in cardiac dimensions and exercise capacity are likely driven by developmental stage rather than by PR interval per se, and should be interpreted accordingly. A further limitation is the use of a fixed PR interval cut-off (< 120 ms) across the full pediatric age range. Although a sensitivity analysis using age- and sex-adjusted z-score thresholds confirmed the robustness of our findings, validated age-specific normative reference values for PR interval in pediatric athletes remain to be established. Finally, we lacked long-term follow-up data to assess the natural history and potential cardiovascular outcomes associated with short PR interval in young athletes. Future studies with extended follow-up periods would help confirm the benign prognosis suggested by our cross-sectional findings.
Conclusions
The prevalence of short PR interval in young athletes varies considerably depending on the definition threshold applied, ranging from 3.82% when age and sex-adjusted z-score criteria are applied to 26.9% using a fixed cut-off. Using both definitions isolated short PR interval was not associated with cardiac symptoms, exercise-induced arrhythmias, or need for additional diagnostic evaluation, reflecting normal cardiac developmental physiology. Our data provide evidence-based guidance for interpreting short PR intervals in young athletes and may reduce unnecessary medical procedures and costs in sports screening programs while maintaining safety. However, these findings apply specifically to the context of sports pre-participation screening in children and adolescent athletes, and assessment of long-term arrhythmic risk requires further prospective longitudinal studies.
Acknowledgements
Not applicable.
Abbreviations
- WHO
World Health Organization
- SPPS
Sports pre-participation screening
- CT
Computer tomography
- ECG
Electrocardiogram
- HR
Heart rate
- BMI
Body mass index
Author Contributions
KK contributed to the conception and design of the study. KK, GR, LA, GDF, and GG contributed to the acquisition, analysis, and interpretation of data. KK, GG, and GR drafted the manuscript. ADI and GG critically revised the manuscript. All authors gave final approval of the final version and agree to be accountable for all aspects of work ensuring integrity and accuracy.
Funding
This work was supported by Interreg SPA south Adriatic, co-founded by the EU project Touristfit SA-0300562 and by MOLISE MULTICARE ACTIVE: Percorso Integrato di Valutazione, Gestione e Prescrizione dell'Esercizio Terapeutico per Pazienti con Multicronicità, Percorso Diagnostico Terapeutico Condiviso e Personalizzato per Pazienti con Multicronitcità Regione Molise, Piano Sanitario Nazionale 2024–2025.
Data Availability
The dataset analyzed during the current study are available from the corresponding author on reasonable request.
Declarations
Ethics Approval and Consent to Participate
This study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of Department of Medicine and Health Sciences, University of Molise, protocol number 18/23. All participants provided informed written consent for anonymous data collection prior to the study.
Competing Interests
All authors declare no competing interests.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Organization. WH. WHO Guidelines on Physical Activity and Sedentary Behaviour. World Health Organization; 2020. http://www.ncbi.nlm.nih.gov/books/NBK566045/. Accessed July 19 2024. [PubMed]
- 2.Deng Y, Fan A. Trends in sports participation in adolescents: data from a large-scale sample in the US adolescents. Front Public Health. 2022;10:960098. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Emmonds S, Till K, Weaving D, Burton A, Lara-Bercial S. Youth sport participation trends across Europe: implications for policy and practice. Res Q Exerc Sport. 2024;95(1):69–80. [DOI] [PubMed] [Google Scholar]
- 4.Zeppilli P, Biffi A, Cammarano M, Castelletti S, Cavarretta E, Cecchi F, et al. Italian Cardiological Guidelines (COCIS) for competitive sport eligibility in athletes with heart disease: update 2024. Minerva Med. 2024;115(5):533–64. [DOI] [PubMed] [Google Scholar]
- 5.Graziano F, Schiavon M, Cipriani A, Savalla F, De Gaspari M, Bauce B, et al. Causes of sudden cardiac arrest and death and the diagnostic yield of sport preparticipation screening in children. Br J Sports Med. 2024;58(5):255–60. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Drezner JA, Sharma S, Baggish A, Papadakis M, Wilson MG, Prutkin JM, et al. International criteria for electrocardiographic interpretation in athletes: consensus statement. Br J Sports Med. 2017;51(9):704–31. [DOI] [PubMed] [Google Scholar]
- 7.Dickinson DF. The normal ECG in childhood and adolescence. Heart. 2005;91(12):1626–30. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Abela M, Grech N, Degiorgio S, Grech V, Adrian Sammut M. Isolated short PR interval in adolescent athletes and non-athletes: should we worry? Hellenic J Cardiol. 2023;72:65–6. [DOI] [PubMed] [Google Scholar]
- 9.Solberg EE, Borjesson M, Sharma S, Papadakis M, Wilhelm M, Drezner JA, et al. Sudden cardiac arrest in sports - need for uniform registration: a position paper from the Sport Cardiology Section of the European Association for Cardiovascular Prevention and Rehabilitation. Eur J Prev Cardiol. 2016;23(6):657–67. [DOI] [PubMed] [Google Scholar]
- 10.Pelliccia A, Sharma S, Gati S, Back M, Borjesson M, Caselli S, et al. 2020 ESC Guidelines on sports cardiology and exercise in patients with cardiovascular disease. Eur Heart J. 2021;42(1):17–96. [DOI] [PubMed] [Google Scholar]
- 11.Lang RM, Badano LP, Mor-Avi V, Afilalo J, Armstrong A, Ernande L, et al. Recommendations for cardiac chamber quantification by echocardiography in adults: an update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging. J Am Soc Echocardiogr. 2015;28(1):1-39 e14. [DOI] [PubMed] [Google Scholar]
- 12.Lopez L, Saurers DL, Barker PCA, Cohen MS, Colan SD, Dwyer J, et al. Guidelines for performing a comprehensive pediatric transthoracic echocardiogram: recommendations from the American Society of Echocardiography. J Am Soc Echocardiogr. 2024;37(2):119–70. [DOI] [PubMed] [Google Scholar]
- 13.Cantinotti M, Di Salvo G, Voges I, Raimondi F, Greil G, Ortiz Garrido A, et al. Standardization in paediatric echocardiographic reporting and critical interpretation of measurements, functional parameters, and prediction scores: a clinical consensus statement of the European Association of Cardiovascular Imaging of the European Society of Cardiology and the Association for European Paediatric and Congenital Cardiology. Eur Heart J Cardiovasc Imaging. 2024;25(8):1029–50. [DOI] [PubMed] [Google Scholar]
- 14.Sharma S, Drezner JA, Baggish A, Papadakis M, Wilson MG, Prutkin JM, et al. International recommendations for electrocardiographic interpretation in athletes. Eur Heart J. 2018;39(16):1466–80. [DOI] [PubMed] [Google Scholar]
- 15.Tanaka H, Monahan KD, Seals DR. Age-predicted maximal heart rate revisited. J Am Coll Cardiol. 2001;37(1):153–6. [DOI] [PubMed] [Google Scholar]
- 16.Bratincsak A, Kimata C, Limm-Chan BN, Vincent KP, Williams MR, Perry JC. Electrocardiogram Standards for Children and Young Adults Using Z-Scores. Circ Arrhythm Electrophysiol. 2020;13(8):e008253. [DOI] [PubMed] [Google Scholar]
- 17.Velasquez-Rodriguez J, Diaz-Gonzalez L, Valenzuela PL, Bruna V, Boraita A, Lucia A. Preparticipation screening in pediatric athletes. Should we be concerned about the PR interval? Revista Española de Cardiología (English Edition). 2021;74(6):556–8. [DOI] [PubMed] [Google Scholar]
- 18.Harteveld LM, Nederend I, Ten Harkel ADJ, Schutte NM, de Rooij SR, Vrijkotte TGM, et al. Maturation of the Cardiac Autonomic Nervous System Activity in Children and Adolescents. J Am Heart Assoc. 2021;10(4):e017405. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Semizel E, Ozturk B, Bostan OM, Cil E, Ediz B. The effect of age and gender on the electrocardiogram in children. Cardiol Young. 2008;18(1):26–40. [DOI] [PubMed] [Google Scholar]
- 20.Lue HC, Wu MH, Wang JK, Lin MT, Lu CW, Chiu SN, et al. Normal ECG standards and percentile charts for infants, children and adolescents. Pediatr Neonatol. 2023;64(3):256–73. [DOI] [PubMed] [Google Scholar]
- 21.Miliaraki M, Germanakis I. Pediatric electrocardiogram in preparticipation screening: narrative review of normal values in key features. Children. 2026;13:2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.O’Connor M, McDaniel N, Brady WJ. The pediatric electrocardiogram: part I: Age-related interpretation. Am J Emerg Med. 2008;26(4):506–12. [DOI] [PubMed] [Google Scholar]
- 23.Gourdie RG, Harris BS, Bond J, Justus C, Hewett KW, O’Brien TX, et al. Development of the cardiac pacemaking and conduction system. Birth Defects Res C Embryo Today. 2003;69(1):46–57. [DOI] [PubMed] [Google Scholar]
- 24.Dimitri P, Joshi K, Jones N. Moving more: physical activity and its positive effects on long term conditions in children and young people. Archives of disease in childhood. 2020;105(11):1035–40. [DOI] [PubMed] [Google Scholar]
- 25.Sharma S, Maron BJ, Whyte G, Firoozi S, Elliott PM, McKenna WJ. Physiologic limits of left ventricular hypertrophy in elite junior athletes: relevance to differential diagnosis of athlete’s heart and hypertrophic cardiomyopathy. J Am Coll Cardiol. 2002;40(8):1431–6. [DOI] [PubMed] [Google Scholar]
- 26.Sharma S, Whyte G, Elliott P, Padula M, Kaushal R, Mahon N, et al. Electrocardiographic changes in 1000 highly trained junior elite athletes. Br J Sports Med. 1999;33(5):319–24. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Komici K, D’Amico F, Verderosa S, Piomboni I, D’Addona C, Picerno V, et al. Impact of body composition parameters on lung function in athletes. Nutrients. 2022;14:18. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Santhanakrishnan R, Wang N, Larson MG, Magnani JW, Vasan RS, Wang TJ, et al. Racial differences in electrocardiographic characteristics and prognostic significance in whites versus Asians. J Am Heart Assoc. 2016;5(3):e002956. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Ackerman MJ, Tester DJ, Jones GS, Will ML, Burrow CR, Curran ME. Ethnic differences in cardiac potassium channel variants: implications for genetic susceptibility to sudden cardiac death and genetic testing for congenital long QT syndrome. Mayo Clin Proc. 2003;78(12):1479–87. [DOI] [PubMed] [Google Scholar]
- 30.Zheng J, Ani C, Abudayyeh I, Zheng Y, Rakovski C, Yaghmaei E, et al. A review of racial differences and disparities in ECG. Int J Environ Res Public Health. 2025. 10.3390/ijerph22030337. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Bell CN, Thorpe RJ Jr., Bowie JV, LaVeist TA. Race disparities in cardiovascular disease risk factors within socioeconomic status strata. Ann Epidemiol. 2018;28(3):147–52. [DOI] [PubMed] [Google Scholar]
- 32.Raimondo C, Flore F, Alberio AMQ, Garibaldi S, Campisi M, Tamburri I, et al. Impact of growth on electrophysiological properties of ventricular pre-excitation in paediatric athletes. Cardiol Young. 2025;35(2):261–6. [DOI] [PubMed] [Google Scholar]
- 33.Sarubbi B, D’Alto M, Vergara P, Calvanese R, Mercurio B, Russo MG, et al. Electrophysiological evaluation of asymptomatic ventricular pre-excitation in children and adolescents. Int J Cardiol. 2005;98(2):207–14. [DOI] [PubMed] [Google Scholar]
- 34.Fuller C, Scott C, Hug-English C, Yang W, Pasternak A. Five-year experience with screening electrocardiograms in National Collegiate Athletic Association Division I athletes. Clin J Sport Med. 2016;26(5):369–75. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Palermi S, Vecchiato M, Ng FS, Attia Z, Cho Y, Anselmino M, et al. Artificial intelligence and the electrocardiogram: a modern renaissance. Eur J Intern Med. 2025;140:106329. [DOI] [PubMed] [Google Scholar]
- 36.Palermi S, Vecchiato M, Saglietto A, Niederseer D, Oxborough D, Ortega-Martorell S, et al. Unlocking the potential of artificial intelligence in sports cardiology: does it have a role in evaluating athlete’s heart? Eur J Prev Cardiol. 2024;31(4):470–82. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The dataset analyzed during the current study are available from the corresponding author on reasonable request.