Effect of Inhaled Xenon on Cerebral White Matter Damage in Comatose Survivors of Out-of-Hospital Cardiac Arrest: A Randomized Clinical Trial

IMPORTANCE: Evidence from preclinical models indicates that xenon gas can prevent the development of cerebral damage after acute global hypoxic-ischemic brain injury but, thus far, these putative neuroprotective properties have not been reported in human studies. OBJECTIVE: To determine the effect of inhaled xenon on ischemic white matter damage assessed with magnetic resonance imaging (MRI). DESIGN, SETTING, AND PARTICIPANTS: A randomized single-blind phase 2 clinical drug trial conducted between August 2009 and March 2015 at 2 multipurpose intensive care units in Finland. One hundred ten comatose patients (aged 24-76 years) who had experienced out-of-hospital cardiac arrest were randomized. INTERVENTIONS: Patients were randomly assigned to receive either inhaled xenon combined with hypothermia (33°C) for 24 hours (n = 55 in the xenon group) or hypothermia treatment alone (n = 55 in the control group). MAIN OUTCOMES AND MEASURES: The primary end point was cerebral white matter damage as evaluated by fractional anisotropy from diffusion tensor MRI scheduled to be performed between 36 and 52 hours after cardiac arrest. Secondary end points included neurological outcome assessed using the modified Rankin Scale (score 0 [no symptoms] through 6 [death]) and mortality at 6 months. RESULTS: Among the 110 randomized patients (mean age, 61.5 years; 80 men [72.7%]), all completed the study. There were MRI data from 97 patients (88.2%) a median of 53 hours (interquartile range [IQR], 47-64 hours) after cardiac arrest. The mean global fractional anisotropy values were 0.433 (SD, 0.028) in the xenon group and 0.419 (SD, 0.033) in the control group. The age-, sex-, and site-adjusted mean global fractional anisotropy value was 3.8% higher (95% CI, 1.1%-6.4%) in the xenon group (adjusted mean difference, 0.016 [95% CI, 0.005-0.027], P = .006). At 6 months, 75 patients (68.2%) were alive. Secondary end points at 6 months did not reveal statistically significant differences between the groups. In ordinal analysis of the modified Rankin Scale, the median (IQR) value was 1 (1-6) in the xenon group and 1 (0-6) in the control group (median difference, 0 [95% CI, 0-0]; P = .68). The 6-month mortality rate was 27.3% (15/55) in the xenon group and 34.5% (19/55) in the control group (adjusted hazard ratio, 0.49 [95% CI, 0.23-1.01]; P = .053). CONCLUSIONS AND RELEVANCE: Among comatose survivors of out-of-hospital cardiac arrest, inhaled xenon combined with hypothermia compared with hypothermia alone resulted in less white matter damage as measured by fractional anisotropy of diffusion tensor MRI. However, there was no statistically significant difference in neurological outcomes or mortality at 6 months. These preliminary findings require further evaluation in an adequately powered clinical trial designed to assess clinical outcomes associated with inhaled xenon among survivors of out-of-hospital cardiac arrest. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT00879892

Comparison of the prognostic value of early-phase proton magnetic resonance spectroscopy and diffusion tensor imaging with serum neuron-specific enolase at 72 h in comatose survivors of out-of-hospital cardiac arrest-a substudy of the XeHypotheca trial

Purpose: We compared the predictive accuracy of early-phase brain diffusion tensor imaging (DTI), proton magnetic resonance spectroscopy (1H-MRS), and serum neuron-specific enolase (NSE) against the motor score and epileptic seizures (ES) for poor neurological outcome after out-of-hospital cardiac arrest (OHCA).Methods: The predictive accuracy of DTI, 1H-MRS, and NSE along with motor score at 72 h and ES for the poor neurological outcome (modified Rankin Scale, mRS, 3 - 6) in 92 comatose OHCA patients at 6 months was assessed by area under the receiver operating characteristic curve (AUROC). Combined models of the variables were included as exploratory.Results: The predictive accuracy of fractional anisotropy (FA) of DTI (AUROC 0.73, 95% CI 0.62-0.84), total N-acetyl aspartate/total creatine (tNAA/tCr) of 1H-MRS (0.78 (0.68 - 0.88)), or NSE at 72 h (0.85 (0.76 - 0.93)) was not significantly better than motor score at 72 h (0.88 (95% CI 0.80-0.96)). The addition of FA and tNAA/tCr to a combination of NSE, motor score, and ES provided a small but statistically significant improvement in predictive accuracy (AUROC 0.92 (0.85-0.98) vs 0.98 (0.96-1.00), p = 0.037).Conclusion: None of the variables (FA, tNAA/tCr, ES, NSE at 72 h, and motor score at 72 h) differed significantly in predicting poor outcomes in this patient group. Early-phase quantitative neuroimaging provided a statistically significant improvement for the predictive value when combined with ES and motor score with or without NSE. However, in clinical practice, the additional value is small, and considering the costs and challenges of imaging in this patient group, early-phase DTI/MRS cannot be recommended for routine use.</p

Effect of nonstationarities on detrended fluctuation analysis

Detrended fluctuation analysis (DFA) is a scaling analysis method used to quantify long-range power-law correlations in signals. Many physical and biological signals are ``noisy'', heterogeneous and exhibit different types of nonstationarities, which can affect the correlation properties of these signals. We systematically study the effects of three types of nonstationarities often encountered in real data. Specifically, we consider nonstationary sequences formed in three ways: (i) stitching together segments of data obtained from discontinuous experimental recordings, or removing some noisy and unreliable parts from continuous recordings and stitching together the remaining parts -- a ``cutting'' procedure commonly used in preparing data prior to signal analysis; (ii) adding to a signal with known correlations a tunable concentration of random outliers or spikes with different amplitude, and (iii) generating a signal comprised of segments with different properties -- e.g. different standard deviations or different correlation exponents. We compare the difference between the scaling results obtained for stationary correlated signals and correlated signals with these three types of nonstationarities.Comment: 17 pages, 10 figures, corrected some typos, added one referenc

Effect of Trends on Detrended Fluctuation Analysis

Detrended fluctuation analysis (DFA) is a scaling analysis method used to estimate long-range power-law correlation exponents in noisy signals. Many noisy signals in real systems display trends, so that the scaling results obtained from the DFA method become difficult to analyze. We systematically study the effects of three types of trends -- linear, periodic, and power-law trends, and offer examples where these trends are likely to occur in real data. We compare the difference between the scaling results for artificially generated correlated noise and correlated noise with a trend, and study how trends lead to the appearance of crossovers in the scaling behavior. We find that crossovers result from the competition between the scaling of the noise and the ``apparent'' scaling of the trend. We study how the characteristics of these crossovers depend on (i) the slope of the linear trend; (ii) the amplitude and period of the periodic trend; (iii) the amplitude and power of the power-law trend and (iv) the length as well as the correlation properties of the noise. Surprisingly, we find that the crossovers in the scaling of noisy signals with trends also follow scaling laws -- i.e. long-range power-law dependence of the position of the crossover on the parameters of the trends. We show that the DFA result of noise with a trend can be exactly determined by the superposition of the separate results of the DFA on the noise and on the trend, assuming that the noise and the trend are not correlated. If this superposition rule is not followed, this is an indication that the noise and the superimposed trend are not independent, so that removing the trend could lead to changes in the correlation properties of the noise.Comment: 20 pages, 16 figure

Distribution of Hyperpolarized Xenon in the Brain Following Sensory Stimulation: Preliminary MRI Findings

In hyperpolarized xenon magnetic resonance imaging (HP 129Xe MRI), the inhaled spin-1/2 isotope of xenon gas is used to generate the MR signal. Because hyperpolarized xenon is an MR signal source with properties very different from those generated from water-protons, HP 129Xe MRI may yield structural and functional information not detectable by conventional proton-based MRI methods. Here we demonstrate the differential distribution of HP 129Xe in the cerebral cortex of the rat following a pain stimulus evoked in the animal's forepaw. Areas of higher HP 129Xe signal corresponded to those areas previously demonstrated by conventional functional MRI (fMRI) methods as being activated by a forepaw pain stimulus. The percent increase in HP 129Xe signal over baseline was 13–28%, and was detectable with a single set of pre and post stimulus images. Recent innovations in the production of highly polarized 129Xe should make feasible the emergence of HP 129Xe MRI as a viable adjunct method to conventional MRI for the study of brain function and disease

Complex systems and the technology of variability analysis

Characteristic patterns of variation over time, namely rhythms, represent a defining feature of complex systems, one that is synonymous with life. Despite the intrinsic dynamic, interdependent and nonlinear relationships of their parts, complex biological systems exhibit robust systemic stability. Applied to critical care, it is the systemic properties of the host response to a physiological insult that manifest as health or illness and determine outcome in our patients. Variability analysis provides a novel technology with which to evaluate the overall properties of a complex system. This review highlights the means by which we scientifically measure variation, including analyses of overall variation (time domain analysis, frequency distribution, spectral power), frequency contribution (spectral analysis), scale invariant (fractal) behaviour (detrended fluctuation and power law analysis) and regularity (approximate and multiscale entropy). Each technique is presented with a definition, interpretation, clinical application, advantages, limitations and summary of its calculation. The ubiquitous association between altered variability and illness is highlighted, followed by an analysis of how variability analysis may significantly improve prognostication of severity of illness and guide therapeutic intervention in critically ill patients

Fluid challenges in intensive care: the FENICE study A global inception cohort study

Fluid challenges (FCs) are one of the most commonly used therapies in critically ill patients and represent the cornerstone of hemodynamic management in intensive care units. There are clear benefits and harms from fluid therapy. Limited data on the indication, type, amount and rate of an FC in critically ill patients exist in the literature. The primary aim was to evaluate how physicians conduct FCs in terms of type, volume, and rate of given fluid; the secondary aim was to evaluate variables used to trigger an FC and to compare the proportion of patients receiving further fluid administration based on the response to the FC.This was an observational study conducted in ICUs around the world. Each participating unit entered a maximum of 20 patients with one FC.2213 patients were enrolled and analyzed in the study. The median [interquartile range] amount of fluid given during an FC was 500 ml (500-1000). The median time was 24 min (40-60 min), and the median rate of FC was 1000 [500-1333] ml/h. The main indication for FC was hypotension in 1211 (59 %, CI 57-61 %). In 43 % (CI 41-45 %) of the cases no hemodynamic variable was used. Static markers of preload were used in 785 of 2213 cases (36 %, CI 34-37 %). Dynamic indices of preload responsiveness were used in 483 of 2213 cases (22 %, CI 20-24 %). No safety variable for the FC was used in 72 % (CI 70-74 %) of the cases. There was no statistically significant difference in the proportion of patients who received further fluids after the FC between those with a positive, with an uncertain or with a negatively judged response.The current practice and evaluation of FC in critically ill patients are highly variable. Prediction of fluid responsiveness is not used routinely, safety limits are rarely used, and information from previous failed FCs is not always taken into account

Nurses' perceptions of aids and obstacles to the provision of optimal end of life care in ICU

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