Heart rate dynamics in low risk human fetuses

• Published in: Pediatric research Vol. 44; no. 1; pp. 111 - 118
• Main Authors: MOONEY, D. M, GROOME, L. J, HOLLAND, S. B, SMITH, Y. D
• Format: Journal Article
• Language: English
• Published: Hagerstown, MD Lippincott Williams & Wilkins 01.07.1998
• Subjects: Apgar Score; Biological and medical sciences; Electrocardiography - methods; Female; Fetus; Gestational Age; Gynecology. Andrology. Obstetrics; Heart Rate, Fetal - physiology; Humans; Infant, Newborn; Management. Prenatal diagnosis; Medical sciences; Normal Distribution; Pregnancy; Pregnancy. Fetus. Placenta; Reference Values; Human; Heart rate; Intraindividual comparison; Variability; Fetus; Time; Normal
• ISSN: 0031-3998; 1530-0447
• DOI: 10.1203/00006450-199807000-00018

Evaluation of nonlinear heart rate (HR) dynamics has received considerable attention in the pediatric literature because such analyses not only provide insight into underlying control mechanisms, but may also help to differentiate between normal and abnormal infants. The purpose of this study was to determine, in eight low risk human fetuses, if nonlinear HR dynamics could be identified by analyzing the dispersion of interbeat intervals at slow (Ds) and fast (Df) HRs. The fetal cardiac electrical signal was captured transabdominally at a resolution of +/- 1 ms. To test the null hypothesis, that the time series is the result of a linear stochastic process, Ds and Df for the original time series were compared with the values calculated for three linear models. The linear models were constructed to preserve the major statistical properties of the original time series, including the mean, SD, and the Fourier power spectrum. For each fetus, there was no evidence of nonlinear cardiac dynamics based on analyses of Ds and Df. In contrast, the distribution of adjacent R-R intervals and the pattern of change across three successive interbeat intervals both revealed significant nonlinearities in HR control in each fetus. If the difference between normal and abnormal infants is the result of aberrant control of nonlinear processes, then our findings indicate that parameters which describe the nonlinearity may be more useful then Ds and Df in assigning a risk status.