Abstract Background: Heart rate variability analysis offers real-time quantification of autonomic disturbance after perinatal asphyxia, and may therefore aid in disease stratification and prognostication after neonatal encephalopathy (NE). Objective: To systematically review the existing literature on the accuracy of early heart rate variability (HRV) to predict brain injury and adverse neurodevelopmental outcomes after NE. Design/Methods: We systematically searched the literature published between May 1947 and May 2018. We included all prospective and retrospective studies reporting HRV metrics, within the first 7 days of life in babies with NE, and its association with adverse outcomes (defined as evidence of brain injury on magnetic resonance imaging and/or abnormal neurodevelopment at ≥1 year of age). We extracted raw data wherever possible to calculate the prognostic indices with confidence intervals. Results: We retrieved 379 citations, 5 of which met the criteria. One further study was excluded as it analysed an already-included cohort.

The 4 studies provided data on 205 babies, 80 (39%) of whom had adverse outcomes. Prognostic accuracy was reported for 12 different HRV metrics and the area under the curve (AUC) varied between 0.79 and 0.94.

The best performing metric reported in the included studies was the relative power of high-frequency band, with an AUC of 0.94. Conclusions: HRV metrics are a promising bedside tool for early prediction of brain injury and neurodevelopmental outcome in babies with NE. Due to the small number of studies available, their heterogeneity and methodological limitations, further research is needed to refine this tool so that it can be used in clinical practice. Metasequoia 4 serial id password key. Karger AG, Basel Introduction Neonatal encephalopathy (NE) results primarily from a presumed lack of oxygen and blood flow to the fetal brain around the time of birth and accounts for 1 million deaths worldwide every year []. Although rescue hypothermic neuroprotection improves survival and neurodevelopment outcome after NE, the early identification of babies at risk of brain injury and adverse outcomes is challenging due to the evolving clinical picture.

An abnormal voltage or pattern of amplitude-integrated electroencephalography (aEEG) has been used as a bedside tool for quantifying brain injury and as an inclusion criterion for some of the cooling trials [, ]. More recent data suggests that aEEG does not offer an added advantage over clinical examination [] and its prognostic accuracy in cooled infants is poor [].

As autonomic disturbance is the hallmark of perinatal hypoxic injury, heart rate variability (HRV) analysis may offer a promising solution. HRV analysis quantifies variations in heartbeat intervals, offering a non-invasive measure of autonomic function, as it reflects the actions of the sympathetic and parasympathetic nervous systems. The simplest measure of HRV is determined by the standard deviation of the difference between consecutive RR intervals (SDNN), but many other measures of HRV continue to be developed [, ]. Currently, HRV analyses can include not only linear measures in time and frequency domains but also several non-linear metrics derived from complexity analysis []. Loss of HRV occurs in traumatic brain injury and during seizures [, ], and is associated with brain injury and adverse neurodevelopment in very-low-birth-weight babies [, ]. In babies with birth asphyxia, the early identification of brain injury risk via HRV analysis could benefit patients by facilitating early disease stratification and the implementation of the most appropriate treatment.