Immunology in COPD and the use of combustible cigarettes and heated tobacco products.

Chronic obstructive pulmonary disease (COPD) is one of the most common chronic respiratory diseases, characterised by high morbidity and mortality. COPD is characterised by a progressive decline of lung function caused by chronic inflammatory reactions in the lung tissue due to continual exposure to harmful molecules by inhalation. As prevention plays a very important role in COPD, quitting smoking is the most important factor in reducing the decline in lung function.

Serial echocardiographic evaluation of COVID-19 patients without prior history of structural heart disease: a 1-year follow-up CRACoV-HHS study.

Background: It is a well-known fact that COVID-19 affects the cardiovascular system by exacerbating heart failure in patients with preexisting conditions. However, there is a poor insight into the cardiovascular involvement and sequelae in patients without preexisting conditions. The aim of the study is to analyse the influence of COVID-19 on cardiac performance in patients without prior history of structural heart disease.

Association between clinical features and course of systemic sclerosis and serum interleukin-8, vascular endothelial growth factor, basic fibroblast growth factor, and interferon alpha.

Background: Certain mediators, such as soluble growth factors and cytokines, among others, are implicated in the immunopathogenesis of systemic sclerosis (SSc).

Objectives: This study aimed to examine the association between serum levels of vascular endothelial growth factor (VEGF), interleukin-8 (IL-8), interferon alpha (IFN-α), and basic fibroblast growth factor (bFGF) and the clinical presentation and course of SSc.

Material And Methods: This longitudinal, observational study included 43 patients with SSc and 24 healthy subjects.

Artificial intelligence guided HRCT assessment predicts the severity of COVID-19 pneumonia based on clinical parameters.

Background: The purpose of the study was to compare the results of AI (artificial intelligence) analysis of the extent of pulmonary lesions on HRCT (high resolution computed tomography) images in COVID-19 pneumonia, with clinical data including laboratory markers of inflammation, to verify whether AI HRCT assessment can predict the clinical severity of COVID-19 pneumonia.

Methods: The analyzed group consisted of 388 patients with COVID-19 pneumonia, with automatically analyzed HRCT parameters of volume: AIV (absolute inflammation), AGV (absolute ground glass), ACV (absolute consolidation), PIV (percentage inflammation), PGV (percentage ground glass), PCV (percentage consolidation). Clinical data included: age, sex, admission parameters: respiratory rate, oxygen saturation, CRP (C-reactive protein), IL6 (interleukin 6), IG - immature granulocytes, WBC (white blood count), neutrophil count, lymphocyte count, serum ferritin, LDH (lactate dehydrogenase), NIH (National Institute of Health) severity score; parameters of clinical course: in-hospital death, transfer to the ICU (intensive care unit), length of hospital stay.