Nonrandomness, nonlinear dependence, and nonstationarity of electroencephalographic recordings from epilepsy patients

To derive tests for randomness, nonlinear-independence, and stationarity, we combine surrogates with a nonlinear prediction error, a nonlinear interdependence measure, and linear variability measures, respectively. We apply these tests to intracranial electroencephalographic recordings (EEG) from patients suffering from pharmacoresistant focal-onset epilepsy. These recordings had been performed prior to and independent from our study as part of the epilepsy diagnostics. The clinical purpose of these recordings was to delineate the brain areas to be surgically removed in each individual patient in order to achieve seizure control. This allowed us to define two distinct sets of signals: One set of signals recorded from brain areas where the first ictal EEG signal changes were detected as judged by expert visual inspection ("focal signals") and one set of signals recorded from brain areas that were not involved at seizure onset ("nonfocal signals"). We find more rejections for both the randomness and the nonlinear-independence test for focal versus nonfocal signals. In contrast more rejections of the stationarity test are found for nonfocal signals. Furthermore, while for nonfocal signals the rejection of the stationarity test increases the rejection probability of the randomness and nonlinear-independence test substantially, we find a much weaker influence for the focal signals. In consequence, the contrast between the focal and nonfocal signals obtained from the randomness and nonlinear-independence test is further enhanced when we exclude signals for which the stationarity test is rejected. To study the dependence between the randomness and nonlinear-independence test we include only focal signals for which the stationarity test is not rejected. We show that the rejection of these two tests correlates across signals. The rejection of either test is, however, neither necessary nor sufficient for the rejection of the other test. Thus, our results suggest that EEG signals from epileptogenic brain areas are less random, more nonlinear-dependent, and more stationary compared to signals recorded from nonepileptogenic brain areas. We provide the data, source code, and detailed results in the public domain.

Percutaneous endoscopic gastrostomy in children on peritoneal dialysis

OBJECTIVE: Insertion of percutaneous endoscopic gastrostomies (PEG) in patients on chronic peritoneal dialysis (PD) has been reported to be contraindicated due to an increased risk of morbidity and mortality. However, no systematic survey on this topic has yet been published. DESIGN: Retrospective multicenter study. SETTING: 23 pediatric dialysis units associated with the working group Arbeitsgemeinschaft für Pädiatrische Nephrologie (APN). DATA SOURCE: A structured questionnaire on clinical details of PD patients who had undergone PEG insertion or open gastrostomy (OG) since 1994 was distributed to all pediatric dialysis units of the APN. RESULTS: 27 PD patients (20 males) from 12 centers in whom PEG insertion was performed after Tenckhoff catheter introduction were evaluated. Age at intervention ranged from 0.25 to 10.9 years (median 1.3 years). Most patients were malnourished, with standard deviation score (SDS) for body weight between -4.2 and -0.6 (median -2.2). Major complications were early peritonitis < 7 days after PEG in 10/27 (37%) patients, episodes of fungal peritonitis in 7/27 (26%) patients, 4 cessations of PD and change to hemodialysis, and 2 associated deaths. However, in 14 patients, no such problems were encountered and, in 4 patients, early peritonitis effectively treated with intraperitoneal antibiotics was the only major complication. Thus, in 18/27 (67%) patients, PD was successfully reinitiated shortly after PEG insertion. Among all participating centers, only two OG procedures were reported during the study period, illustrating a clear preference for the PEG over the OG procedure among members of the APN. CONCLUSION: PEG insertion following PD initiation carries a high risk for fungal peritonitis and potential PD failure; however, complication rates in this largest reported series were lower than previously described. Antibiotic and antifungal prophylaxis, withholding PD for 2 - 3 days, and gastrostomy placement by an experienced endoscopy team are suggested precautions for lowering the risk of associated complications. When gastrostomy placement does not occur prior to or at the time of initiating PD, the risks and benefits of percutaneous versus open placement must be carefully weighed.

Observation errors in early historical upper-air observations

Upper-air observations are a fundamental data source for global atmospheric data products, but uncertainties, particularly in the early years, are not well known. Most of the early observations, which have now been digitized, are prone to a large variety of undocumented uncertainties (errors) that need to be quantified, e.g., for their assimilation in reanalysis projects. We apply a novel approach to estimate errors in upper-air temperature, geopotential height, and wind observations from the Comprehensive Historical Upper-Air Network for the time period from 1923 to 1966. We distinguish between random errors, biases, and a term that quantifies the representativity of the observations. The method is based on a comparison of neighboring observations and is hence independent of metadata, making it applicable to a wide scope of observational data sets. The estimated mean random errors for all observations within the study period are 1.5 K for air temperature, 1.3 hPa for pressure, 3.0 ms−1for wind speed, and 21.4° for wind direction. The estimates are compared to results of previous studies and analyzed with respect to their spatial and temporal variability.

Estimation of aortic pressure waveforms from 4D phase-contrast MRI

Several approaches for the non-invasive MRI-based measurement of the aortic pressure waveform over the heart cycle have been proposed in the last years. These methods are normally based on time-resolved, two-dimensional phase-contrast sequences with uni-directionally encoded velocities (2D PC-MRI). In contrast, three-dimensional acquisitions with tridirectional velocity encoding (4D PC-MRI) have been shown to be a suitable data source for detailed investigations of blood flow and spatial blood pressure maps. In order to avoid additional MR acquisitions, it would be advantageous if the aortic pressure waveform could also be computed from this particular form of MRI. Therefore, we propose an approach for the computation of the aortic pressure waveform which can be completely performed using 4D PC-MRI. After the application of a segmentation algorithm, the approach automatically computes the aortic pressure waveform without any manual steps. We show that our method agrees well with catheter measurements in an experimental phantom setup and produces physiologically realistic results in three healthy volunteers.