Skip to main navigation menu Skip to main content Skip to site footer

Diagnostic methodology of neonatal cardiac dynamics by spatial occupation of the chaotic attractor

Metodología diagnóstica de la dinámica cardíaca neonatal mediante la ocupación espacial del atractor caótico





Section
Research Articles

How to Cite
Rodríguez Velásquez, J. O., Prieto Bohórquez, S. E., Correa Herrera, C., López, R., Flórez, M., Soracipa Muñoz, M. Y., Velasco Rueda, A., Hoyos, N., & Valero Morales, L. P. (2015). Diagnostic methodology of neonatal cardiac dynamics by spatial occupation of the chaotic attractor. Archivos De Medicina (Manizales), 15(2), 305-319. https://doi.org/10.30554/archmed.15.2.806.2015
Download Citation

Dimensions
PlumX

How to Cite

Rodríguez Velásquez, J. O., Prieto Bohórquez, S. E., Correa Herrera, C., López, R., Flórez, M., Soracipa Muñoz, M. Y., Velasco Rueda, A., Hoyos, N., & Valero Morales, L. P. (2015). Diagnostic methodology of neonatal cardiac dynamics by spatial occupation of the chaotic attractor. Archivos De Medicina (Manizales), 15(2), 305-319. https://doi.org/10.30554/archmed.15.2.806.2015

Download Citation

Javier Oswado Rodríguez Velásquez
Signed Esperanza Prieto Bohórquez
Catalina Correa Herrera
Ruth López
Milena Flórez
María Yolanda Soracipa Muñoz
Alejandro Velasco Rueda
Natalia Hoyos
Laura Paola Valero Morales

Most read articles by the same author(s)

Objective: To develop a diagnostic methodology of neonatal cardiac dynamics from fractal geometry, the theory of dynamical systems and spatial occupation of heart attractor in the Box-Counting fractal space. Methodology: initially a mathematical induction was performed with two Holter evaluated clinically as normal and three with acute disease from the Intensive Care Unit (ICU). The sequence of values of heart rate (HR) was generated, taking the maximum and minimum values of the HR/hour and total beats/hour for 21 hours. Heart attractors were constructed and its fractal dimension
and their respective spaces of occupation of two grids in fractal space of Box-Counting, were calculated, differentiating between normal and disease. The results of induction were applied to 20 dynamic, five normal and 25 pathological, to confirm the results
by a blind study. Results: induction allowed establishing mathematical characteristics that differences between normality and disease by spatial occupation of chaotic attractors,
presenting values equal to or greater than 98 in the kg grid for normality, and less than 98 for acute illness; values which were later confirmed in other cases, achieving sensitivity and specificity of 100% and a kappa coefficient of 1. Conclusions: A
new physical and mathematical diagnostic with clinical application was developed to evaluate the neonatal cardiac dynamics, which allows early detection of abnormalities with potential gravity and quantitatively indicate the level of intensification of specific
alterations, useful for clinical decision making in the ICU.

Article visits | PDF visits


Downloads

Download data is not yet available.
  1. World Health Organization. Neonatal and Perinatal Mortality. Country, Regional and Global Estimate. Geneva: WHO press, 2006.
  2. Fairchild KD, O'Shea TM. Heart Rate Characteristics: Physiomarkers for Detection of Late-Onset Neonatal Sepsis. Clin Perinatol. 2010; 37(3): 581–598.
  3. Longin E, Gerstner T, Schaible T, Lenz T, König S. Maturation of the autonomic nervous system: differences in heart rate variability in premature vs. term infants. J Perinat Med. 2006;34(4):303-8.
  4. Eiselt M, Curzi-Dascalova L, Clairambault J, Kauffmann F, Médigue C, Peirano P. Heart-rate variability in low-risk prematurely born infants reaching normal term: a comparison with full-term newborns. Early Hum Dev. 1993;32(2-3):183-95.
  5. Griffin MP, Lake DE, Moorman JR. Heart Rate Characteristics and Laboratory Tests in Neonatal Sepsis. Pedíatrics 2005;115:937–941.
  6. Devaney R. A first course in chaotic dynamical systems theory and experiments. Reading Mass.: Addison-Wesley. 1992.
  7. Mandelbrot B. The Fractal Geometry of Nature. Barcelona. Freeman, Tusquets Eds S.A., 1972, p. 3-17.
  8. Peitgen H, Jurgens H, Saupe D. Strange attractors, the locus of chaos. En: Chaos and Fractals: New Frontiers of Science. New York: Springer-Verlag; 1992. pp. 655-768.
  9. Goldberger A, Amaral L, Hausdorff JM, Ivanov P, Peng Ch, Stanley HE. Fractal dynamics in physiology: alterations with disease and aging. PNAS 2002; 99: 2466 - 2472.
  10. Huikuri HV, Mäkikallio T, Peng CK, Goldberger AL, Hintze U, Møller M, et al. Fractal correlation properties of R – R interval dynamics and mortality in patients with depressed left ventricular function after and acute myocardial infarction. Circulation. 2000; 101: 47-53.
  11. Rodríguez J, Correa C Ortiz L, Prieto S, Bernal P, Ayala J. Evaluación matemática de la dinámica cardíaca con la teoría de la probabilidad. Rev Mex Cardiol 2009; 20 (4):183 - 189.
  12. Rodríguez J. Mathematical law of chaotic cardíac dynamic: Predictions of clinic application. J. Med. Med. Sci. 2011; 2(8):1050-1059.
  13. Rodríguez J. Entropía proporcional de los sistemas dinámicos cardíacos. Predicciones físicas y matemáticas de la dinámica cardíaca de aplicación clínica. Rev Col Cardiol. 2010; 17(3):115-129.
  14. Rodríguez J, Correa C, Melo M, Domínguez D, Prieto S, Cardona DM, et al. Chaotic cardíac law. Developing predictions of clinical application. J. Med. Med. Sci. 2013;4(2): 79-84.
  15. Rodriguez Javier. Proportional Entropy applied to the Clinic Prediction of Cardíac Dynamics. Innovations in Cardiovascular Interventions. ICI meeting, Tel Aviv-Israel. 2012.
  16. Rodríguez J, Prieto S, Domínguez D, Melo M, Mendoza F, Correa C, et al. Mathematical-physical prediction of cardíac dynamics using the proportional entropy of dynamic systems. J. Med. Med. Sci. 2013; 4(8): 370-381.
  17. Rodríguez J, Prieto S, Correa C, Soracipa Y, Aguirre G, Méndez L. Proportional entropy applied to the clinical díagnostic of cardíac dynamic: blind study with 600 holter. The 61st Annual Conference of the Israel Heart Society in association with The Israel Society of Cardiothoracic Surgery. 2014.
  18. Rodriguez Javier. Proportional Entropy of the cardíac dynamics in CCU patients. 7th International Meeting of Acute Cardíac Care, Tel Aviv-Israel. 2011.
  19. Rodríguez J, Prieto S, Bernal P, Izasa D, Salazar G, Correa C, et al. Entropía proporcional aplicada a la evolución de la dinámica cardíaca. Predicciones de aplicación clínica. En La emergencia de los enfoques de la complejidad en América Latina. Compilado por: Comunidad de Pensamiento Complejo (CPC). Argentina. (En prensa)
  20. Rodríguez J, Prieto S, Ortiz L, Bautista A, Bernal P, Avilán N. Diagnóstico Matemático de la monitoria fetal aplicando la ley de Zipf-Mandelbrot. Rev Fac Med Univ Nac Colomb. 2006; 54(2):96-107.
  21. Rodríguez J. Dynamical systems theory and ZIPF – Mandelbrot Law applied to the development of a fetal monitoring díagnostic methodology. XVIII FIGO World Congress of Gynecology and Obstetrics. Kuala Lumpur, MALAYSIA. November 2006.
  22. Rodríguez J. Nuevo Diagnóstico físico y matemático de la monitoria fetal: predicción de aplicación clínica. Momento Revista de Física. 2012; 44: 49-65.
  23. Rodríguez J, Prieto S, Avilán N, Correa C, Bernal P, Ortiz L, et al. Nueva metodología física y matemática de evaluación del Holter. Rev Colomb Cardiol 2008; 15: 50-54.
  24. Rodríguez J, Prieto S, Bernal P, Soracipa Y, Salazar G, Isaza D, et al. Nueva metodología de ayuda diagnóstica de la dinámica geométrica cardíaca dinámica cardíaca caótica del holter. Rev Acad Colomb Cienc 2011; 35 (134):5-12.
  25. Rodríguez J, Prieto S, Flórez M, Alarcón M, López R, Aguirre G, et al. Sistemas dinámicos cardiacos en neonatos normales: Ley caótica cardiaca neonatal. Salud Uninorte, Barranquilla (Col.) 2014, 30(3):359-368
  26. Rodríguez J, Prieto S, Flórez M, Alarcón C, López R, Aguirre G, et al. Physical-mathematical díagnosis of cardíac dynamic on neonatal sepsis: predictions of clinical application. J. Med. Med. Sci. 2014; 5(5): 102-108.
  27. República de Colombia. Ministerio de salud. Resolución número 8430. Por la cual se establecen las normas científicas, técnicas y administrativas para la investigación en salud. Bogotá D.C. 1993.
  28. Heart rate variability: standards of measurement, physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Circulation. 1996;93(5):1043–65.
  29. Bauer A, Kantelhardt JW, Barthel P, Schneider R, Mäkikallio T, Ulm K, et al. Deceleration capacity of heart rate as a predictor of mortality after myocardíal infarction: cohort study. Lancet. 2006;367(9523):1674–81.
  30. Schmidt G, Malik M, Barthel P, Schneider R, Ulm K, Rolnitzky L, et al. Heart-rate turbulence after ventricular premature beats as a predictor of mortality after acute myocardíal infarction. Lancet. 1999;353(9162):1390–6.
  31. Voss A, Schroeder R, Vallverdu M, Cygankiewicz I, Vazquez R, Bayes de Luna A, et al. Linear and nonlinear heart rate variability risk stratification in heart failure patients. Comput Cardiol. 2008;2008:557–60.
  32. Maestri R, Pinna GD, Accardo A, Allegrini P, Balocchi R, D’Addio G, et al. Nonlinear indices of heart rate variability in chronic heart failure patients: redundancy and comparative clinical value. J Cardiovasc Electrophysiol. 2007;18(4):425–33.
  33. Ahmad S, Tejuja A, Newman K, Zarychanski R, Seely A. Clinical review: a review and analysis of heart rate variability and the díagnosis and prognosis of infection. Crit Care. 2009;13(6):232.
  34. Chen WL, Kuo CD. Characteristics of heart rate variability can predict impending septic shock in emergency department patients with sepsis. Acad Emerg Med. 2007;14(5):392–7.
  35. Papaioannou VE, Dragoumanis C, Theodorou V, Gargaretas C, Pneumatikos I. Relation of heart rate variability to serum levels of C-reactive protein, interleukin 6, and 10 in patients with sepsis and septic shock. J Crit Care. 2009;24(4):625.e1–7.
  36. Ahmad S, Ramsay T, Huebsch L, Flanagan S, McDíarmid S, Batkin I, et al. Continuous multi-parameter heart rate variability analysis heralds onset of sepsis in adults. PLoS One. 2009;4(8): e6642.33.
  37. Buchan C, Bravi A, Seely A. Variability Analysis and the Díagnosis, Management, and Treatment of Sepsis. Curr Infect Dis Rep. 2012; 14:512–521.
  38. Gonçalves H1, Pinto P, Silva M, Ayres-de-Campos D, Bernardes J. Toward the improvement in fetal monitoring during labor with the inclusion of maternal heart rate analysis. Med Biol Eng Comput. 2015; [Epub ahead of print]
  39. Prieto S, Rodríguez J, Correa C, Soracipa Y. Díagnosis of cervical cells based on fractal and Euclidían geometrical measurements: Intrinsic Geometric Cellular Organization. BMC Medical Physics. 2014, 14(2):1-9.
  40. Velásquez J, Prieto S, Correa C, Dominguez D, Cardona DM, Melo M. Geometrical nuclear díagnosis and total paths of cervix cell evolution from normality to cancer. J Can Res Ther. 2015; 11(1): 98-104.
  41. Correa C, Rodríguez J, Prieto S, Álvarez L, Ospino B, Munévar A, et al. Geometric díagnosis of erythrocyte morphophysiology. J. Med. Med. Sci. 2012; 3(11): 715-720.
  42. Rodríguez J, Prieto S, Correa C, Bernal P, Puerta G, Vitery S, et al. Theoretical generalization of normal and sick coronary arteries with fractal dimensions and the arterial intrinsic mathematical harmony. BMC Med Phys. 2010;10:1-6.
  43. Rodríguez J. Teoría de unión al HLA clase II teorías de Probabilidad Combinatoria y Entropía aplicadas a secuencias peptídicas. Inmunología. 2008; 27(4):151-166.
  44. Rodríguez J, Bernal P, Prieto S, Correa C. Teoría de péptidos de alta unión de malaria al glóbulo rojo. Predicciones teóricas de nuevos péptidos de unión y mutaciones teóricas predictivas de aminoácidos críticos. Inmunología. 2010; 29(1):7-19.
  45. Rodríguez J. Método para la predicción de la dinámica temporal de la malaria en los municipios de Colombia. Rev Panam Salud Pública. 2010; 27(3):211-218.
  46. Rodríguez J, Prieto S, Correa C, Pérez C, Mora J, Bravo J, et al. Predictions of CD4 lymphocytes’ count in HIV patients from complete blood count. BMC Medical Physics. 2013; 13:3.