Feasibility of Mouth-to-Mouth Ventilation through FPP2 Respirator in BLS Training during COVID-19 Pandemic (MOVERESP Study): Simulation-Based Study.

BACKGROUND: Due to the COVID-19 pandemic, Basic Life Support (BLS) training has been limited to compression-only or bag-mask ventilation. The most breathable nanofiber respirators carry the technical possibility for inflation of the mannequin. The aim of this study was to assess the efficacy of mouth-to-mouth breathing through a FFP2 respirator during BLS. METHODS: In the cross-over simulation-based study, the medical students performed BLS using a breathable nanofiber respirator for 2 min on three mannequins. The quantitative and qualitative efficacy of mouth-to-mouth ventilation through the respirator in BLS training was analyzed. The primary aim was the effectivity of mouth-to-mouth ventilation through a breathable respirator. The secondary aims were mean pause, longest pause, success in achieving the optimal breath volume, technique of ventilation, and incidence of adverse events. RESULTS: In 104 students, effective breath was reached in 951 of 981 (96.9%) attempts in Adult BLS mannequin (Prestan), 822 of 906 (90.7%) in Resusci Anne, and 1777 of 1857 (95.7%) in Resusci Baby. In Resusci Anne and Resusci Baby, 28.9%/15.9% of visible chest rises were evaluated as low-, 33.0%/44.0% as optimal-, and 28.8%/35.8% as high-volume breaths. CONCLUSIONS: Mouth-to-mouth ventilation through a breathable respirator had an effectivity greater than 90%.

Comparative analysis of wavelet transform filtering systems for noise reduction in ultrasound images.

Wavelet transform (WT) is a commonly used method for noise suppression and feature extraction from biomedical images. The selection of WT system settings significantly affects the efficiency of denoising procedure. This comparative study analyzed the efficacy of the proposed WT system on real 292 ultrasound images from several areas of interest. The study investigates the performance of the system for different scaling functions of two basic wavelet bases, Daubechies and Symlets, and their efficiency on images artificially corrupted by three kinds of noise. To evaluate our extensive analysis, we used objective metrics, namely structural similarity index (SSIM), correlation coefficient, mean squared error (MSE), peak signal-to-noise ratio (PSNR) and universal image quality index (Q-index). Moreover, this study includes clinical insights on selected filtration outcomes provided by clinical experts. The results show that the efficiency of the filtration strongly depends on the specific wavelet system setting, type of ultrasound data, and the noise present. The findings presented may provide a useful guideline for researchers, software developers, and clinical professionals to obtain high quality images.

Noninvasive Continuous Blood Pressure Estimation From Pulse Transit Time: A Review of the Calibration Models.

Noninvasive continuous blood pressure estimation is a promising alternative to minimally invasive blood pressure measurement using cuff and invasive catheter measurement, because it opens the way to both long-term and continuous blood pressure monitoring in ecological situation. The most current estimation algorithm is based on pulse transit time measurement where at least two measured signals need to be acquired. From the pulse transit time values, it is possible to estimate the continuous blood pressure for each cardiac cycle. This measurement highly depends on arterial properties which are not easily accessible with common measurement techniques; but these properties are needed as input for the estimation algorithm. With every change of input arterial properties, the error in the blood pressure estimation rises, thus a periodic calibration procedure is needed for error minimization. Recent research is focused on simplified constant arterial properties which are not constant over time and uses only linear model based on initial measurement. The elaboration of continuous calibration procedures, independent of recalibration measurement, is the key to improving the accuracy and robustness of noninvasive continuous blood pressure estimation. However, most models in literature are based on linear approximation and we discuss here the need for more complete calibration models.