Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

Advertisement

Springer Nature Link
Log in

A comprehensive electrocardiographic analysis for young athletes

  • Original Article
  • Published:
Medical & Biological Engineering & Computing Aims and scope Submit manuscript

Abstract

ECG-based differences between athletes and sedentary adolescents are a frequently investigated subject in sports medicine. Especially, training-induced ECG variations are common in adult athletes and sustained training often leads to anatomical changes in the heart that can yield abnormalities in ECG. Therefore, ECG screening in athletes is important in diagnosis of cardiac problems of young athletes. The present work investigated the ECG characteristics of young athletes in terms of both gender and sedentary healthy young control group differences. Besides comparison between groups, analysis parameters were also investigated within the groups using correlation analysis. ECG characteristics were extracted using wavelet transform–based adaptive algorithms. Results showed that ECGs of athletes demonstrate differences related to gender and compared to young sedentary. Athletes had significantly lower heart rate; higher QTc, P, and T amplitudes; ST segment; and ST, QT, and RR intervals compared to control group (p < 0.05). Proposed new parameter, namely “scalogram” of each wave, was lower in male athletes compared to other groups (p < 0.05). Negative correlation between T wave amplitude and RR interval could be an indicator of long QT syndrome for male athletes. Furthermore, prolongation of QRS interval in athletes could be the underlying reason of changes in T wave amplitude. Findings of this study can propose indicators for understanding the possible diseases as well as help evaluate the sudden changes in athlete’s heart.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  1. Blackburn H (1965) The electrocardiogram in cardiovascular epidemiology: problems in standardized application. Ann N Y Acad Sci 126(2):882–905. https://doi.org/10.1111/j.1749-6632.1965.tb14331.x

    Article  CAS  PubMed  Google Scholar 

  2. Maron BJ (1986) Structural features of the athlete heart as defined by echocardiography. J Am Coll Cardiol 7(1):190–203. https://doi.org/10.1016/S0735-1097(86)80282-0

    Article  CAS  PubMed  Google Scholar 

  3. Drezner JA, Ashley E, Baggish AL et al (2013) Abnormal electrocardiographic findings in athletes: recognising changes suggestive of cardiomyopathy. Br J Sports Med 47(3):137–152. https://doi.org/10.1136/bjsports-2012-092069

    Article  PubMed  Google Scholar 

  4. Brosnan M, La Gerche A, Kalman J et al (2014) The Seattle Criteria increase the specificity of preparticipation ECG screening among elite athletes. Br J Sports Med 48(15):1144–1150. https://doi.org/10.1136/bjsports-2013-092420

    Article  PubMed  Google Scholar 

  5. Drezner JA, Ackerman MJ, Anderson J et al (2013) Electrocardiographic interpretation in athletes: the ‘Seattle criteria.’ Br J Sports Med 47(3):122–124. https://doi.org/10.1136/bjsports-2012-092067

    Article  PubMed  Google Scholar 

  6. Yilmaz DC, Buyukakilli B, Gurgul S et al (2013) Adaptation of heart to training: a comparative study using echocardiography & impedance cardiography in male & female athletes. Indian J Med Res 137(6):1111

    PubMed  PubMed Central  Google Scholar 

  7. Waase MP, Mutharasan RK, Whang W et al (2018) Electrocardiographic findings in national basketball association athletes. JAMA cardiol 3(1):69–74. https://doi.org/10.1001/jamacardio.2017.4572

    Article  PubMed  Google Scholar 

  8. Van Ganse W, Versee L, Eylenbosch W et al (1970) The electrocardiogram of athletes comparison with untrained subjects. Heart 32(2):160–164. https://doi.org/10.1136/hrt.32.2.160

    Article  Google Scholar 

  9. Beckner GL, Winsor T (1954) Cardiovascular adaptations to prolonged physical effort. Circulation 9(6):835–846. https://doi.org/10.1161/01.CIR.9.6.835

    Article  CAS  PubMed  Google Scholar 

  10. Castro RRT, Magini M, Pedrosa S et al (2011) Principal components analysis to evaluate ventilatory variability: comparison of athletes and sedentary men. Med Biol Eng Comput 49(3):305–311. https://doi.org/10.1007/s11517-010-0693-z

    Article  CAS  PubMed  Google Scholar 

  11. Wong S, Kervio G, Altuve M, et al (2012) Comparing six QT correction methods in an athlete population, Chapter 39, In Computing in Cardiology, Krakow, Poland

  12. Kumar N, Saini D, Froelicher V (2013) A gender-based analysis of high school athletes using computerized electrocardiogram measurements. PloS one 8(1):e53365. https://doi.org/10.1371/journal.pone.0053365

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Bessem B, de Bruijn MC, Nieuwland W (2017) Gender differences in the electrocardiogram screening of athletes. J Sci Med Sport 20(2):213–217. https://doi.org/10.1016/j.jsams.2016.06.010

    Article  PubMed  Google Scholar 

  14. Corici OM, Mirea-Munteanu O, Donoiu I, et al (2018) Gender-related electrocardiographic changes in athletes. Curr Health Sci J 44(1): 29–33. https://doi.org/10.12865/CHSJ.44.01.05

  15. Yanık H, Değirmenci E, Büyükakıllı B et al (2020) Electrocardiography (ECG) analysis and a new feature extraction method using wavelet transform with scalogram analysis. Biomed Tech 65(5):543–556. https://doi.org/10.1515/bmt-2019-0147

    Article  Google Scholar 

  16. Vandenberk B, Vandael E, Robyns T et al (2016) Which QT correction formulae to use for QT monitoring? J Am Heart Assoc 5(6):e003264. https://doi.org/10.1161/JAHA.116.003264

    Article  PubMed  PubMed Central  Google Scholar 

  17. Dash A, Torado C, Paw N et al (2019) QT correction in atrial fibrillation – measurement revisited. J Electrocardiol 56:70–76. https://doi.org/10.1016/j.jelectrocard.2019.06.009

    Article  PubMed  Google Scholar 

  18. Benesty J, Chen J, Huang Y, Cohen I (2009) Pearson correlation coefficient. In: Noise reduction in speech processing. Springer Topics in Signal Processing, vol 2. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00296-0_5

  19. Akoglu H (2018) User’s guide to correlation coefficients. Turk J Emerg Med 18(3):91–93. https://doi.org/10.1016/j.tjem.2018.08.001

    Article  PubMed  PubMed Central  Google Scholar 

  20. Fagard R (2003) Athlete’s heart. Heart 89:1445–1461. https://doi.org/10.1136/heart.89.12.1455

    Article  Google Scholar 

  21. Stout M (2008) Athletes’ heart and echocardiography: athletes’ heart. Echocardiography 25(7):749–754. https://doi.org/10.1111/j.1540-8175.2008.00670.x

    Article  PubMed  Google Scholar 

  22. Johannesen L, Grove U, Sørensen J et al (2010) Analysis of T-wave amplitude adaptation to heart rate using RR-binning of long-term ECG recordings. Comput Cardiol 37:369–372

    CAS  Google Scholar 

  23. Couderc JP, Vaglio M, Xia X et al (2007) Impaired T-amplitude adaptation to heart rate characterizes IKr inhibition in the congenital and acquired forms of the long QT syndrome. J Cardiovasc Electrophysiol 18:1299–1305. https://doi.org/10.1111/j.1540-8167.2007.00960.x

    Article  PubMed  Google Scholar 

  24. Johnson JN, Ackerman MJ (2013) Return to play? Athletes with congenital long QT syndrome. Br J Sports Med 47:28–33. https://doi.org/10.1136/bjsports-2012-091751

    Article  PubMed  Google Scholar 

  25. Zdravkovic M, Milovanovic B, Hinic S, et al (2017) Correlation between ECG changes and early left ventricular remodeling in preadolescent footballers. Physiol Int 104:42–51. https://doi.org/10.1556/2060.104.2017.1.2

  26. Toufan M, Kazemi B, Akbarzadeh F et al (2012) Assessment of electrocardiography, echocardiography, and heart rate variability in dynamic and static type athletes. Int J Gen Med 5:655–660. https://doi.org/10.2147/IJGM.S33247

    Article  PubMed  PubMed Central  Google Scholar 

  27. La Gerche A, Macisaac AI, Prior DL (2011) Should pre-participation cardiovascular screening for competitive athletes be introduced in Australia? A timely debate in a sport-loving nation. Heart Lung Circ 20:629–633. https://doi.org/10.1016/j.hlc.2010.08.002

    Article  PubMed  Google Scholar 

  28. Hong L, Andersen LJ, Graff C et al (2015) T-wave morphology analysis of competitive athletes. J Electrocardiol 48(1):35–42. https://doi.org/10.1016/j.jelectrocard.2014.10.011

    Article  CAS  PubMed  Google Scholar 

  29. Parry-Williams G, Malhotra A, Dhutia H et al (2019) The short PR interval in young athletes. Heart 105(Suppl 6):A1–A193. https://doi.org/10.1136/heartjnl-2019-BCS.28

    Article  Google Scholar 

  30. Han Y, Huang L, Li Z. et al (20019) Relationship between left ventricular isovolumic relaxation flow patterns and mitral inflow patterns studied by using vector flow mapping. Sci Rep 9 16264. https://doi.org/10.1038/s41598-019-52680-x

  31. Field ME, Donateo P, Bottoni N, et al (2018) P-wave amplitude and PR changes in patients with inappropriate sinus tachycardia: findings supportive of a central mechanism. J Am Heart Assoc 7: pii: e008528. https://doi.org/10.1161/JAHA.118.008528

  32. Daniel MB (2020) Title of subordinate document: Lown-Ganong-Levine Syndrome. Available at: https://emedicine.medscape.com/article/160097-overview. Accessed 12 December 2020.

  33. Merghani A, Maestrini V, Rosmini S et al (2017) Prevalence of subclinical coronary artery disease in masters endurance athletes with a low atherosclerotic risk profile. Circulation 136:126–137. https://doi.org/10.1161/CIRCULATIONAHA.116.026964

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

The analyzes of this study were carried out using the method and toolbox that Hüseyin Yanık proposed in his Master’s Thesis. Evren Değirmenci is the supervisor of the Thesis and the principal author of this study. Belgin Büyükakıllı contributed to the article on some medical issues. The authors would like to thank the participants for their support to the study and efforts during the experiments, Dilek Çiçek Yılmaz for evaluating the health status of participants, and also Serkan Gürgül and the undergraduate students who assisted during the data collection.

Author information

Authors and Affiliations

  1. Faculty of Engineering, Department of Electrical and Electronics Engineering, Mersin University, 33110, Mersin, Turkey

    Hüseyin Yanık & Evren Değirmenci

  2. Faculty of Medicine, Department of Biophysics, Mersin University, 33110, Mersin, Turkey

    Belgin Büyükakıllı

Authors
  1. Hüseyin Yanık
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Evren Değirmenci
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Belgin Büyükakıllı
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Evren Değirmenci.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yanık, H., Değirmenci, E. & Büyükakıllı, B. A comprehensive electrocardiographic analysis for young athletes. Med Biol Eng Comput 59, 1865–1876 (2021). https://doi.org/10.1007/s11517-021-02401-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11517-021-02401-2

Keywords

Search

Navigation