Cerebrovascular pressure reactivity monitoring using wavelet analysis in traumatic brain injury patients: A retrospective study

Abstract

BackgroundAfter traumatic brain injury (TBI), the ability of cerebral vessels to appropriately react to changes in arterial blood pressure (pressure reactivity) is impaired, leaving patients vulnerable to cerebral hypo- or hyperperfusion. Although, the traditional pressure reactivity index (PRx) has demonstrated that impaired pressure reactivity is associated with poor patient outcome, PRx is sometimes erratic and may not be reliable in various clinical circumstances. Here, we introduce a more robust transform-based wavelet pressure reactivity index (wPRx) and compare its performance with the widely used traditional PRx across 3 areas: its stability and reliability in time, its ability to give an optimal cerebral perfusion pressure (CPPopt) recommendation, and its relationship with patient outcome.Methods and findingsFive hundred and fifteen patients with TBI admitted in Addenbrooke’s Hospital, United Kingdom (March 23rd, 2003 through December 9th, 2014), with continuous monitoring of arterial blood pressure (ABP) and intracranial pressure (ICP), were retrospectively analyzed to calculate the traditional PRx and a novel wavelet transform-based wPRx. wPRx was calculated by taking the cosine of the wavelet transform phase-shift between ABP and ICP. A time trend of CPPopt was calculated using an automated curve-fitting method that determined the cerebral perfusion pressure (CPP) at which the pressure reactivity (PRx or wPRx) was most efficient (CPPopt_PRx and CPPopt_wPRx, respectively).There was a significantly positive relationship between PRx and wPRx (r = 0.73), and wavelet wPRx was more reliable in time (ratio of between-hour variance to total variance, wPRx 0.957 ± 0.0032 versus PRx and 0.949 ± 0.047 for PRx, p = 0.002). The 2-hour interval standard deviation of wPRx (0.19 ± 0.07) was smaller than that of PRx (0.30 ± 0.13, p < 0.001). wPRx performed better in distinguishing between mortality and survival (the area under the receiver operating characteristic [ROC] curve [AUROC] for wPRx was 0.73 versus 0.66 for PRx, p = 0.003). The mean difference between the patients’ CPP and their CPPopt was related to outcome for both calculation methods. There was a good relationship between the 2 CPPopts (r = 0.814, p < 0.001). CPPopt_wPRx was more stable than CPPopt_PRx (within patient standard deviation 7.05 ± 3.78 versus 8.45 ± 2.90; p < 0.001).Key limitations include that this study is a retrospective analysis and only compared wPRx with PRx in the cohort of patients with TBI. Prior prospective validation is required to better assess clinical utility of this approach.ConclusionswPRx offers several advantages to the traditional PRx: it is more stable in time, it yields a more consistent CPPopt recommendation, and, importantly, it has a stronger relationship with patient outcome. The clinical utility of wPRx should be explored in prospective studies of critically injured neurological patients.

Wavelet pressure reactivity index: a validation study

“…; Liu et al . ). In this paper, we have applied a wavelet semblance algorithm first in two piglet experiments and used wavelet coherence as a measure of a reliable ABP–ICP phase relationship.…”

“…; Liu et al . ). In brief, the WTP at each scale‐frequency point was calculated from 500 s data segments (moving window, with update every 10 s), and subsequently WTC was used to reject corresponding unreliable phase values.…”

“…In this paper, the WTC threshold of 0.48 was used, determined through 10,000 Monte Carlo simulations (detailed description can be found in Liu et al . ). Individual phase shift values with coherence higher than 0.48 were kept, while data points with coherence lower than the threshold were deleted.…”

Pressure reactivity index: journey through the past 20 years

“…-Its reliability can be improved at the cost of the complexity of calculations and interpretation, but only marginally. A good example is the recently proposed 'wavelet PRx' [17]. -Reliable 'optimal CPP' calculations require a sufficiently large span of CPP change, which may not be captured using fixed, relatively short (4-h) data periods.…”

A Wavelet‐Based Correlation Analysis Framework to Study Cerebromuscular Activity in Essential Tremor

“…A wavelet coherence-based clustering of EEG signals has been developed to estimate the brain connectivity in absence epileptic patients [24]. It has also been applied to studies on autism [25], traumatic brain injury [26], schizophrenia [27], and poor sleep quality [28]. However, there is very limited research focusing on its application on ET.…”