Long-Range Correlations in Rectal Temperature Fluctuations of Healthy Infants during Maturation

Abstract

BackgroundControl of breathing, heart rate, and body temperature are interdependent in infants, where instabilities in thermoregulation can contribute to apneas or even life-threatening events. Identifying abnormalities in thermoregulation is particularly important in the first 6 months of life, where autonomic regulation undergoes critical development. Fluctuations in body temperature have been shown to be sensitive to maturational stage as well as system failure in critically ill patients. We thus aimed to investigate the existence of fractal-like long-range correlations, indicative of temperature control, in night time rectal temperature (Trec) patterns in maturing infants.Methodology/Principal FindingsWe measured Trec fluctuations in infants every 4 weeks from 4 to 20 weeks of age and before and after immunization. Long-range correlations in the temperature series were quantified by the correlation exponent, α using detrended fluctuation analysis. The effects of maturation, room temperature, and immunization on the strength of correlation were investigated. We found that Trec fluctuations exhibit fractal long-range correlations with a mean (SD) α of 1.51 (0.11), indicating that Trec is regulated in a highly correlated and hence deterministic manner. A significant increase in α with age from 1.42 (0.07) at 4 weeks to 1.58 (0.04) at 20 weeks reflects a change in long-range correlation behavior with maturation towards a smoother and more deterministic temperature regulation, potentially due to the decrease in surface area to body weight ratio in the maturing infant. α was not associated with mean room temperature or influenced by immunizationConclusionsThis study shows that the quantification of long-range correlations using α derived from detrended fluctuation analysis is an observer-independent tool which can distinguish developmental stages of night time Trec pattern in young infants, reflective of maturation of the autonomic system. Detrended fluctuation analysis may prove useful for characterizing thermoregulation in premature and other infants at risk for life-threatening events.

Dynamics and complexity of body temperature in preterm infants nursed in incubators

“…To our best knowledge, this is the first study to assess fractal long-range correlations of body temperature in preterm infants. Stern et al previously showed that mean (SD) T alpha obtained from monthly temperature measurements in healthy term infants increased from 1.42 (0.07) at 4 weeks to 1.58 (0.04) at 20 weeks of age [ 16 ]. They interpreted this to be due to a maturational effect towards a more deterministic system with increasing age post term.…”

“…These methods are established mathematical tools to quantify statistical long-range correlations in time series and have been successfully used for monitoring of disease severity and risk prediction [ 10 – 15 ]. DFA has been successfully used to quantify long-range correlations of body temperature in healthy term infants beyond the neonatal age [ 16 ]. In these infants, DFA indicates an association between statistical long-range correlations of body temperature and postnatal age.…”

Scale invariance as a symmetry in physical and biological systems: listening to photons, bubbles and heartbeats

“…in blood pressure dynamics, electroencephalographic potentials, stride intervals, center-of-pressure displacements, body temperature, respiration and human cognition [15,28,29,30,31]. Since the heart dynamics is the simplest physiological observable, it is also the best studied time series.…”

Surface electromyography for analysis of heart rate variability in preterm infants

“…In order to evaluate whether the amount of data fragmentation introduced by the signal cleaning process influences outcomes of DFA and SampEn, IBIs calculated using all technically acceptable segments of the sEMG measurement were compared to those calculated from the single longest technically acceptable consecutive series of data points using the four step quality control algorithm. The minimal number of consecutive IBI data points considered to be acceptable for time series analysis by DFA was set to 360 as recommended previously (Stern et al 2009).…”