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Introduction: The heart rate variability (HRV) continually evolves throughout life, reflecting modifications in the architecture of the sinoatrial node (SAN) and in the regulation of heart rate by the autonomic nervous system (ANS). Both can be considerably affected by Chagas disease, causing important changes in the complex nature of HRV. We aim to evaluate the ability of an index based on the false nearest neighbors method (FN10) to reflect these changes during disease progression. Methods: We perform a retrospective, descriptive, and cross-sectional study analyzing HRV time series of participants with Chagas disease. We determine the dependence of FN10 on age and sex in a healthy population, and then evaluate FN10 in individuals with Chagas disease. Results and discussion: In the healthy population, FN10 has a scaling behavior with age, which is independent of sex. In Chagas disease, some individuals show FN10 values significantly above those seen in the healthy population. We relate the findings to the pathophysiological mechanisms that determine the progression of the disease. The results indicate that FN10 may be a candidate prognostic biomarker for heart disease.
RESUMO
In this work we study the characteristics of heart rate variability (HRV) as a function of age and gender. Our analysis covers a wider age range than that studied so far. It includes results previously reported in the literature and reveals behaviours not reported before. We can establish basic scale relationships in different HRV measurements. The mean value of the RR intervals shows a power-law behaviour independent of gender. Magnitudes such as the standard deviation or pNN50 show abrupt changes at around the age of 12 years, and above that age they show gender dependence, which mainly affects short-time (or high frequency) scales. We present a unified analysis for the calculation of the non-linear α and ß parameters. Both parameters depend on age; they increase in the extremes of life and reach a minimum at around one year of age. These gender-independent changes occur at low frequencies and in scale ranges that depend on age. The results obtained in this work are discussed in terms of the effects of basal metabolic rate, hormonal regulation, and neuronal activity on heart rate variability. This work finally discusses how these findings influence the interpretation of HRV measurements from records of different lengths.
Assuntos
Fatores Etários , Eletrocardiografia Ambulatorial/métodos , Frequência Cardíaca/fisiologia , Coração/fisiologia , Fatores Sexuais , Adolescente , Adulto , Distribuição por Idade , Idoso , Idoso de 80 Anos ou mais , Sistema Nervoso Autônomo/fisiologia , Metabolismo Basal/fisiologia , Análise Química do Sangue , Criança , Pré-Escolar , Estudos Transversais , Feminino , Voluntários Saudáveis , Humanos , Lactente , Masculino , Pessoa de Meia-Idade , Distribuição por Sexo , Adulto JovemRESUMO
Theoretical studies have thus far been unable to model pattern formation during the reaction in this system on physically feasible length and time scales. In this paper, we derive a computational reaction-diffusion model for this system in which most of the input parameters have been determined experimentally. We model the surface on a mesoscopic scale intermediate between the microscopic size of CO islands and the macroscopic length scale of pattern formation. In agreement with experimental investigations [M. Eiswirth et al., Z. Phys. Chem., Neue Folge 144, 59 (1985)], the results from our model divide the CO and O(2) partial pressure parameter space into three regions defined by the level of CO coverage or the presence of sustained oscillations. We see CO fronts moving into oxygen-covered regions, with the 1 x 1 to hex phase change occurring at the leading edge. There are also traveling waves consisting of successive oxygen and CO fronts that move into areas of relatively high CO coverage, and in this case, the phase change is more gradual and of lower amplitude. The propagation speed of these reaction waves is similar to those observed experimentally for CO and oxygen fronts [H. H. Rotermund et al., J. Chem. Phys. 91, 4942 (1989); H. H. Rotermund et al., Nature (London) 343, 355 (1990); J. Lauterbach and H. H. Rotermund, Surf. Sci. 311, 231 (1994)]. In the two-dimensional version of our model, the traveling waves take the form of target patterns emitted from surface inhomogeneities.
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La variabilidad de la frecuencia cardíaca (VFC) presenta características complejas que se manifiestan mediante diagramas de disperción los cuales exhiben patrones relacionados con diversas cardiopatías. Sosnowski et al. desarrollaron un índice para cuantificar la densidad de puntos en ellos. En este trabajo analizamos su utilidad en el diagnóstico precoz de la disautonomía chagásica. Objetivos: 1) Detectar la presencia de alteraciones de la fracción de la variabilidad de la frecuencia cardíaca (FVFC) y el r-SDNN en pacientes portadores de enfermedad de Chagas tanto en periodo indeterminado como crónico versus pacientes sanos. 2) Asociación de estas alteraciones con el estadio de la enfermedad de Chagas. El estudio se llevó a cabo sobre dos grupos poblacionales: uno control de 59 individuos sanos y otro de 24 portadores de enfermedad de Chagas. Se recolectaron y analizaron registros Holter de 24 hs. y se construyeron series temporales de intervalos RR. Sobre cada serie se calculó el promedio, el desvio estándar, el r-SDNN, el pNN50 y el FVFC. Se analiza la capacidad discriminante de los índices. Los valores medios de los diversos índices de VFC en el grupo control se corresponden con los reportados previamente en la literatura. El índice FVFC no discrimina entre los distintos grupos. El r-SDNN es el índice que mejor discrimina entre individuos sanos y portadores de enfermedad de Chagas (indeterminados y con cardiopatia tipo A). El índice FVFC no contempla la dispersión de los puntos en torno a la diagonal principal de los diagramas de dispersión.