The impact of the COVID-19 pandemic on the number of brain tumor surgeries in Poland: A national database study.

BACKGROUND: The coronavirus disease (COVID-19) pandemic has greatly affected the treatment of most medical conditions. In particular, the treatment of seriously ill patients had to be adjusted due to the limited availability of in-hospital procedures. OBJECTIVES: The aim of this study was to evaluate the effects of COVID-19-related changes on neuro-oncological surgeries in the Polish medical system. MATERIAL AND METHODS: Data from the period of 2010-2020 were collected from National Health Insurance database for 2 diagnosis-related groups: A11 (complex intracranial procedures) and A12 (large intracranial procedures). The total number of procedures and diagnoses per year, trend changes and changes in procedures grouped by medical type were analyzed, including resections/biopsies, malignant/stable (nonmalignant) lesions, elective/acute procedures, and length of stay. RESULTS: Mean yearly numbers of 7177 (standard deviation (SD) = 760) procedures and 5934 (SD = 1185) diagnoses were recorded. Both numbers were growing up to 9.1% per year until 2018. From 2018, a 3.1% decrease in the number of procedures was observed, with a significantly larger decrease of 10.5% observed in 2020 (p < 0.001). The number of diagnoses decreased in 2019 by 2.7%, and by 9.2% in 2020 (p = 0.706), with a statistically significant change in the annual growth rate (p = 0.044). The number of resections decreased by 11.5% in 2020 (p = 0.204), with a significant change in the annual growth rate (p < 0.001). The number of biopsies decreased by 2.5% in 2020 (p = 0.018), with the annual decrement in 2019/2020 also being significant (p = 0.004). Decreases were observed in 2019 and 2020 for the number of malignant (0.5% and 6.3%, respectively) and nonmalignant (5.4% and 12.9%, respectively) tumors (p = 0.233 and p = 0.682 for absolute values, and p = 0.008 and p = 0.004 for the annual growth rates, respectively). The number of acute procedures in 2020 further decreased by 9.8% from 5.5% decrease in 2019 (p = 0.004), and the number of elective procedures decreased by 11.8% (p = 0.009). The annual growth rates for both acute and elective procedures were statistically significant (p < 0.001 and p < 0.001). CONCLUSIONS: The decrease in the number of neuro-oncological surgeries appeared to be much lower than the 20% decrease observed for general oncological surgeries in Poland during the COVID-19 pandemic. This seems to have resulted from postponing the treatment of less critical cases (i.e., nonmalignant and elective) and focusing on the treatment of the most precarious patients.

High-frequency changes in single-trial visual evoked potentials for unattended stimuli in chronic schizophrenia.

BACKGROUND: Patients with schizophrenia reveal changes in information processing associated with external stimuli, which is reflected in the measurements of brain evoked potentials. We discuss actual knowledge on electro- (EEG) and magnetoencephalographic (MEG) changes in schizophrenia. NEW METHOD: The commonly used averaging technique entails the loss of information regarding the generation of evoked responses. We propose a methodology to describe single-trial (non-averaged) visual evoked potentials (VEP) using spectral and statistical analyses. We analysed EEG data registered in the O1-Cz and O2-Cz leads during unattended pattern-reversal stimulation, collected from a group of adult patients with chronic schizophrenia, and compared them to those of healthy individuals. Short-time single-trial VEP were transformed to the frequency domain using the FFT algorithm. Changes of the spectral power were visualized using spectrograms which were created by stacking single-trial spectra across all trials. Measures of the absolute and the relative spectral power were calculated and compared statistically. RESULTS: In schizophrenia, the energy density of VEP oscillations is shifted towards higher (gamma) frequencies, compared to healthy individuals. These differences are statistically significant in all analysed frequency bands for the relative power. This indicates distorted early processing of visual stimuli in schizophrenia. COMPARISON WITH EXISTING METHODS: The main advantage of the presented methodology is its simplicity and ease of interpretation of obtained results. The presented observations complement the knowledge on gamma oscillations acquired from computationally more complex methods of time-frequency analysis. CONCLUSIONS: High-frequency changes for single-trial VEPs are detected in chronic schizophrenia.

Acute Stroke Care during COVID-19: National Data.

(1) Background: The pandemic of COVID-19 and subsequent lockdown strategies had a profound impact on many aspects of everyday life. During this time the world faced the unprecedented crisis of healthcare disrupting timely care delivery. This study was designed to evaluate the impact of the pandemic on the acute treatment of stroke in Poland. (2) Methods: The national data on hospitalizations with stroke as a primary diagnosis were obtained from the National Health Fund of Poland. Poisson regression was used to determine the significance of the change in hospital admissions. The differences between proportions were analyzed using the "N-1" Chi-squared test. (3) Results: During the COVID-19 period, the number of hospitalizations dropped by 8.28% with a monthly nadir of 22.02 in April. On a monthly scale during 2020, the greatest decrease was 22.02%. The thrombolysis ratio was also affected, with the highest monthly drop of 15.51% in November. The overall number of in-hospital deaths did not change. (4) Conclusions: The pandemic caused a serious disruption of the acute care of stroke. There is no evidence that the quality of care was seriously compromised.

Time-series analysis of trial-to-trial variability of MEG power spectrum during rest state, unattended listening, and frequency-modulated tones classification.

BACKGROUND: The nonstationarity of EEG/MEG signals is important for understanding the functioning of the human brain. From our previous research we know that short, 250-500-ms MEG signals are variance-nonstationary. The covariance of a stochastic process is mathematically associated with its spectral density, therefore we investigate how the spectrum of such nonstationary signals varies in time. NEW METHOD: We analyse data from 148-channel MEG, which represent rest state, unattended listening, and frequency-modulated tones classification. We transform short-time MEG signals to the frequency domain and for the dominant frequencies of 8-12 Hz we prepare the time series representing their trial-to-trial variability. Then, we test them for level- and trend-stationarity, unit root, heteroscedasticity, and gaussianity, and propose ARMA-modelling for their description. RESULTS: The analysed time series have weak-stationarity properties independently of the functional state of the brain and channel localization. Only a small percentage of them, mostly related to the cognitive task, reveal nonstationarity. The obtained mathematical models show that the spectral density of the analysed signals depends on only two to three previous trials. COMPARISON WITH EXISTING METHODS: The presented method has limitations related to FFT resolution and univariate models, but it is computationally simple and allows obtaining a low-complex stochastic model of the EEG/MEG spectrum variability. CONCLUSIONS: Although physiological short-time MEG signals are in principle nonstationary in time, their power spectrum at the dominant (alpha) frequencies varies as a weakly stationary process. The proposed methodology has possible applications in prediction of EEG/MEG spectral properties in theoretical and clinical neuroscience.

The Usefulness of Quantitative EEG and Advanced MR Techniques in the Monitoring and Long-Term Prognosis of Lance-Adams Syndrome.

Objectives: Chronic post-hypoxic myoclonus, known as Lance-Adams syndrome (LAS), is a rare complication of successful cardiopulmonary resuscitation. It is characterized by intention myoclonus, cerebellar ataxia, and preserved intellect. The basis of the disease and its long-term prognosis remain unclear. Case report: The authors present a 53-year-old woman with a history of asthma bronchiale who suffered from myoclonus after hypoxic brain damage due to cardiac arrest. Advanced electrophysiological (quantitative EEG) and MR (MR spectroscopy) techniques were employed. Conclusions: Over long-term observation the results suggested permanent synaptic rearrangements of the neuronal networks due to brain plasticity in the patient after the brain hypoxia.

Hearing Tests on Mobile Devices: Evaluation of the Reference Sound Level by Means of Biological Calibration.

BACKGROUND: Hearing tests carried out in home setting by means of mobile devices require previous calibration of the reference sound level. Mobile devices with bundled headphones create a possibility of applying the predefined level for a particular model as an alternative to calibrating each device separately. OBJECTIVE: The objective of this study was to determine the reference sound level for sets composed of a mobile device and bundled headphones. METHODS: Reference sound levels for Android-based mobile devices were determined using an open access mobile phone app by means of biological calibration, that is, in relation to the normal-hearing threshold. The examinations were conducted in 2 groups: an uncontrolled and a controlled one. In the uncontrolled group, the fully automated self-measurements were carried out in home conditions by 18- to 35-year-old subjects, without prior hearing problems, recruited online. Calibration was conducted as a preliminary step in preparation for further examination. In the controlled group, audiologist-assisted examinations were performed in a sound booth, on normal-hearing subjects verified through pure-tone audiometry, recruited offline from among the workers and patients of the clinic. In both the groups, the reference sound levels were determined on a subject's mobile device using the Bekesy audiometry. The reference sound levels were compared between the groups. Intramodel and intermodel analyses were carried out as well. RESULTS: In the uncontrolled group, 8988 calibrations were conducted on 8620 different devices representing 2040 models. In the controlled group, 158 calibrations (test and retest) were conducted on 79 devices representing 50 models. Result analysis was performed for 10 most frequently used models in both the groups. The difference in reference sound levels between uncontrolled and controlled groups was 1.50 dB (SD 4.42). The mean SD of the reference sound level determined for devices within the same model was 4.03 dB (95% CI 3.93-4.11). Statistically significant differences were found across models. CONCLUSIONS: Reference sound levels determined in the uncontrolled group are comparable to the values obtained in the controlled group. This validates the use of biological calibration in the uncontrolled group for determining the predefined reference sound level for new devices. Moreover, due to a relatively small deviation of the reference sound level for devices of the same model, it is feasible to conduct hearing screening on devices calibrated with the predefined reference sound level.

Stationarity stopping criterion for matching pursuit-framework and encephalographic illustration.

We present a new stopping criterion for the matching pursuit (MP) algorithm, based on evaluating stationarity of the residua of the consecutive MP iterations. The new stopping criterion is based on a model of a nonstationary signal, which assumes that the part of the signal that is of interest is nonstationary and contaminated by a weakly stationary noise. Mean- and variance-stationarity of the residua obtained from each step of MP is evaluated by means of dedicated statistical tests-the Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test and the White test, respectively. We illustrate the proposed concept by an example in which we analyse magnetoencephalographic (MEG) data.

Application of modern tests for stationarity to single-trial MEG data: transferring powerful statistical tools from econometrics to neuroscience.

Stationarity is a crucial yet rarely questioned assumption in the analysis of time series of magneto- (MEG) or electroencephalography (EEG). One key drawback of the commonly used tests for stationarity of encephalographic time series is the fact that conclusions on stationarity are only indirectly inferred either from the Gaussianity (e.g. the Shapiro-Wilk test or Kolmogorov-Smirnov test) or the randomness of the time series and the absence of trend using very simple time-series models (e.g. the sign and trend tests by Bendat and Piersol). We present a novel approach to the analysis of the stationarity of MEG and EEG time series by applying modern statistical methods which were specifically developed in econometrics to verify the hypothesis that a time series is stationary. We report our findings of the application of three different tests of stationarity--the Kwiatkowski-Phillips-Schmidt-Schin (KPSS) test for trend or mean stationarity, the Phillips-Perron (PP) test for the presence of a unit root and the White test for homoscedasticity--on an illustrative set of MEG data. For five stimulation sessions, we found already for short epochs of duration of 250 and 500 ms that, although the majority of the studied epochs of single MEG trials were usually mean-stationary (KPSS test and PP test), they were classified as nonstationary due to their heteroscedasticity (White test). We also observed that the presence of external auditory stimulation did not significantly affect the findings regarding the stationarity of the data. We conclude that the combination of these tests allows a refined analysis of the stationarity of MEG and EEG time series.