Complexity of intracranial pressure correlates with outcome after traumatic brain injury

Abstract

This study applied multiscale entropy analysis to investigate the correlation between the complexity of intracranial pressure waveform and outcome after traumatic brain injury. Intracranial pressure and arterial blood pressure waveforms were low-pass filtered to remove the respiratory and pulse components and then processed using a multiscale entropy algorithm to produce a complexity index. We identified significant differences across groups classified by the Glasgow Outcome Scale in intracranial pressure, pressure-reactivity index and complexity index of intracranial pressure (P < 0.0001; P = 0.001; P < 0.0001, respectively). Outcome was dichotomized as survival/death and also as favourable/unfavourable. The complexity index of intracranial pressure achieved the strongest statistical significance (F = 28.7; P < 0.0001 and F = 17.21; P < 0.0001, respectively) and was identified as a significant independent predictor of mortality and favourable outcome in a multivariable logistic regression model (P < 0.0001). The results of this study suggest that complexity of intracranial pressure assessed by multiscale entropy was significantly associated with outcome in patients with brain injury.

Identification of Atrial Fibrillation by Quantitative Analyses of Fingertip Photoplethysmogram

“…Recently, several nonlinear analytical methods had been applied to quantify the complex regulatory dynamics of human biological signals such as heart rate variability21, electroencephalography22, and intracranial pressure23. Because the characteristics of those signals are physiologically nonlinear, the advantages of using nonlinear methods vs. conventional linear methods to describe the complex patterns have been shown in several earlierstudies21222324.…”

Entropy of Entropy: Measurement of Dynamical Complexity for Biological Systems

“…MSE has been widely applied in analyzing many physiologic signals, such as heart rate [2,3,24], electroencephalography (EEG) signal [25][26][27], blood oxygen level-dependent signals in functional magnetic resonance imaging [28], diffusion tensor imaging (DTI) of the brain [29], neuronal spiking [30], center of pressure signals in balance [31,32] and intracranial pressure signal [33].…”

Effect of infusion tests on the dynamical properties of intracranial pressure in hydrocephalus

“…For this reason, prior research has been devoted to the development of alternatives to study ICP. Some of them were based on non-linear methods, including approximate entropy [13], multiscale entropy [14] and Lempel-Ziv complexity [8,15]. Results revealed that intracranial hypertension was associated with a lower ICP signal complexity in children with TBI [13,15] and in adults with hydrocephalus [8].…”

“…Results revealed that intracranial hypertension was associated with a lower ICP signal complexity in children with TBI [13,15] and in adults with hydrocephalus [8]. Moreover, reduced complexity seems to be linked to poor outcome after TBI [14]. On the other hand, previous studies addressed the spectral analysis of ICP signals [11,[16][17][18].…”