Statistical Modeling of Heart Rate Variability to Unravel the Factors Affecting Autonomic Regulation in Preterm Infants

Pilot study shows skin-to-skin care with parents improves heart rate variability in preterm infants in the neonatal intensive care unit

Background

Skin-to-skin care in the newborn intensive care unit typically lasts for short periods of time and enhances breastfeeding, attachment, and parental self-esteem. Heart rate variability (HRV) increases with gestational age and is a measure of maturation of parasympathetic vs. sympathetic autonomic nervous system activity. HRV measurements may be useful in capturing changes in autonomic regulation in response to skin-to-skin care.

Objective

To analyze the effects of skin-to-skin care on HRV in preterm infants receiving respiratory support. We hypothesized that skin-to-skin care would result in a more mature pattern of parasympathetic activity.

Methods

In this prospective crossover study, infants <30 weeks' gestation and 1-6 weeks postnatal age had HRV recorded for 30 min before, during, and after skin-to-skin care sessions. HRV characteristics analyzed included the standard deviation of the normal-to-normal interval (SDNN), the root mean squared of successive differences of normal-to-normal intervals (RMSSD), and the standard deviation of decelerations (SDDec).

Results

10 infants between 25 5/7-29 6/7 weeks gestational age and 7-41 days postnatal age completed 22 sessions while receiving respiratory support (positive pressure ventilation or nasal cannula oxygen). Two measures of HRV (SDNN and RMSSD) were significantly decreased by the end of the skin-to-skin sessions, compared to pre-session values. SDNN decreased from a median of 10.44 ms before the session to 6.70 ms after being placed back in bed (p < 0.05), with RMSSD decreasing from a median of 6.80 ms before the session to 4.32 ms while being held at the end of 30 min (p < 0.05).

Discussion

Skin-to-skin care with a parent resulted in a more mature autonomic nervous system pattern in preterm infants receiving respiratory support, suggesting physiologic benefit for the infant. No adverse events were seen during any session.

Comparing Full and Pre-Term Neonates' Heart Rate Variability in Rest Condition and during Spontaneous Interactions with Their Parents at Home

BACKGROUND

Preterm neonates show decreased HRV compared to those at full-term. We compared HRV metrics between preterm and full-term neonates in transfer periods from neonate rest state to neonate-parent interaction, and vice versa.

METHODS

Short-term recordings of the HRV parameters (time and frequency-domain indices and non-linear measurements) of 28 premature healthy neonates were compared with the metrics of 18 full-term neonates. HRV recordings were performed at home at term-equivalent age and HRV metrics were compared between the following transfer periods: from first rest state of the neonate (TI1) to a period in which the neonate interacted with the first parent (TI2), from TI2 to a second neonate rest state (TI3), and from TI3 to a period of neonate interaction with the second parent (TI4).

RESULTS

For the whole HRV recording period, PNN50, NN50 and HF (%) was lower for preterm neonates compared to full-terms. These findings support the reduced parasympathetic activity of preterm compared to full-term neonates. The results of comparisons between transfer period simply a common coactivation of SNS and PNS systems for both full and pre-term neonates.

CONCLUSIONS

Spontaneous interaction with the parent may reinforce both full and pre-term neonates' ANS maturation.

The impact of a violent community on mental health and the benefits of a sport program for social development

The aim of the present study was to evaluate the impact of a violent environment on mental health and the impact of a sport for social development (SSD) program on quality of life, mental distress symptoms, and heart rate variability (HRV). HRV and psychometric data were measured from 20 men professional athletes assisted by the SSD and 20 men living in the same violent community. The comparison of groups revealed greater sympathetic parameters of HRV, positive affect, and quality of life in the SSD group. Multiple regression analysis showed that the quality of life in the SSD group was positively predicted by positive affect, while in the control group the quality of life was negatively predicted by their history of traumatic events. Both groups reported high levels of exposure to traumatic events and posttraumatic stress symptoms. However, this study demonstrates the benefits of SSD programs in mental health.

Characterizing the effect of demographics, cardiorespiratory factors, and inter-subject variation on maternal heart rate variability in pregnancy with statistical modeling: a retrospective observational analysis

Pregnancy complications are associated with insufficient adaptation of the maternal autonomic nervous system to the physiological demands of pregnancy. Consequently, assessing maternal heart rate variability (mHRV)-which reflects autonomic regulation-is a promising tool for detecting early deterioration in maternal health. However, before mHRV can be used to screen for complications, an understanding of the factors influencing mHRV during healthy pregnancy is needed. In this retrospective observational study, we develop regression models to unravel the effects of maternal demographics (age, body mass index (BMI), gestational age (GA), and parity), cardiorespiratory factors (heart rate and breathing rate), and inter-subject variation on mHRV. We develop these models using two datasets which are comprised of, respectively, single measurements in 290 healthy pregnant women and repeated measurements (median = 8) in 29 women with healthy pregnancies. Our most consequential finding is that between one-third and two-thirds of the variation in mHRV can be attributed to inter-subject variability. Additionally, median heart rate dominantly affects mHRV (p < 0.001), while BMI and parity have no effect. Moreover, we found that median breathing rate, age, and GA all impact mHRV (p < 0.05). These results suggest that personalized, long-term monitoring would be necessary for using mHRV for obstetric screening.

Correlation between diminished vagal tone and somatic dysfunction severity in very and extremely low birth weight preterm infants assessed with frequency spectrum heart rate variability and salivary cortisol

Osteopathic manipulative treatment (OMT) is evolving in the neonatal intensive care unit (NICU) setting. Studies showed its efficacy in length of stay and hospitalization costs reduction. Moreover, it was suggested that OMT has a modulatory effect on the preterm infants' autonomic nervous system (ANS), influencing saturation and heart rate. Even if OMT is based on the palpatory examination of the somatic dysfunctions (SD), there are controversies about its identification and clinical relevance. The objective of this study was to evaluate the inter-rater reliability, clinical characteristics, and functional correlation of the SD Grade score with the heart rate variability (HRV) and the salivary cortisol (sCor) using a multivariate linear model approach. To evaluate those features, we implemented an ad hoc SD examination for preterm infants that was performed by 2 trained osteopaths. It was based on the new variability model of SD that includes an SD Grade assessment procedure. The ANS features were assessed by frequency parameters of HRV studying high frequency (HF), low frequency (LF), and HF/LF, whereas sCor was tested with a radioimmunoassay. The ANS assessment was standardized and performed before SD testing. Sixty-nine premature infants were eligible. SD Grade showed excellent concordance between the blinded raters. Using SD Grade as a grouping variable, the infants presented differences in GA, Apgar, pathological findings, length of stay, and ventilatory assistance. In our multivariate model, HF, LF, and LF/HF resulted linearly correlated with SD Grade. Instead, sCor presented a linear correlation with 5' Apgar and respiratory distress syndrome but not with SD Grade. SD Grade was in line with the natural history of the underdevelopment due to prematurity. Our models indicate that the cardiac vagal tone is linearly related with SD Grade. This finding may improve the multidisciplinary decision making inside NICU and the management of modifiable factors, like SD, for cardiac vagal tone regulation.

High frequency band limits in spectral analysis of heart rate variability in preterm infants

OBJECTIVES

The current study aims to assess different high-frequency (HF) band power calculations based on different frequency bandwidth values, and compare them with the time domain the root mean square of successive RR differences (RMSSD) value in preterm infants.

METHODS

At week 32, electrocardiogram (ECG) and breathing rate (BR) were recorded for 24 h on 30 preterm infants born between 28 and 32 weeks. The recording held in the neonatal intensive care unit without any interruption of routine.

RESULTS

The median 24 h BR was 40-78 breaths per minute. The RMSSD was highly and positively correlated with frequency bands that were based on each preterms BR range, or on a constant frequency with band limits of 0.4-2 Hz.

CONCLUSIONS

At week 32, HF band Hz limits should be calculated based on each child's breathing rate, generally between 0.4 and 2 Hz.

Neonatal heart rate variability: a contemporary scoping review of analysis methods and clinical applications

BACKGROUND

Neonatal heart rate variability (HRV) is widely used as a research tool. However, HRV calculation methods are highly variable making it difficult for comparisons between studies.

OBJECTIVES

To describe the different types of investigations where neonatal HRV was used, study characteristics, and types of analyses performed.

ELIGIBILITY CRITERIA

Human neonates ≤1 month of corrected age.

SOURCES OF EVIDENCE

A protocol and search strategy of the literature was developed in collaboration with the McGill University Health Center's librarians and articles were obtained from searches in the Biosis, Cochrane, Embase, Medline and Web of Science databases published between 1 January 2000 and 1 July 2020.

CHARTING METHODS

A single reviewer screened for eligibility and data were extracted from the included articles. Information collected included the study characteristics and population, type of HRV analysis used (time domain, frequency domain, non-linear, heart rate characteristics (HRC) parameters) and clinical applications (physiological and pathological conditions, responses to various stimuli and outcome prediction).

RESULTS

Of the 286 articles included, 171 (60%) were small single centre studies (sample size <50) performed on term infants (n=136). There were 138 different types of investigations reported: physiological investigations (n=162), responses to various stimuli (n=136), pathological conditions (n=109) and outcome predictor (n=30). Frequency domain analyses were used in 210 articles (73%), followed by time domain (n=139), non-linear methods (n=74) or HRC analyses (n=25). Additionally, over 60 different measures of HRV were reported; in the frequency domain analyses alone there were 29 different ranges used for the low frequency band and 46 for the high frequency band.

CONCLUSIONS

Neonatal HRV has been used in diverse types of investigations with significant lack of consistency in analysis methods applied. Specific guidelines for HRV analyses in neonates are needed to allow for comparisons between studies.

Evaluation of maturation in preterm infants through an ensemble machine learning algorithm using physiological signals

This study was designed to test if heart rate variability (HRV) data from preterm and full-term infants could be used to estimate their functional maturational age (FMA), using a machine learning model. We propose that the FMA, and its deviation from the postmenstrual age (PMA) of the infants could inform physicians about the progress of the maturation of the infants. The HRV data was acquired from 50 healthy infants, born between 25 and 41 weeks of gestational age, who did not present any signs of abnormal maturation relative to their age group during the period of observation. The HRV features were used as input for a machine learning model that uses filtering and genetic algorithms for feature selection, and an ensemble machine learning (EML) algorithm, which combines linear and random forest regressions, to produce as output a FMA. Using HRV data, the FMA had a mean absolute error of 0.93 weeks, 95% CI [0.78, 1.08], compared to the PMA. These results demonstrate that HRV features of newborn infants can be used by an EML model to estimate their FMA. This method was also generalized using respiration rate variability (RRV) and bradycardia data, obtaining similar results. The FMA, predicted either by HRV, RRV or bradycardia, and its deviation from the true PMA of the infants, could be used as a surrogate measure of the maturational age of the infants, which could potentially be monitored non-invasively and in real-time in the setting of neonatal intensive care units.

Heart Rate Variability in the Perinatal Period: A Critical and Conceptual Review

Neonatal intensive care units (NICUs) greatly expand the use of technology. There is a need to accurately diagnose discomfort, pain, and complications, such as sepsis, mainly before they occur. While specific treatments are possible, they are often time-consuming, invasive, or painful, with detrimental effects for the development of the infant. In the last 40 years, heart rate variability (HRV) has emerged as a non-invasive measurement to monitor newborns and infants, but it still is underused. Hence, the present paper aims to review the utility of HRV in neonatology and the instruments available to assess it, showing how HRV could be an innovative tool in the years to come. When continuously monitored, HRV could help assess the baby’s overall wellbeing and neurological development to detect stress-/pain-related behaviors or pathological conditions, such as respiratory distress syndrome and hyperbilirubinemia, to address when to perform procedures to reduce the baby’s stress/pain and interventions, such as therapeutic hypothermia, and to avoid severe complications, such as sepsis and necrotizing enterocolitis, thus reducing mortality. Based on literature and previous experiences, the first step to efficiently introduce HRV in the NICUs could consist in a monitoring system that uses photoplethysmography, which is low-cost and non-invasive, and displays one or a few metrics with good clinical utility. However, to fully harness HRV clinical potential and to greatly improve neonatal care, the monitoring systems will have to rely on modern bioinformatics (machine learning and artificial intelligence algorithms), which could easily integrate infant’s HRV metrics, vital signs, and especially past history, thus elaborating models capable to efficiently monitor and predict the infant’s clinical conditions. For this reason, hospitals and institutions will have to establish tight collaborations between the obstetric, neonatal, and pediatric departments: this way, healthcare would truly improve in every stage of the perinatal period (from conception to the first years of life), since information about patients’ health would flow freely among different professionals, and high-quality research could be performed integrating the data recorded in those departments.