Evaluation of the relationship between slow-waves of intracranial pressure, mean arterial pressure and brain tissue oxygen in TBI: a CENTER-TBI exploratory analysis

Abstract

Brain tissue oxygen (PbtO₂) monitoring in traumatic brain injury (TBI) has demonstrated strong associations with global outcome. Additionally, PbtO₂ signals have been used to derive indices thought to be associated with cerebrovascular reactivity in TBI. However, their true relationship to slow-wave vasogenic fluctuations associated with cerebral autoregulation remains unclear. The goal of this study was to investigate the relationship between slow-wave fluctuations of intracranial pressure (ICP), mean arterial pressure (MAP) and PbtO₂ over time. Using the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) high resolution ICU sub-study cohort, we evaluated those patients with recorded high-frequency digital intra-parenchymal ICP and PbtO₂ monitoring data of a minimum of 6 h in duration. Digital physiologic signals were processed for ICP, MAP, and PbtO₂ slow-waves using a moving average filter to decimate the high-frequency signal. The first 5 days of recording were analyzed. The relationship between ICP, MAP and PbtO₂ slow-waves over time were assessed using autoregressive integrative moving average (ARIMA) and vector autoregressive integrative moving average (VARIMA) modelling, as well as Granger causality testing. A total of 47 patients were included. The ARIMA structure of ICP and MAP were similar in time, where PbtO₂ displayed different optimal structure. VARIMA modelling and IRF plots confirmed the strong directional relationship between MAP and ICP, demonstrating an ICP response to MAP impulse. PbtO₂ slow-waves, however, failed to demonstrate a definite response to ICP and MAP slow-wave impulses. These results raise questions as to the utility of PbtO₂ in the derivation of cerebrovascular reactivity measures in TBI. There is a reproducible relationship between slow-wave fluctuations of ICP and MAP, as demonstrated across various time-series analytic techniques. PbtO₂ does not appear to reliably respond in time to slow-wave fluctuations in MAP, as demonstrated on various VARIMA models across all patients. These findings suggest that PbtO₂ should not be utilized in the derivation of cerebrovascular reactivity metrics in TBI, as it does not appear to be responsive to changes in MAP in the slow-waves. These findings corroborate previous results regarding PbtO₂ based cerebrovascular reactivity indices.

Keywords: Autoregulation; Brain tissue oxygen; Cerebrovascular reactivity; TBI; Traumatic brain injury.

Fig. 1

VARIMA IRF Plots for ICP/MAP, PbtO₂/MAP, and PbtO₂/ICP—Patient Example. ICP intracranial pressure, IRF impulse response function, lags refers to number of time points where 1 lag is 10-s, MAP mean arterial pressure, PbtO₂ brain tissue oxygen, VARIMA vector autoregressive integrative moving average. All VARIMA models were constructed using an autoregressive order of 4, integrative order of 1, and moving average order of 4. The IRF plots display the response of one physiologic variable to one standard deviation impulse of the other. Of note, there is minimal response of PbtO₂ to an impulse in MAP or ICP, with a quite extended duration low level elevation in PbtO₂ to MAP impulse that fails to return to baseline even after 5 min worth of lags

Fig. 2

Tri-Variate VARIMA Model IRF Plot—ICP, MAP and PbtO₂—Patient Example. ICP intracranial pressure, IRF impulse response function, lags refers to number of time points where 1 lag is 10-s, MAP mean arterial pressure, PbtO₂ brain tissue oxygen, VARIMA vector autoregressive integrative moving average. The tri-variate VARIMA model was constructed using an autoregressive order of 4, integrative order of 1, and moving average order of 4. The IRF plots display the response of one physiologic variable to one standard deviation impulse of the other. Of note, there is minimal response of PbtO₂ to an impulse in MAP or ICP