Assessment of Outliers and Detection of Artifactual Network Segments Using Univariate and Multivariate Dispersion Entropy on Physiological Signals.

Network physiology has emerged as a promising paradigm for the extraction of clinically relevant information from physiological signals by moving from univariate to multivariate analysis, allowing for the inspection of interdependencies between organ systems. However, for its successful implementation, the disruptive effects of artifactual outliers, which are a common occurrence in physiological recordings, have to be studied, quantified, and addressed. Within the scope of this study, we utilize Dispersion Entropy (DisEn) to initially quantify the capacity of outlier samples to disrupt the values of univariate and multivariate features extracted with DisEn from physiological network segments consisting of synchronised, electroencephalogram, nasal respiratory, blood pressure, and electrocardiogram signals. The DisEn algorithm is selected due to its efficient computation and good performance in the detection of changes in signals for both univariate and multivariate time-series. The extracted features are then utilised for the training and testing of a logistic regression classifier in univariate and multivariate configurations in an effort to partially automate the detection of artifactual network segments. Our results indicate that outlier samples cause significant disruption in the values of extracted features with multivariate features displaying a certain level of robustness based on the number of signals formulating the network segments from which they are extracted. Furthermore, the deployed classifiers achieve noteworthy performance, where the percentage of correct network segment classification surpasses 95% in a number of experimental setups, with the effectiveness of each configuration being affected by the signal in which outliers are located. Finally, due to the increase in the number of features extracted within the framework of network physiology and the observed impact of artifactual samples in the accuracy of their values, the implementation of algorithmic steps capable of effective feature selection is highlighted as an important area for future research.

Augmentation of Dispersion Entropy for Handling Missing and Outlier Samples in Physiological Signal Monitoring.

Entropy quantification algorithms are becoming a prominent tool for the physiological monitoring of individuals through the effective measurement of irregularity in biological signals. However, to ensure their effective adaptation in monitoring applications, the performance of these algorithms needs to be robust when analysing time-series containing missing and outlier samples, which are common occurrence in physiological monitoring setups such as wearable devices and intensive care units. This paper focuses on augmenting Dispersion Entropy (DisEn) by introducing novel variations of the algorithm for improved performance in such applications. The original algorithm and its variations are tested under different experimental setups that are replicated across heart rate interval, electroencephalogram, and respiratory impedance time-series. Our results indicate that the algorithmic variations of DisEn achieve considerable improvements in performance while our analysis signifies that, in consensus with previous research, outlier samples can have a major impact in the performance of entropy quantification algorithms. Consequently, the presented variations can aid the implementation of DisEn to physiological monitoring applications through the mitigation of the disruptive effect of missing and outlier samples.

Visualizing Cerebrovascular Autoregulation Insults and Their Association with Outcome in Adult and Paediatric Traumatic Brain Injury.

OBJECTIVE: The aim of this study is to assess visually the impact of duration and intensity of cerebrovascular autoregulation insults on 6-month neurological outcome in severe traumatic brain injury. MATERIAL AND METHODS: Retrospective analysis of prospectively collected minute-by-minute intracranial pressure (ICP) and mean arterial blood pressure data of 259 adult and 99 paediatric traumatic brain injury (TBI) patients from multiple European centres. The relationship of the 6-month Glasgow Outcome Scale with cerebrovascular autoregulation insults (defined as the low-frequency autoregulation index above a certain threshold during a certain time) was visualized in a colour-coded plot. The analysis was performed separately for autoregulation insults occurring with cerebral perfusion pressure (CPP) below 50 mmHg, with ICP above 25 mmHg and for the subset of adult patients that did not undergo decompressive craniectomy. RESULTS: The colour-coded plots showed a time-intensity-dependent association with outcome for cerebrovascular autoregulation insults in adult and paediatric TBI patients. Insults with a low-frequency autoregulation index above 0.2 were associated with worse outcomes and below -0.6 with better outcomes, with and approximately exponentially decreasing transition curve between the two intensity thresholds. All insults were associated with worse outcomes when CPP was below 50 mmHg or ICP was above 25 mmHg. CONCLUSIONS: The colour-coded plots indicate that cerebrovascular autoregulation is disturbed in a dynamic manner, such that duration and intensity play a role in the determination of a zone associated with better neurological outcome.

Early Detection of Increased Intracranial Pressure Episodes in Traumatic Brain Injury: External Validation in an Adult and in a Pediatric Cohort.

OBJECTIVE: A model for early detection of episodes of increased intracranial pressure in traumatic brain injury patients has been previously developed and validated based on retrospective adult patient data from the multicenter Brain-IT database. The purpose of the present study is to validate this early detection model in different cohorts of recently treated adult and pediatric traumatic brain injury patients. DESIGN: Prognostic modeling. Noninterventional, observational, retrospective study. SETTING AND PATIENTS: The adult validation cohort comprised recent traumatic brain injury patients from San Gerardo Hospital in Monza (n = 50), Leuven University Hospital (n = 26), Antwerp University Hospital (n = 19), Tübingen University Hospital (n = 18), and Southern General Hospital in Glasgow (n = 8). The pediatric validation cohort comprised patients from neurosurgical and intensive care centers in Edinburgh and Newcastle (n = 79). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The model's performance was evaluated with respect to discrimination, calibration, overall performance, and clinical usefulness. In the recent adult validation cohort, the model retained excellent performance as in the original study. In the pediatric validation cohort, the model retained good discrimination and a positive net benefit, albeit with a performance drop in the remaining criteria. CONCLUSIONS: The obtained external validation results confirm the robustness of the model to predict future increased intracranial pressure events 30 minutes in advance, in adult and pediatric traumatic brain injury patients. These results are a large step toward an early warning system for increased intracranial pressure that can be generally applied. Furthermore, the sparseness of this model that uses only two routinely monitored signals as inputs (intracranial pressure and mean arterial blood pressure) is an additional asset.

Continuous Optimal CPP Based on Minute-by-Minute Monitoring Data: A Study of a Pediatric Population.

This paper describes the use of minute-by-minute monitoring data to determine continuous optimal cerebral perfusion pressure (CPP) recommendations based on the autoregulatory status of pediatric patients with traumatic brain injury. Data from 79 children were retrospectively studied. Optimal CPP recommendations were obtained for the majority of the first 72 h of monitoring time. Actual CPP close to recommended CPP values was significantly associated with better outcome and was a significant independent predictor of better outcome when considering IMPACT model covariates in multivariate logistic regression.

Visualization of the Intracranial Pressure and Time Burden in Childhood Brain Trauma: What We Have Learned One Decade on With KidsBrainIT.

To validate the intracranial pressure (ICP) dose-response visualization plot for the first time in a novel prospectively collected pediatric traumatic brain injury (pTBI) data set from the multi-center, multi-national KidsBrainIT consortium. Prospectively collected minute-by-minute ICP and mean arterial blood pressure time series of 104 pTBI patients were categorized in ICP intensity-duration episodes. These episodes were correlated with the 6-month Glasgow Outcome Score (GOS) and displayed in a color-coded ICP dose-response plot. The influence of cerebrovascular reactivity and cerebral perfusion pressure (CPP) were investigated. The generated ICP dose-response plot on the novel data set was similar to the previously published pediatric plot. This study confirmed that higher ICP episodes were tolerated for a shorter duration of time, with an approximately exponential decay curve delineating the positive and negative association zones. ICP above 20 mm Hg for any duration in time was associated with poor outcome in our patients. Cerebrovascular reactivity state did not influence their respective transition curves above 10 mm Hg ICP. CPP below 50 mm Hg was not tolerated, regardless of ICP and duration, and was associated with worse outcome. The ICP dose-response plot was reproduced in a novel and independent pTBI data set. ICP above 20 mm Hg and CPP below 50 mm Hg for any duration in time were associated with worse outcome. This highlighted a pressing need to reduce pediatric ICP therapeutic thresholds used at the bedside.

Stratified Multivariate Multiscale Dispersion Entropy for Physiological Signal Analysis.

Multivariate entropy quantification algorithms are becoming a prominent tool for the extraction of information from multi-channel physiological time-series. However, in the analysis of physiological signals from heterogeneous organ systems, certain channels may overshadow the patterns of others, resulting in information loss. Here, we introduce the framework of Stratified Entropy to prioritize each channels' dynamics based on their allocation to respective strata, leading to a richer description of the multi-channel time-series. As an implementation of the framework, three algorithmic variations of the Stratified Multivariate Multiscale Dispersion Entropy are introduced. These variations and the original algorithm are applied to synthetic time-series, waveform physiological time-series, and derivative physiological data. Based on the synthetic time-series experiments, the variations successfully prioritize channels following their strata allocation while maintaining the low computation time of the original algorithm. In experiments on waveform physiological time-series and derivative physiological data, increased discrimination capacity was noted for multiple strata allocations in the variations when benchmarked to the original algorithm. This suggests improved physiological state monitoring by the variations. Furthermore, our variations can be modified to utilize a priori knowledge for the stratification of channels. Thus, our research provides a novel approach for the extraction of previously inaccessible information from multi-channel time series acquired from heterogeneous systems.

Asthma in paediatric intensive care in England residents: observational study.

Despite high prevalence of asthma in children in the UK, there were no prior report on asthma admissions in paediatric intensive care units (PICU). We investigated the epidemiology and healthcare resource utilisation in children with asthma presenting to PICUs in England. PICANet, a UK national PICU database, was queried for asthma as the primary reason for admission, of children resident in England from April 2006 until March 2013. There were 2195 admissions to PICU for a median stay of 1.4 days. 59% were males and 51% aged 0-4 years. The fourth and fifth most deprived quintiles represented 61% (1329) admissions and 73% (11) of the 15 deaths. Deaths were most frequent in 10-14 years age (n = 11, 73%), with no deaths in less than 5 years age. 38% of admissions (828/2193) received invasive ventilation, which was more frequent with increasing deprivation (13% (108/828) in least deprived to 31% (260/828) in most deprived) and with decreasing age (0-4-year-olds: 49%, 409/828). This first multi-centre PICU study in England found that children from more deprived neighbourhoods represented the majority of asthma admissions, invasive ventilation and deaths in PICU. Children experiencing socioeconomic deprivation could benefit from enhanced asthma support in the community.

Face Coverings, Aerosol Dispersion and Mitigation of Virus Transmission Risk.

The SARS-CoV-2 virus is primarily transmitted through virus-laden fluid particles ejected from the mouth of infected people. Face covers can mitigate the risk of virus transmission but their outward effectiveness is not fully ascertained. Objective: by using a background oriented schlieren technique, we aim to investigate the air flow ejected by a person while quietly and heavily breathing, while coughing, and with different face covers. Results: we found that all face covers without an outlet valve reduce the front flow through by at least 63% and perhaps as high as 86% if the unfiltered cough jet distance was resolved to the anticipated maximum distance of 2-3 m. However, surgical and handmade masks, and face shields, generate significant leakage jets that may present major hazards. Conclusions: the effectiveness of the masks should mostly be considered based on the generation of secondary jets rather than on the ability to mitigate the front throughflow.

Quality of cardio-pulmonary resuscitation (CPR) during paediatric resuscitation training: time to stop the blind leading the blind.

AIMS: Recent evidence suggested that the quality of cardio-pulmonary resuscitation (CPR) during adult advanced life support training was suboptimal. This study aimed to assess the CPR quality of a paediatric resuscitation training programme, and to determine whether it was sufficiently addressed by the trainee team leaders during training. METHODS: CPR quality of 20 consecutive resuscitation scenario training sessions was audited prospectively using a pre-designed proforma. A consultant intensivist and a senior nurse who were also Advanced Paediatric Life Support (APLS) instructors assessed the CPR quality which included ventilation frequency, chest compression rate and depth, and any unnecessary interruption in chest compressions. Team leaders' response to CPR quality and elective change of compression rescuer during training were also recorded. RESULTS: Airway patency was not assessed in 13 sessions while ventilation rate was too fast in 18 sessions. Target compression rate was not achieved in only 1 session. The median chest compression rate was 115 beats/min. Chest compressions were too shallow in 10 sessions and were interrupted unnecessarily in 13 sessions. More than 50% of training sessions did not have elective change of the compression rescuer. 19 team leaders failed to address CPR quality during training despite all team leaders being certified APLS providers. CONCLUSIONS: The quality of CPR performance was suboptimal during paediatric resuscitation training and team leaders-in-training had little awareness of this inadequacy. Detailed CPR quality assessment and feedback should be integrated into paediatric resuscitation training to ensure optimal performance in real life resuscitations.

Application of Dispersion Entropy to Healthy and Pathological Heartbeat ECG Segments.

Entropy quantification algorithms are a prominent tool for the quantification of irregularity in biological signal segments towards the characterization of the physiological state of individuals. This paper investigates the potential of Dispersion Entropy (DisEn) as a non-linear method to quantify the uncertainty of ECG signal segments for different types of heartbeats and the stratification of healthy heartbeats for the potential detection of developing pathologies in individuals. Our results indicate that the DisEn algorithm produces distributions with significant differences for the considered types of heartbeats, with higher DisEn values being more prominent in pathological heartbeats and normal heartbeats preceding them. This suggests that, with further research, DisEn algorithms can be integrated with heartbeat detection and classification algorithms for the improvement of medical prognosis through ECG signal processing.

Visualizing the pressure and time burden of intracranial hypertension in adult and paediatric traumatic brain injury.

PURPOSE: To assess the impact of the duration and intensity of episodes of increased intracranial pressure on 6-month neurological outcome in adult and paediatric traumatic brain injury. METHODS: Analysis of prospectively collected minute-by-minute intracranial pressure and mean arterial blood pressure data of 261 adult and 99 paediatric traumatic brain injury patients from multiple European centres. The relationship of episodes of elevated intracranial pressure (defined as a pressure above a certain threshold during a certain time) with 6-month Glasgow Outcome Scale was visualized in a colour-coded plot. RESULTS: The colour-coded plot illustrates the intuitive concept that episodes of higher intracranial pressure can only be tolerated for shorter durations: the curve that delineates the duration and intensity of those intracranial pressure episodes associated with worse outcome is an approximately exponential decay curve. In children, the curve resembles that of adults, but the delineation between episodes associated with worse outcome occurs at lower intracranial pressure thresholds. Intracranial pressures above 20 mmHg lasting longer than 37 min in adults, and longer than 8 min in children, are associated with worse outcomes. In a multivariate model, together with known baseline risk factors for outcome in severe traumatic brain injury, the cumulative intracranial pressure-time burden is independently associated with mortality. When cerebrovascular autoregulation, assessed with the low-frequency autoregulation index, is impaired, the ability to tolerate elevated intracranial pressures is reduced. When the cerebral perfusion pressure is below 50 mmHg, all intracranial pressure insults, regardless of duration, are associated with worse outcome. CONCLUSIONS: The intracranial pressure-time burden associated with worse outcome is visualised in a colour-coded plot. In children, secondary injury occurs at lower intracranial pressure thresholds as compared to adults. Impaired cerebrovascular autoregulation reduces the ability to tolerate intracranial pressure insults. Thus, 50 mmHg might be the lower acceptable threshold for cerebral perfusion pressure.