Athlete's ECG Research Articles

Athlete's ECG Made Easy: A Practical Guide to Surviving Everyday Clinical Practice.

Electrocardiogram modifications in athletes are common and usually reflect structural and electrical heart adaptations to regular physical training, known as the athlete's heart. However, these electrical modifications sometimes overlap with electrocardiogram findings that are characteristic of various heart diseases. A missed or incorrect diagnosis can significantly impact a young athlete's life and potentially have fatal consequences during exercise, such as sudden cardiac death, which is the leading cause of death in athletes. Therefore, it is crucial to correctly distinguish between expected exercise-related electrocardiogram changes in an athlete and several electrocardiogram abnormalities that may indicate underlying heart disease. This review aims to serve as a practical guide for cardiologists and sports clinicians, helping to define normal and physiology-induced electrocardiogram findings from those borderlines or pathological, and indicating when further investigations are necessary. Therefore, the possible athlete's electrocardiogram findings, including rhythm or myocardial adaptation, will be analyzed here, focusing mainly on the differentiation from pathological findings.

Interpretation of athlete's ECG in a pediatric population using the International Criteria

Interpretation of athlete's ECG in a pediatric population using the International Criteria

Prevalence and determinants of low QRS voltages and QRS fragmentation in children and adolescents undergoing sports pre-participation screening.

Low QRS voltages (LQRSV) in limb leads and QRS fragmentation (FQRS) are possible electrocardiographic signs of myocardial fibrosis and cardiomyopathy, but they are not listed in current criteria for interpreting athlete's electrocardiogram (ECG). We investigated the prevalence and determinants of LQRSV and FQRS in a cohort of young apparently healthy athletes undergoing pre-participation screening (PPS). We analysed a consecutive series of 2140 ECG obtained during PPS of young athletes (mean age 12.5 ± 2.6 years, 7-18-year-old, 49% males). The peak-to-peak QRS voltage was measured in all limb leads, and LQRSV were defined when maximum value was <0.5 mV. Fragmented QRS morphologies were grouped into five patterns. Lead aVR was not considered. Maximum peak-to-peak QRS voltage in limb leads was 1.4 ± 0.4 mV, similar between younger and older athletes, but significantly lower in females than males (1.35 ± 0.38 mV vs. 1.45 ± 0.42 mV; P < 0.001). There was a weak correlation between maximal QRS voltages and body mass index (BMI), but not with type of sport or training load. Only five (0.2%) individuals showed LQRSV. At least one fragmented QRS complex was identified in 831 (39%) individuals but excluding the rSr' pattern in V1-V2, only 10 (0.5%) showed FQRS in ≥2 contiguous leads. They were older than those without FQRS, but did not differ in terms of gender, BMI, type of sport, or training load. Low QRS voltages in limb leads and FQRS in ≥2 contiguous leads excluding V1-V2 are rare in young apparently healthy athletes and are not related to the type and intensity of sport activity. Therefore, they may require additional testing to rule out an underlying disease particularly when other abnormalities are present.

Analyzing ECG signals in professional football players using machine learning techniques

BackgroundFootball player's health is important, and preventing sudden cardiac arrest may be a critical issue. Professional football players have different ECG signals than the average population, yet there are considerable gaps in study whereas the general population has been extensively studied. Objectives(a) Generate a reference and innovative resting 12-lead ECG database from 54 UEFA PRO level male football players from La Liga. This is a novel approach to cope the ECG and possible arrythmias in athletes. (b) Manage each XML athlete ECG data and develop a free-use program to visualize, denoise and filter the signal with the capacity to automate the labelling of the waves and save the reports. (c) Study the ECG wave shape and generate models through ML to analyse its utility to automate basic diagnosis. MethodsThe dataset collection is based on a prospective observational cohort and includes 10 s, 12-lead ECGs and rhythm and condition labels for each athlete. Physiological sport arrhythmias, T-Wave shape and other findings were studied and labelled. ECG Visualizer was developed and used for 3 machine learning (ML) methods to automate sinus bradycardia arrhythmia diagnosis. ResultsA dataset with 163 ECGs in XML format was collected comprising the Pro Football 12-lead Resting Electrocardiogram Database (PF12RED). “ECG Visualizer” software was developed, and ML was shown to be useful in detecting sinus bradycardia. ConclusionsThe study demonstrates that AI and machine learning can detect simple arrhythmias with accuracy, also it provides a valuable dataset and a free software application.

The Fragmented QRS Complex in Lead V1: Time for an Update of the Athlete’s ECG?

Differentiating between ECG patterns related to athletes' heart remodeling and pathological findings is a challenge in sports cardiology. As the significance of fragmented complex in athletes remains uncertain, this study aimed to assess the presence of fragmented QRS in lead V1 (fQRSV1) among young athletes and its association with heart adaptations and arrhythmias. Young athletes referred for annual pre-participation screening receiving a maximal exercise testing and transthoracic echocardiography from January 2015 to March 2021 were included. The study included 684 young athletes. The prevalence of fQRSV1 was 33%. Subjects with fQRSV1 had higher exercise capacity and indexes of right ventricular function and remodeling. Among highly trained athletes, the fQRSV1 group demonstrated also increased left ventricular wall thickness. No significant association existed between fQRSV1 and exercise-induced arrhythmias, even in highly trained athletes. The high prevalence of fQRSV1 in young athletes is associated with training-induced heart adaptations but not exercise-induced ventricular arrhythmias.Graphical The fragmented QRS complex in lead V1 in young athletes. PPS = preparticipation screening; EST = exercise stress test; fQRSV1 = fragmented QRS in lead V1; PSBs = premature supraventricular beats; PVBs = premature ventricular beats.

Clinical outcomes of 10 years of cardiac screening in elite New Zealand athletes

ObjectivesTo report findings from the High Performance Sport New Zealand cardiac screening programme, including comparisons between sexes and ethnicities. DesignRetrospective cohort study. MethodsElite Olympic-sport athletes were screened (2012–2022) with personal/family history, physical examination, resting 12-lead ECG and followed from the date of first screening until July 2022. An audit reviewed screening records, including demographic data, ECGs, follow-up and diagnoses. Flagged/equivocal ECGs were re-reviewed (International Criteria). Results2075 ECGs from 1189 athletes (53 % female, mean age 21 years; 83 % European, 9 % Māori, 5 % Pacific Islander, 3 % other) were included. No athletes retired for cardiac reasons; there were no cardiac deaths or major cardiac incidents (mean follow-up from first screening: 6.1 years (range: 0.6–10.9 years)). Diagnoses included Wolff-Parkinson-White (WPW) syndrome (0.7 %) and cardiomyopathies (0.3 %). Overall, 3.5 % of ECGs were abnormal, with ECGs of females more commonly abnormal (4.4 % vs 2.5 %, p = 0.02) and with a higher proportion of ECGs with abnormal T-wave inversion (TWI) (3.1 % vs 0.9 %, p < 0.001) compared to males. Of the abnormal TWI in females (all aged ≥16 years), 47 % was limited to V1–V3 with no other abnormalities. Abnormality rates were similar between Māori, Pacific Islander and European athlete ECGs. ConclusionsWPW was the most frequent diagnosis, with very little cardiomyopathy found. The proportion of abnormal ECGs was low overall, but higher in females. This was driven by anterior TWI in V1–V3 which was not associated with diagnoses of conditions associated with sudden cardiac death (SCD). There was no difference in the proportion of abnormal ECGs of Māori or Pacific Island athletes compared to European athletes.

Abstract 14679: Electrocardiogram Findings From Athletic Adaptation and COVID-19 Infection in Collegiate Football Players

Introduction: Improved criteria have enhanced the sensitivity and specificity of the 12-lead ECG to identify underlying cardiovascular conditions predisposing to sudden cardiac death or morbidity. However, the impacts of chronic high-intensity exercise and especially ethnicity on changes in longitudinal ECG remain unknown. Furthermore, given the ongoing pandemic, we must consider how COVID19 infection may impact ECG findings. We analyzed collegiate student athlete ECGs over time to determine whether longitudinal training, race, and post-COVID19 status impact the ECG findings with the goal of informing future interpretation criteria. Methods: We included twenty-two NCAA Division I football players from January 2018 to January 2021. Ten athletes contracted COVID19 during this period. We compared pre-season ECGs prior to the first and third years of athletic participation as well as any within 34 days after confirmed COVID19 infection. Heart rate, QRS duration, QT interval, and any International Criteria findings were identified. The ECGs acquired prior to the athlete’s first-year of participation served as the baseline for comparison for the third-year and post-COVID19 ECG. T-tests and two-sample z-tests were used as appropriate for statistical analysis. Results: Compared to matched first-year baseline, the QRS duration of post-COVID19 ECGs was significantly longer (102 ± 26 ms vs 100 ± 31 ms, p = 0.01, 95% CI 0.62-3.77), which was not seen when compared to matched third-year ECGs. There were no other significant differences between white and black athletes, or those of third-year ECGs compared to the matched first-year baseline. Conclusions: In this small cohort of 22 athletes, there was no significant change in heart rate, QRS duration, QT interval, or International Criteria classifications, including early repolarization and voltage, between first- and third-year ECGs of white and black athletes. Although the post-COVID19 QRS duration was significantly increased compared to first-year ECGs, the range was still within normal; there was no increase with respect to third-year ECGs. Further analysis of a larger sampling of athletes of different sexes and sports that also considers the impact of training on the post-COVID ECG is ongoing.

Patterns of resting electrocardiogram of male college track and field athletes

This study sought to determine the resting Electrocardiogram of male college Track and Field athletes, with a view to identifying electrocardiographic changes attributable to cardiac adaptations and possible differences in ECG morphologies by the athletic event. A descriptive survey design was used in the study. The population was male track and field athletes of Obafemi Awolowo University (OAU), Ile-Ife, Nigeria. Eighteen athletes; track (n=10) and field (n=8), were purposively selected from the OAU Athletics team that participated in the 14th West-African Universities’ Games, held at the University of Port-Harcourt, Rivers State Nigeria in 2018. Resting ECG was recorded with a 12-lead Electrocardiograph (SCHILLER-Cardiovit AT-2 plus), blood pressure was recorded with a digital blood pressure monitor (OMRON-M6 Comfort), weight, height, and BMI were recorded with an electronic BMI scale (SECA-220). Descriptive statistic of mean and standard deviation was computed and a paired-sample t-test was used to compare the resting ECG of athletes in the two divisions. Track and field athletes had mean RR-interval, P-wave, PR-interval, QRS-interval, QT-interval, and QTc of 993.22 ± 111.51ms, 97.12 ± 10.87ms, 157.00 ± 34.34ms, 120.67 ± 58.22ms, 376.94 ± 55.34ms and 416.78 ± 46.98mm respectively. With regards to voltage, athletes had mean voltages of 0.11 ± 0.09mm, -0.98 ± 0.77mm, and 1.54 ± 0.73mm for P-wave in lead II, S in VI, and R in V5 respectively. When athletes’ ECGs in the two divisions were compared, a significant difference was only found in the RR-interval (t = -3.08; P &amp;lt; 0.05). The study concluded that there were no distinctive morphological differences in the resting ECG of Nigerian collegiate track and field athletes.

The Impact of Ethnicity on Athlete ECG Interpretation: A Systematic Review

Athlete ECG interpretation criteria have been developed and refined from research in athlete populations; however, current guidelines are based on available data primarily from Caucasian and Black athletes. This study aimed to assess the impact of ethnicity on ECG interpretation in athletes. A systematic review was conducted of the MEDLINE, EMBASE, Scopus, SPORTDiscus, and Web of Science databases, for papers that assessed athlete screening ECGs and compared findings on the basis of ethnicity. Fifty-one papers which compared ECGs from various ethnicities were included. Most studies assessed Black athletes against Caucasian athletes and found a greater prevalence of T-wave inversion (TWI) (2.6–22.8% vs. 0–5.0%) and anterior TWI (3.7–14.3% vs. 0.6–2.0%). Black athlete subgroups in Africa had TWI (20–40%) and anterior TWI (4.3–18.7%) at a higher prevalence than other Black athletes. Athletes who were defined as mixed-race, Asian, and Pacific Islander are potentially more like Black athletes than Caucasian athletes. Black ethnicity is known to have an impact on the accurate interpretation of athlete ECGs; however, there is nuance related to origin of both parents. Asian and Pacific Islander origin also may impact athlete ECG interpretation. Further research is required to assist in distinguishing abnormal and normal athlete ECGs in different ethnic populations.

ECG in Athletes: Limits of Normal

ECG in Athletes: Limits of Normal

The Impact of Ethnicity on Electrocardiogram (ECG) Interpretation For Athletes: A Systematic Review

Athlete ECG interpretation criteria have been developed and refined from research in athlete populations. Ethnicity is known to play a role in cardiac adaptation, however current guidelines are based on available data primarily from Caucasian and African American athletes.

Analysis of Athlete QT Intervals by Age: Fridericia and Hodges Heart Rate Correction Methods Outperform the Bazett's Method for Athlete ECG Screening

Analysis of Athlete QT Intervals by Age: Fridericia and Hodges Heart Rate Correction Methods Outperform the Bazett's Method for Athlete ECG Screening

Norwegian Endurance Athlete ECG Database.

Athletes often have training-induced remodeling of the heart, and this can sometimes be seen as abnormal but non-pathological changes in the electrocardiogram. However, these changes can be confused with severe cardiovascular diseases that, in some cases, can cause cardiovascular death. Electrocardiogram data from athletes is therefore important to learn more about the difference between normal athletic remodeling and pathological remodeling of the heart. This work provides a dataset of electrocardiograms from 28 Norwegian elite endurance athletes. The electrocardiograms are standard 12-lead resting ECGs, recorded for 10 seconds while the athlete's lay supine on a bench. The electrocardiograms were then interpreted by an interpretation algorithm and by a trained cardiologist. The electrocardiogram waveform data and the interpretations were stored in Python Waveform Database format and made publicly available through PhysioNet.

Estimation of anaerobic threshold by cardiac repolarization instability: a prospective validation study

BackgroundAssessing lactate (LT) or anaerobic thresholds (AT) in athletes is an important tool to control training intensities and to estimate individual performance levels. Previously we demonstrated that ECG-based assessment of cardiac repolarization instability during exercise testing allows non-invasive estimation of AT in recreational athletes. Here, we validate this method in professional and amateur team sports athletes.MethodsWe included 65 team sports athletes (32 professionals and 33 amateur athletes; 51 men, 14 women, mean age 22.3 ± 5.2 years) undergoing a standardized incremental cycle exercise test. During exercise testing a high-resolution ECG (1000 Hz) was recorded in Frank-leads configuration and beat-to-beat vector changes of cardiac repolarization (dT°) were assessed by previously established technologies. Repolarization-based AT (ATdT°) was estimated by its typical dT°-signal pattern. Additionally, LT was detected in accordance to methods established by Mader (LTMader) and Dickhuth (LTDickhuth).ResultsAll athletes performed exercise testing until exhaustion with a mean maximum workload of 262.3 ± 60.8 W (241.8 ± 64.4 W for amateur athletes and 283.4 ± 49.5 W for professional athletes). Athletes showed ATdT° at 187.6 ± 44.4 W, LTDickhuth at 181.1 ± 45.6 W and LTMader at 184.3 ± 52.4 W. ATdT° correlated highly significantly with LTDickhuth (r = 0.96, p < 0.001) and LTMader (r = 0.98, p < 0.001) in the entire cohort of athletes as well as in the subgroups of professional and amateur athletes (p < 0.001 for all).ConclusionsATdT°, defined by the maximal discordance between dT° and heart rate, can be assessed reliably and non-invasively via the use of a high-resolution ECG in professional and amateur athletes.

Pediatric athletes' ECG and diagnostic performance of contemporary ECG interpretation criteria

BackgroundElectrocardiographic (ECG) pre-participation screening(PPS) can prevent sudden cardiac death(SCD) but the Interpretation of the athlete's ECG is based on specific criteria addressed for adult athletes while few data exist about the pediatric athlete's ECG.We aimed to assess the features of pediatric athletes' ECG and compared the diagnostic performance of 2017 International ECG recommendation, 2010 European Society of Cardiology recommendation and 2013-Seattle criteria in detecting clinical conditions at risk of SCD. Methods886 consecutive pediatric athletes (mean age 11.7 ± 2.5 years; 7–16-years) were enrolled and prospectively evaluated with medical history, physical examination, resting and exercise ECG and transthoracic echocardiography during their PPS. ResultsThe most common physiological ECG patterns in pediatric athletes were isolated left ventricular hypertrophy criteria (26.9%), juvenile T-wave pattern (22%) and early repolarization pattern (13.2%). The most frequent borderline abnormalities were left axis deviation (1.8%) and right axis deviation (0.9%) while T-wave inversion (0.8%) especially located in inferior leads (0.7%) was the most prevalent abnormal findings. Seven athletes (0.79%) were diagnosed with a condition related to SCD. Compared to Seattle and ESC, the International improved ECG specificity (International = 98% ESC = 64% Seattle = 95%) with lower sensitivity (ESC and Seattle 86%vs International 57%). The false-positive rate decreases from 36% of ESC to 2.2% of International but the latter showed a higher false-negative rate(0.34%). ConclusionPediatric athletes like the adult counterpart exhibit a high prevalence of ECG abnormalities mostly representing training-related ECG adaptation. The International criteria showed a lower false-positive rate but at the cost of loss of sensitivity.

Comparison Between a 6-lead Smartphone ECG and 12-lead ECG in Athletes

Athletes sometimes experience transient arrhythmias during intense exercise, which may be difficult to capture with traditional monitors. New highly portable technology, such as 6-lead smartphone electrocardiogram (6L iECG) devices, may assist in documenting and diagnosing exercise-induced arrhythmias.

Master athletes'ECG and the diagnostic accuracy of contemporary ECG interpretation criteria

Abstract Background Over the last years, several efforts have been made to refine the ECG criteria for interpretation of young (16–35 years) competitive athlete's ECG in order to improve specificity maintaining good sensitivity. However, few data exist about the efficacy of such interpretation criteria in master athletes (over 35 years). We aimed to assess the diagnostic performance of screening based on 2017 International ECG recommendation (2017-International), 2010 European Society of Cardiology recommendation (2010-ESC) and Seattle criteria in a cohort of master athletes competing at regional and national level. Methods 506 Caucasian master athletes (mean ages 47.9±8.7, 85,6% male, 65% endurance athletes) underwent standardized medical history, physical examination, resting and exercise ECG during their pre-participation screening. ECGs were retrospectively interpreted based on 2010-ESC, Seattle-criteria and 2017-International. For the purpose of the study we included also a transthoracic echocardiography as reference, to calculate the sensibility and specificity, area under the ROC curve (AUC) was estimated as measure of discriminative ability of each ECG criteria. Athletes with abnormalities underwent further examinations according to the European Guidelines. Results Twelve athletes (2,3%) were diagnosed with a condition potentially related to SCD (1 hypertrophic cardiomyopathy, 1 Type1 Brugada Syndrome, 4 Chronic Coronary Syndromes, 2 Dilated Cardiomyopathy, 3 Aortic Dilation, 1 Moderate aortic stenosis) during the pre-participation screening. International criteria failed to identify two athletes with DCM and left axis deviation on ECG while no athletes with complete right bundle branch block showed serious structural abnormalities. The most common ECG abnormalities were left axis deviation (7,1%), left atrial enlargement (4,2%) and T wave inversion (3%). 29 athletes (5,7%) exhibited a long QT interval according to 2010-ESC and 1 athlete according to International and Seattle criteria. The false positive ECG rate was 15% for 2017-International based screening, 21,9% for Seattle based screening and 30,40% for 2010-ESC based screening while the diagnostic accuracy for pathologies at risk of SCD was 0,73 (95% CI 0,69–0,77) for 2017 International based screening; 0,81 (95% CI 0,77–0,84) for Seattle Criteria based screening and 0,77 (95% CI 0,73–0,80) for 2010-ESC based screening. Conclusion In master athletes the 2017-International ECG criteria showed inferior accuracy compared to the Seattle criteria and 2010-ESC, the least showing a higher false positive rate mostly due to lower cut-off for long QT. Furthermore complete right bundle branch block may be considered a normal finding also in master asymptomatic athletes. Accuracy of ECG criteria Funding Acknowledgement Type of funding source: None

Non Type-1 Brugada pattern, diagnostic yield of 5 ECG criteria in a young adult cohort

Abstract Introduction Distinguishing between non-Type 1 Brugada pattern (non-T1BrP) and an athlete's ECG remains challenging and may have important prognostic implications. We aimed to study prevalence and the diagnostic yield of experts and non-experts for the electrocardiographic non-T1BrP criteria in the young adults from the Sudden Cardiac Death-Screening Of risk factorS (SCD-SOS) cohort. Methods We performed a cross-sectional study in which we reviewed 14662 ECGs of SCD-SOS survey participants and selected 2494 that presented a rSr'-pattern in V1-V2. Among these, 98 were classified by experts in hereditary arrhythmic syndromes for the presence of non-T1BrP and by non-experts who performed manual measurements of the diagnostic criteria based on triangle formed by r'-wave. We estimated intra and interobserver concordance for each criterion, and used logistic regression and receiver operating characteristics (ROC) analysis and C-statistics for diagnostic accuracy and definition of the most appropriate cut-off values. Results We detected a rSr'-pattern in V1-V2 in 17% of the individuals and found that it was associated with higher PQ and QTc intervals, male gender and lower BMI. The manual measurements of non-T1BrP criteria were reproducible: we had high intraobserver concordance coefficients (CC) ranging from 0.90 to 0.94 (except for d(B) that had 0.66), but interobserver CC were lower (0.45–0.68). The measurements performed were highly correlated with non-T1BrP diagnosis and the criteria with higher discriminatory capacity were the distance d(B) (AUC 0.77; 95% CI0.69–0.84) and the degree of ST-ascent (AUC 0.79; 95% CI 0.72–0.86). The cut-offs defined by other authors had very low sensitivity (8–12%), despite high specificity (98%), so we defined new cut-offs: d(A) ≥2mm, d(B) ≥1.25mm, d(B)/h ≥0.38, β-angle ≥19° and ST-ascent ≥1mm. The addition of the degree of ST-ascent to a model with these 4 parameters presented an increase in C-statistics from 0.77 (95% CI: 0.68–0.86) to 0.83 (95% CI: 0.75–0.91) for the diagnosis of non-T1BrP by an expert in Sudden Arrhythmic Death and Channelopathies. Conclusion A rSr'-pattern in precordial leads V1-V2 is a frequent finding and the detection of non-T1BrP by using the aforementioned 5 measurements is reproducible and accurate. In this study, we describe new cut-off values that may help untrained clinicians to identify young individuals who should be referred for provocative drug testing for Brugada Syndrome. Accuracy of non-T1 BrP criteria Funding Acknowledgement Type of funding source: None

Electrocardiogram interpretation in college athletes: Local institution versus sports cardiology center interpretation

BackgroundElectrocardiogram (ECG) screening in athletes enhances the detection of conditions associated with sudden cardiac death (SCD), but concerns remain for false positive results when conducted outside of specialized centers. This study compared ECG interpretation in college athletes between local physicians and a sports cardiology center (SCC). MethodsScreening ECGs in athletes from eight Pacific-12 Conference institutions performed between 2010 and 2016 were included. Local interpretation was compared to SCC interpretation using both the Seattle Criteria (SCC-SC) and the International Criteria (SCC-IC). ResultsA total of 2445 athlete ECGs (mean age 18.5 years; 57.1% male; 63.2% Caucasian and 15.3% African American) were reviewed. The proportion of ECGs classified as abnormal was similar between local and SCC-SC interpretation (3.5% vs. 3.4%, respectively; p = .94), but was lower by SCC-IC interpretation (1.5%, p < .001). ECG abnormalities interpreted as normal by local physicians but as abnormal by SCC-SC (n = 33) and SCC-IC (n = 16) standards included: pathological Q waves (n = 15 SCC-SC; n = 3 SCC-IC), T-wave inversions (n = 8 both), and ST-depressions (n = 3 both). There was a 97.5% ECG interpretation agreement and substantial interobserver reliability (k = 0.611, p < .001) between local and SCC-SC interpretation in athletes screened starting one year after publication of the Seattle Criteria (n = 1388). Both local and SCC physicians correctly identified six abnormal ECGs associated with conditions at risk of SCD. ConclusionsECG interpretation by local physicians at college universities had similar accuracy compared to a specialized SCC with a low overall abnormal rate, similar sensitivity, and substantial interobserver reliability. Uniform application of current ECG interpretation standards is recommended to further improve accuracy.

Cardiac screening of athletes: consensus needed for clinicians on indications for follow-up echocardiography testing

Many sporting teams, leagues and federations now mandate cardiac screening of athletes. The most common screening protocol in Australian sports involves a personal/family history and physical examination, together with a...