Heart rate variability during plateau waves of intracranial pressure: A pilot descriptive study

Heart rate variability (HRV) after traumatic brain injury (TBI): a scoping review

BACKGROUND

Heart rate variability (HRV), defined as the variability between successive heart beats, is a noninvasive measure of autonomic nervous system (ANS) function, which may be altered following traumatic brain injury (TBI). This scoping review summarizes the existing literature regarding changes in HRV after TBI as well as the association between measures of HRV and outcomes following TBI.

METHODS

A literature search for articles assessing 'heart rate variability' and 'brain injury' or 'concussion' was completed. Articles were included if HRV was measured in human subjects with TBI or concussion. Review articles, protocol papers, and studies including non-traumatic injuries were excluded.

RESULTS

Sixty-three articles were included in this review. Varied methods were used to measure HRV in the different studies. Forty articles included information about differences in HRV measures after TBI and/or longitudinal changes after TBI. Fifteen studies assessed HRV and symptoms following TBI, and 15 studies assessed HRV and either functional or cognitive outcomes after TBI.

CONCLUSIONS

HRV has been studied in the context of mortality, clinical symptoms, and medical, functional, or cognitive outcomes following TBI. Methods used to measure HRV have varied amongst the different studies, which may impact findings, standardized protocols are needed for future research.

Multiscale Information Decomposition of Long Memory Processes: Application to Plateau Waves of Intracranial Pressure

Traumatic Brain Injury (TBI) patients present high levels of physical stress, which in some situations can manifest as Plateau Wave (PW) episodes. This intense stress phenomenon can be evidenced by Heart Rate Variability (HRV). Thus, the multivariate and simultaneous analysis of cardio-cerebrovascular oscillations, involving the RR intervals, mean arterial pressure (MAP) and the amplitude of intracranial pressure (AMP), will be useful to understand the interconnections between body signals, allowing the interpretation of the combined activity of pathophysiological mechanisms. In this work, the multiscale representation of the Transfer Entropy (TE) and of its decomposition in the network of these three interacting processes is obtained, based on a Vector AutoRegressive Fractionally Integrated (VARFI) framework for Gaussian processes. This method allows to assess directed interactions and to quantify the information flow accounting for the simultaneous presence of short-term dynamics and long-range correlations. The results show that the baseline RR, but not MAP can provide information about the possibility of a PW arising. During PW, the long-term correlations highlight synergistic interactions between MAP and AMP processes on RR. The multiscale decomposition of the information along with the incorporation of the long term correlations allowed a better description of HRV during PW, highlighting the fact that the HRV mirrors this cerebrovascular phenomena.