Lerma C, Reyna MA, Carvajal R

Idioma: Ingles.
Referencias bibliográficas: 37
Paginas: 55-64
Archivo PDF: 381.21 Kb.

RESUMEN

Objetivo: Comparar la dimensión de correlación (DC) de la variabilidad de la frecuencia cardiaca (VFC) entre adultos con electrocardiograma (ECG) normal y anormal.
Métodos: Se registró un Holter de 24 horas y un electrocardiograma (ECG) estándar de 100 trabajadores universitarios. Después de la exclusión de 10 registros con más de 5% de intervalos RR falsos, se incluyeron en el estudio a 90 sujetos (edad 46.2±8.7 años, 45 mujeres). Dos cardiólogos clasificaron 29 ECG estándar como anormales. La DC se calculó en series de tiempo de VFC de 10,000 latidos en la mañana (desde las 11:00), tarde (desde las 17:00) y noche (desde las 2:00). Las características demográficas fueron comparadas mediante análisis de varianza (considerando diagnóstico de ECG y sexo como factores independientes) o con prueba exacta de Fisher. Los valores promedio de DC fueron comparados con análisis de varianza considerando como factores independientes el diagnóstico de ECG, sexo y hora del día.
Resultados: Las características demográficas fueron similares excepto por mayor proporción de hombres con ECG anormal (69%) que normal (41%). La DC no fue diferente con respecto a la hora del día, pero fue mayor en sujetos con ECG normal (10.86 ± 2.41) que con ECG anormal (10.20 ± 2.48), y también fue mayor en mujeres que en hombres: 11.04 ± 2.14 vs 10.63 ± 2.71 (grupo de ECG normal), 10.84 ± 2.41 vs 9.92 ± 2.44 (grupo de ECG anormal).
Conclusión: El hallazgo de ECG anormal en adultos está asociado con menor complejidad de la VFC. Palabras clave: humanos adultos, circadiano, dimensión de correlación, diferencias de género, a

REFERENCIAS (EN ESTE ARTÍCULO)

1. S. Akselrod, D. Gordon, F.A. Ubel, D.C. Shannon, A.C. Berger, R.J. Cohen, “Power spectrum analysis of heart rate fluctuation: a quantitative probe of beat-to-beat cardiovascular control,” Science, vol. 213, pp. 220-222, 1981.

2. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology, “Heart rate variability: standards of measurement, physiological interpretation and clinical use,” Circulation, 93, pp. 1043-1065, 1996.

3. F.L. Abel, E.P. McCutcheon, Neural Control. In: Abel FL, McCutcheon EP, eds. London: Little Brown and Company, 1979.

4. P.B. Persson, “Modulation of cardiovascular control mechanisms and their interaction,” Physiol Rev., vol. 76, pp. 193-244, 1996.

5. D.L. Eckberg, “Sympathovagal balance: a critical appraisal,” Circulation, vol. 96, pp. 3224-3232, 1997.

6. R.E. Kleiger, J.P. Miller, J.T. Bigger, A.J. Moss, “Decreased heart rate variability and its association with increased mortality after acute myocardial infarction,” Am J Cardiol., vol. 59, pp. 256-262, 1987.

7. M. Pagani, G. Malfatto, S. Pierini, et al., “Spectral analysis of heart rate variability in the assessment of autonomic diabetic neuropathy,” J Auton Nerv Syst., vol. 23, pp. 143-153, 1988.

8. S. Guzzetti, R. Magatelli, E. Borroni, S. Mezzetti, “Heart rate variability in chronic heart failure,” Auton Neurosci., vol. 90, pp. 102-105, 2001.

9. J. Pontet, P. Contreras, A. Curbelo, et al., “Heart rate variability as early marker of multiple organ dysfunction syndrome in septic patients,” J Crit Care, vol. 18, pp.156-163, 2003.

10. V.K. Yeragani, E. Sobolewski, J. Kay, V.C. Jampala, G. Igel, “Effect of age on long-term heart rate variability,” Cardiovasc Res., vol. 35, pp. 35-42, 1997.

11. L. Glass, D. Kaplan, “Time series analysis of complex dynamics in physiology and medicine,” Med Prog Technol., vol. 19, pp. 115-28, 1993.

12. A. Voss, J. Kurths, H.J. Kleiner, A. Witt, N. Wessel, “Improved analysis of heart rate variability by methods of nonlinear dynamics,” J Electrocardiol., vol. 28, Suppl, pp. 81-88, 1995.

13. R.B. Northrop, Introduction to complexity and complex systems, CRC Press (Boca Raton, Florida), 2011.

14. A. Babloyantz, A. Destexhe, “Is the normal heart a periodic oscillator?” Biol Cybern, vol. 58, 203-211, 1988.

15. F. Beckers, B. Verheyden, A.E. Aubert, “Aging and nonlinear heart rate control in a healthy population,” Am J Physiol Heart Circ Physiol., vol. 290, H2560- H2570, 2006.

16. A.L. Goldberger, D.R. Rigney, B.J. West, “Chaos and fractals in human physiology,” Sci Am., vol. 262, pp. 42- 49, 1990.

17. L.A. Lipsitz, A.L. Goldberger, “Loss of ’complexity’ and aging. Potential applications of fractals and chaos theory to senescence,” JAMA, vol. 267, pp. 1806-1809, 1992.

18. H.V. Huikuri, J.S. Perkiomaki, R. Maestri, G.D. Pinna, “Clinical impact of evaluation of cardiovascular control by novel methods of heart rate dynamics,” Philos Transact A Math Phys Eng Sci., vol. 367, pp. 1223-1238, 2009.

19. J.E. Skinner, C.M. Pratt, T. Vybiral, “A reduction in the correlation dimension of heartbeat intervals precedes imminent ventricular fibrillation in human subjects,” Am Heart J., vol. 125, pp. 731-743, 1993.

20. M. Javorka, Z. Trunkvalterova, I. Tonhajzerova, J. Javorkova, K. Javorka, M. Baumert, “Short-term heart rate complexity is reduced in patients with type 1 diabetes mellitus,” Clin Neurophysiol., vol. 119, no. 5, pp. 1071-1081, 2008.

21. M. Ferrario, M.G. Signorini, G. Magenes, “Complexity analysis of the fetal heart rate variability: early identification of severe intrauterine growth-restricted fetuses,” Med Biol Eng Comput., vol. 47, no. 9, pp. 911- 919, 2009.

22. P. Melillo, M. Bracali, L. Pecchia, “Nonlinear Heart Rate Variability features for real-life stress detection. Case study: students under stress due to university examination,” Biomed Eng Online, vol. 10, pp. 1-13, 2011.

23. C.D. Wagner, B. Nafz, P.B. Persson, “Chaos in blood pressure control,” Cardiovasc Res., vol. 31, pp. 380-387, 1996.

24. R. Carvajal, J.J. Zebrowski, M. Vallverdu, et al., “Dimensional analysis of HRV in hypertrophic cardiomyopathy patients,” IEEE Eng Med Biol Mag, vol. 21, pp. 71-78, 2002.

25. R. Carvajal, M. Vallverdu, R. Baranowski, J.J. Orlowska-Baranowska, J.J. Zebrowski, P. Caminal, “Dynamic nonlinear analysis of heart rate variability in patients with aortic stenosis,” Comput Cardiol., vol. 29, pp. 449-452, 2002.

26. R. Carvajal, N. Wessel, M. Vallverdú, P. Caminal, A. Voss, “Correlation dimension analysis of heart rate variability in patients with dilated cardiomyopathy,” Comput Methods Programs Biomed., vol. 78, pp. 133- 140, 2005.

27. N. Wessel, A. Voss, H. Malberg, et al., “Nonlinear analysis of complex phenomena in cardiological data,” Herzschr Elektrophys, vol. 11, pp. 159- 173, 2000.

28. P. Grassberger, I. Procaccia, “Measuring the strangeness of strange attractors,” Physica D, vol. 9, pp. 189- 208, 1983.

29. J.J. Zebrowski, W. Poplawska, R. Baranowski, “Entropy, pattern entropy, and related methods for the analysis of data on the time intervals between heartbeats from 24- h electrocardiograms,” Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics, vol. 50, pp. 4187-4205, 1994.

30. Y. Yamamoto, R.L. Hughson, J.R. Sutton, et al., “Operation Everest II: an indication of deterministic chaos in human heart rate variability at simulated extreme altitude,” Biol Cybern, vol. 69, pp. 205-212, 1993.

31. X. Bornas, J. Llabrés, A. Morillas- Romero, B. Aguayo-Siquier, M. Balle, M. Tortella-Feliu, “Complexity of everyday life heart rate dynamics and attentional control in healthy students,” Nonlinear Dynamics Psychol Life Sci., vol. 17, pp. 345-60, 2013.

32. D. Almoznino-Sarafian, G. Sarafian, I. Zyssman, et al. “Application of HRVCD for estimation of life expectancy in various clinical disorders,” Eur J Intern Med., vol. 20, pp. 779-783, 2009.

33. J.L. Chen, Y.J. Tseng, H.W. Chiu, T.C. Hsiao, W.C. Chu, “Nonlinear analysis of heart rate dynamics in hyperthyroidism,” Physiol Meas., vol. 28, 427-437, 2007.

34. A. Kikuchi, T. Shimizu, A. Hayashi, et al., “Nonlinear analyses of heart rate variability in normal and growthrestricted fetuses,” Early Hum Dev., vol. 82, pp. 217-226, 2006.

35. H.V. Huikuri, T. Seppanen, M.J. Koistinen, et al., “Abnormalities in beat-to-beat dynamics of heart rate before the spontaneous onset of lifethreatening ventricular tachyarrhythmias in patients with prior myocardial infarction,” Circulation, vol. 93, pp. 1836-1844, 1996.

36. A. Voss, K. Hnatkova, N. Wessel, et al., “Multiparametric analysis of heart rate variability used for risk stratification among survivors of acute myocardial infarction,” Pacing Clin Electrophysiol., vol. 21, pp. 186-192, 1998.

37. M.A. Woo, W.G. Stevenson, D.K. Moser, H.R: Middlekauff, “Complex heart rate variability and serum norepinephrine levels in patients with advanced heart failure,” J Am Coll Cardiol., vol. 23, pp. 565-569, 1994.