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Annals of Computer Science and Information Systems, Volume 15

Proceedings of the 2018 Federated Conference on Computer Science and Information Systems

ECG Signal Analysis for Troponin Level Assessment and Coronary Artery Disease Detection: the NEEDED Study 2014

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DOI: http://dx.doi.org/10.15439/2018F247

Citation: Proceedings of the 2018 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 15, pages 10651068 ()

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Abstract. Physical exercise is widely recognized as beneficial to the cardiovascular system. However, intense exercise may also carry fatal risk. Investigation of this phenomenon is one of the primary purposes of the North Sea Race Endurance Exercise Study (NEEDED). This paper describes analysis of electrocardiograms (ECG) and heart rate signals collected from amateur athletes, participants of the race, to facilitate noninvasive estimation of the level of cardiac troponin I (cardiovascular risk biomarker) and detection of coronary artery disease (CAD). It was demonstrated that the combination of ECG and heart rate parameters can predict CAD with high specificity (up to 98\%) and relatively good sensitivity. Moreover, while troponin level assessment is unlikely to be reliably performed using regression techniques, it might be possible using a new, probabilistic classification-based model. Further evaluation of the latter requires the use of additional data, which is one of possible directions for the future work.

References

  1. J. Sarko and C. V. Pollack, “Cardiac troponins,” Am J Emerg Med, vol. 23, no. 1, pp. 57–65, Jul. 2002.
  2. L. Babuin and A. S. Jaffe, “Troponin: the biomarker of choice for the detection of cardiac injury,” CMAJ, vol. 173, no. 10, pp. 1191–1202, Nov. 2005.
  3. T. Omland, M. A. Pfeffer, S. D. Solomon, J. A. de Lemos, H. Røsjø et al., “Prognostic Value of Cardiac Troponin I Measured With a Highly Sensitive Assay in Patients With Stable Coronary Artery Disease,” J Am Coll Cardiol, vol. 61, no. 12, pp. 1240–1249, Mar. 2013.
  4. P. Aagaard, A. Sahlén, L. Bergfeldt, and F. Braunschweig, “Heart Rate and Its Variability in Response to Running—Associations with Troponin,” Med Sci Sports Exerc, vol. 46, no. 8, p. 1624, Aug. 2014.
  5. R. Shave, A. Baggish, K. George, M. Wood, J. Scharhag et al., “Exercise-Induced Cardiac Troponin Elevation: Evidence, Mechanisms, and Implications,” J Am Coll Cardiol, vol. 56, no. 3, pp. 169–176, Jul. 2010.
  6. T. M. H. Eijsvogels, M. D. Hoogerwerf, M. F. H. Maessen, J. P. H. Seeger, K. P. George et al., “Predictors of cardiac troponin release after a marathon,” J Sci Med Sport, vol. 18, no. 1, pp. 88–92, Jan. 2015.
  7. A. Legaz-Arrese, K. George, L. E. Carranza-García, D. Munguía-Izquierdo, T. Moros-García et al., “The impact of exercise intensity on the release of cardiac biomarkers in marathon runners,” Eur J Appl Physiol, vol. 111, no. 12, pp. 2961–2967, Dec. 2011.
  8. S. Regwan, E. A. Hulten, S. Martinho, J. Slim, T. C. Villines et al., “Marathon Running as a Cause of Troponin Elevation: A Systematic Review and Meta-Analysis,” J Interv Cardiol, vol. 23, no. 5, pp. 443–450, Oct. 2010.
  9. E. Serrano-Ostáriz, A. Legaz-Arrese, J. L. Terreros-Blanco, M. López-Ramón, D. Cremades-Arroyos et al., “Cardiac Biomarkers and Exercise Duration and Intensity During a Cycle-touring Event,” Clin J Sport Med, vol. 19, no. 4, pp. 293–299, Jul. 2009.
  10. Ø. Skadberg, Ø. Kleiven, M. Bjørkavoll-Bergseth, T. Melberg, R. Bergseth et al., “Highly increased Troponin I levels following high-intensity endurance cycling may detect subclinical coronary artery disease in presumably healthy leisure sport cyclists,” Eur J Prev Cardiol, vol. 24, no. 8, pp. 885–894, May 2017.
  11. Ø. Kleiven, M. Bjoerkavoll-Bergseth, Ø. Skadberg, T. Melberg, B. Auestad et al., “P3242prolonged release of cardiac troponin I after endurance exercise could indicate silent coronary artery disease in recreational athletes,” Eur Heart J, vol. 38, no. suppl_1, Aug. 2017.
  12. K. Oskal, “Myocardial damage during mountain bike race - an analysis of data from Nordsjørittet 2014 (NEEDED study),” Master’s thesis, University of Stavanger, Jun. 2016.
  13. D. Długosz, T. Eftestøl, S. Ørn, T. Wiktorski, and A. Królak, “The North Sea Bicycle Race ECG Project: Time-Domain Analysis,” vol. 11. Prague: Annals of Computer Science and Information Systems, Sep. 2017, pp. 1353–1356.
  14. B. Vandenberk, E. Vandael, T. Robyns, J. Vandenberghe, C. Garweg et al., “Which QT Correction Formulae to Use for QT Monitoring?” Journal of the American Heart Association, vol. 5, no. 6, Jun. 2016.
  15. Thomas B. Garcia and Neil E. Holtz, EKG - sztuka interpretacji, 1st ed. Warszawa: MediPage, 2007.
  16. A. C. Guyton and J. E. Hall, Textbook of Medical Physiology, 11th ed. Pennsylvania: ELSEVIER SAUNDERS, 2006.
  17. E. Pietka and J. Kawa, Information Technologies in Biomedicine. Springer Science & Business Media, May 2010.
  18. M. L. Talbi and A. Charef, “PVC discrimination using the QRS power spectrum and self-organizing maps,” Comput Methods Programs Biomed, vol. 94, no. 3, pp. 223–231, Jun. 2009.
  19. H. Tanaka, K. D. Monahan, and D. R. Seals, “Age-predicted maximal heart rate revisited,” J Am Coll Cardiol, vol. 37, no. 1, pp. 153–156, Jan. 2001.
  20. R. Olson, R. Urbanowicz, P. Andrews, N. Lavender, L. Kidd et al., “Automating Biomedical Data Science Through Tree-Based Pipeline Optimization,” in Applications of Evolutionary Computation: 19th European Conference, EvoApplications 2016, Porto, Portugal, March 30 – April 1, 2016, Proceedings, Part I, ser. Lecture Notes in Computer Science. Springer, Cham, Mar. 2016, pp. 123–137.
  21. M. Bjorkavoll-Bergseth, O. Kleiven, T. Melberg, O. Skadberg, B. Uestad et al., “Increased heart rate does not explain the cardiac troponin increase following strenous exercise - the needed 2014 advanced heart rate monitor substudy,” Europrevent, p. 296, 2018.