Search

Background: The COVID-19 pandemic, which affected the entire global population, had an impact on our health and quality of life. Many people had complications, were hospitalised or even died due to SARS-CoV-2 infection. The health systems of many countries had to radically change their way of functioning and scientists around the world worked intensively to develop a vaccine for the SARS-CoV-2 virus. Aim: The aim of this work is to assess the quality of life of patients who were hospitalised for COVID-19, using the SF-36 questionnaire. Methods: Between May and August 2022, we conducted a telephone assessment of quality of life in patients who were hospitalised for COVID-19 at the Temporary Hospital in Pyrzowice (Silesia, Poland), between November 2021 and January 2022. Results: Quality of life was significantly lower in women (p = 0.040), those with DM2 (p = 0.013), CKD (p = 0.041) and the vaccinated (p = 0.015). Conclusions: People with chronic kidney disease, diabetes mellitus and women had a lower quality of life after COVID-19 disease. However, people who were vaccinated for SARS-CoV-2 had a lower quality of life than non-vaccinated people did. This is possibly due to the higher mean age, and probably the higher disease burden, in the vaccinated group. [ABSTRACT FROM AUTHOR]

Drug-eluting stents (DES) demonstrated superior efficacy when compared to bare metal stents and plain-old balloon angioplasty and are nowadays used in almost all percutaneous revascularization procedures. The design of the stent platforms is constantly improving to maximize its efficacy and safety. Constant development of DES includes adoption of new materials used for scaffold production, new design types, improved overexpansion abilities, new polymers coating and, finally, improved antiproliferative agents. Especially nowadays, with the immense number of available DES platforms, it is crucial to understand how different aspects of stents impact the effect of their implantation, as subtle differences between various stent platforms could impact the most important issue—clinical outcomes. This review discusses the current status of coronary stents and the impact of stent material, strut design and coating techniques on cardiovascular outcomes. [ABSTRACT FROM AUTHOR]

Diagnostic imaging has become an integral part of the healthcare system. In recent years, scientists around the world have been working on artificial intelligence-based tools that help in achieving better and faster diagnoses. Their accuracy is crucial for successful treatment, especially for imaging diagnostics. This study used a deep convolutional neural network to detect four categories of objects on digital chest X-ray images. The data were obtained from the publicly available National Institutes of Health (NIH) Chest X-ray (CXR) Dataset. In total, 112,120 CXRs from 30,805 patients were manually checked for foreign objects: vascular port, shoulder endoprosthesis, necklace, and implantable cardioverter-defibrillator (ICD). Then, they were annotated with the use of a computer program, and the necessary image preprocessing was performed, such as resizing, normalization, and cropping. The object detection model was trained using the You Only Look Once v8 architecture and the Ultralytics framework. The results showed not only that the obtained average precision of foreign object detection on the CXR was 0.815 but also that the model can be useful in detecting foreign objects on the CXR images. Models of this type may be used as a tool for specialists, in particular, with the growing popularity of radiology comes an increasing workload. We are optimistic that it could accelerate and facilitate the work to provide a faster diagnosis. [ABSTRACT FROM AUTHOR]

Machine learning (ML), artificial neural networks (ANNs), and deep learning (DL) are all topics that fall under the heading of artificial intelligence (AI) and have gained popularity in recent years. ML involves the application of algorithms to automate decision-making processes using models that have not been manually programmed but have been trained on data. ANNs that are a part of ML aim to simulate the structure and function of the human brain. DL, on the other hand, uses multiple layers of interconnected neurons. This enables the processing and analysis of large and complex databases. In medicine, these techniques are being introduced to improve the speed and efficiency of disease diagnosis and treatment. Each of the AI techniques presented in the paper is supported with an example of a possible medical application. Given the rapid development of technology, the use of AI in medicine shows promising results in the context of patient care. It is particularly important to keep a close eye on this issue and conduct further research in order to fully explore the potential of ML, ANNs, and DL, and bring further applications into clinical use in the future. [ABSTRACT FROM AUTHOR]

Introduction The problem of theatre personnel being exposed to substances produced during electrosurgery has only recently started to be taken into consideration. This problem is particularly significant for personnel operating on patients with massive burns, since the optimal procedure for treating massive and deep burns is the early removal of tissue necrosis. For this purpose i.a. electrosurgery is used. The use of such instruments generates high temperature and increases exposure to harmful volatile agents in the smoke discharged from the tissues that are being removed. Aim of the study was qualitative and semi-quantitative analysis of non-polar volatile compounds released during burned tissue excision using cutting diathermy. Materials and methods The study was conducted during resection of patient's burned tissue on the first day after the burn (30% TBSA, depth third degree). The analyzed compounds were being absorbed by solid state extraction, using SPME fibers. Exposure time of the fibers was 30 minutes and began with the start of the procedure. The fibers were analyzed by gas chromatography coupled with mass spectrometry. Results In our pilot studies which employed SPME technique to test surgical smoke composition, we have demonstrated the presence of several hundred of non-polar organic compounds. They were identified as simple aliphatic and aromatic hydrocarbons, such as acid ester, hexane, acetone and complex organic derivatives of unknown toxicology. The analysis has also shown the presence of anesthetic gas - sevoflurane. Conclusions The current tests of electrosurgical smoke and fumes have been connected with the resection of healthy tissue. Our research, for the first time, shows the analysis of smoke resulting from the burned tissue resection. The majority of detected compounds has a potentially toxic effect and may constitute risk factors for the theatre personnel, that had not been previously taken into account. [ABSTRACT FROM AUTHOR]