TABLE 2.

Interpretations and/or usefulness of some HRV metrics (Task Force of the European Society of Cardiology the North American Society of Pacing Electrophysiology, 1996; Shaffer et al., 2014; Shaffer and Ginsberg, 2017; Oliveira et al., 2019b).

Metric	Interpretation
Most common metrics
RMSSD	Main time-domain measure to assess the HRV modulation due to vagal activity
SDNN	Standard metric of overall HRV, influenced by both SNS and PNS. Gold standard for medical stratification of cardiac risk in adults when recorded over a 24 h period
ULF	No consensus regarding the mechanisms underlying ULF power. Very slow-acting biological processes, such as circadian rhythms, are implicated
VLF	Related to the heart’s intrinsic nervous system, which generates VLF rhythm when afferent sensory cardiac neurons are stimulated. SNS activity due to physical and stress responses influences its oscillations amplitude and frequency
LF	Non-specific index that reflects baroreceptor activity, it contains contributions of both the sympathetic and parasympathetic influences
HF	Expression of parasympathetic activity, it corresponds to the HR variations related to the respiratory cycle known as RSA. It changes according to vagal modulation but does not reflect vagal tone
LF/HF	Used to estimate SNS and PNS balance, although LF does not purely represent SNS, and PNS and SNS interact in a complex non-linear manner
Complex metrics or groups of metrics
fABAS	Scale used for evaluating fetal ANS maturation. It derives from the integration of Hoyer et al. (2013): •amplitude (ACTAMP20), evaluating the fluctuation range of heart beat intervals above an approximated baseline increasing complexity; •skewness, evaluating the complexity of heart rate patterns essentially modulated by complex sympatho-vagal rhythms; •gMSE(3), evaluating the asymmetry, contribution of vagal and sympathetic activity with their different time constants, decline of decelerations, and formation of acceleration patterns; •pNN5, evaluating the formation of vagal rhythms; •VLF/LF, evaluating the baseline fluctuation in relation to sympatho-vagal modulations.
DFA α1 – AsymI – KLPE – SDLE α	Used for assessing vagal modulation in fetuses (Herry et al., 2019)
HRC index	Displayed by the HeRO monitor to estimate the risk of sepsis within 24 h. It derives from a logistic regression calculated on standard deviation of the RR intervals, sample asymmetry, and SampEn to detect irregularities and transient decelerations in HR. HRC index is higher in preterm infants than in full term ones (they show less variability), and it decreases as postmenstrual age increases. HRC index can also rise due to acute inflammation, respiratory deterioration, intraventricular hemorrhage, brain injury, NEC, surgery, ventilation, and drugs, such as anticholinergics, anesthetics, and dexamethasone (in this last case, HRC decreases) (Fairchild and O’Shea, 2010; Fairchild, 2013; Kumar et al., 2020)
RMSS – RMSL – DFA αS – LF – HF	Used to estimate outcomes in case of HIE, especially during hypothermia treatment. Low values of RMSS, RMSL, DFA αS, and LF and a high value of HF may predict an adverse outcome and the need of adjuvant neuroprotective therapies. These metrics could discriminate among different types of brain injury. All these metrics decreased also proportionally to NEC severity (Metzler et al., 2017; Al-Shargabi et al., 2018; Campbell et al., 2018)