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Introduction: Pressure reactivity index (PRx) is used for continuous monitoring of cerebrovascular reactivity in traumatic brain injury (TBI). However, PRx has a noisy character. Oscillations in arterial blood pressure (ABP) introduced by cyclic positive end-expiratory pressure adjustment, can make PRx more reliable. However, if oscillations are introduced by the cycling process of an anti-decubitus-mattress the effect on PRx is confounding, as they affect directly also intracranial pressure (ICP). In our routine monitoring in TBI patients we noticed periods of highly regular, slow, spontaneous oscillations in ABP and ICP signals. Research question: We set out to explore the nature of these oscillations and establish if PRx remains reliable during the oscillations. Materials and methods: 10 TBI patients' recordings with oscillations in ICP and ABP were analysed. We computed PRx, PRx variability (hourly-average of standard-deviation, SD), phase-shift and coherence between ABP and ICP in the slow frequency range. Metrics were compared between oscillation and peri-oscillation periods. Results: During oscillations (frequency 0.006 ± 0.002Hz), a significantly lower variability of PRx (SD 0.185vs0.242) and higher coherence ABP-ICP (0.618 ± 0.09 vs 0.534 ± 0.09) were observed. No external oscillations sources could be identified. 34 out of 48 events showed signs of 'active' transmission associated with negative PRx, indicating a potential positive impact on PRx reliability. Discussion and conclusions: Spontaneous oscillations observed in ABP and ICP signals were found to enhance rather than confound PRx reliability. Further research is warranted to elucidate the nature of these oscillations and develop strategies to leverage them for enhancing PRx reliability in TBI monitoring.
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Introduction: PRx can be used as surrogate measure of Cerebral Autoregulation (CA) in traumatic brain injury (TBI) patients. PRx can provide means for individualising cerebral perfusion pressure (CPP) targets, such as CPPopt. However, a recent Delphi consensus of clinicians concluded that consensus could not be reached on the accuracy, reliability, and validation of any current CA assessment method. Research question: We aimed to quantify the short-term uncertainty of PRx time-trends and to relate this to other physiological measurements. Material and methods: Intracranial pressure (ICP), arterial blood pressure (ABP), end-tidal CO2 (EtCO2) high-resolution recordings of 911 TBI patients were processed with ICM + software. Hourly values of metrics that describe the variability within modalities derived from ABP, ICP and EtCO2, were calculated for the first 24h of neuromonitoring. Generalized additive models were used to describe the time trend of the variability in PRx. Linear correlations were studied for describing the relationship between PRx variability and the other physiological modalities. Results: The time profile of variability of PRx decreases over the first 12h and was higher for average PRx â¼0. Increased variability of PRx was not linearly linked with average ABP, ICP, or CPP. For coherence between slow waves of ABP and ICP >0.7, the variability in PRx decreased (R = -0.47, p < 0.001). Discussion and conclusion: PRx is a highly variable parameter. PRx short-term dispersion was not related to average ICP, ABP or CPP. The determinants of uncertainty of PRx should be investigated to improve reliability of individualised CA assessment in TBI patients.
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Introduction: Continuous monitoring of the pressure reactivity index (PRx) provides an estimation of dynamic cerebral autoregulation (CA) at the bedside in traumatic brain injury (TBI) patients. Visualising the time-trend of PRx with a risk bar chart in ICM + software at the bedside allows for better real-time interpretability of the autoregulation status. When PRx>0.3 is sustained for long periods, typically of at least half an hour, the bar shows a pattern called "red solid line" (RSL). RSL was previously described to precede refractory intracranial hypertension and brain death. Research question: We aimed to describe pathophysiological changes in measured signals/parameters during RSL. Material and methods: Observation of time-trends of PRx, intracranial pressure, cerebral perfusion pressure, brain oxygenation and compensatory reserve of TBI patients with RSL. Results: Three pathophysiological patterns were identified: RSL precedes intracranial hypertension, RSL is preceded by intracranial hypertension, or RSL is preceded by brain hypoperfusion. In all cases, RSL was followed by death and the RSL onset was between 1 h and 1 day before the terminal event. Discussion and conclusion: RSL precedes death in intensive care and could represent a marker for terminal clinical deterioration in TBI patients. These findings warrant further investigations in larger cohorts to characterise pathophysiological mechanisms underlying the RSL pattern and whether RSL has a significant relationship with outcome after TBI.
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BACKGROUND: Invasive intracranial pressure (ICP) monitoring is a standard practice in severe brain injury cases, where it allows to derive cerebral perfusion pressure (CPP); ICP-tracing can also provide additional information about intracranial dynamics, forecast episodes of intracranial hypertension and set targets for a tailored therapy to prevent secondary brain injury. Nevertheless, controversies about the advantages of an ICP clinical management are still debated. FINDINGS: This article reviews recent research on ICP to improve the understanding of the topic and uncover the hidden information in this signal that may be useful in clinical practice. Parameters derived from time-domain as well as frequency domain analysis include compensatory reserve, autoregulation estimation, pulse waveform analysis, and behavior of ICP in time. The possibility to predict the outcome and apply a tailored therapy using a personalised perfusion pressure target is also described. CONCLUSIONS: ICP is a crucial signal to monitor in severely brain injured patients; a bedside computer can empower standard monitoring giving new metrics that may aid in clinical management, establish a personalized therapy, and help to predict the outcome. Continuous collaboration between engineers and clinicians and application of new technologies to healthcare, is vital to improve the accuracy of current metrics and progress towards better care with individualized dynamic targets.