Chronic Obstructive Pulmonary Disease (COPD) is a chronic respiratory disease characterised by persistent respiratory symptoms and airflow limitation. COPD has a major impact on public health, mainly because of its increasing prevalence, morbidity and mortality. The natural course of COPD is aggravated by episodes of respiratory symptom worsening termed exacerbations that contribute to disease progression. Acute Exacerbations of COPD (AECOPD) can be triggered by a multitude of different factors, including respiratory tract infections, various exposures, prior exacerbations, non‐adherence to treatment and associated comorbidities. AECOPD are associated with an inexorable decline of lung function and a significantly worse survival outcome. This review will summarise the most important aspects regarding the impact of different factors that contribute to COPD exacerbations.

Breast cancer, affecting both genders, but mostly females, exhibits shifting demographic patterns, with an increasing incidence in younger age groups. Early identification through mammography, clinical examinations, and breast self-exams enhances treatment efficacy, but challenges persist in low- and medium-income countries due to limited imaging resources. This review assesses the feasibility of employing breast ultrasound as the primary breast cancer screening method, particularly in resource-constrained regions. Following the PRISMA guidelines, this study examines 52 publications from the last five years. Breast ultrasound, distinct from mammography, offers advantages like radiation-free imaging, suitability for repeated screenings, and preference for younger populations. Real-time imaging and dense breast tissue evaluation enhance sensitivity, accessibility, and cost-effectiveness. However, limitations include reduced specificity, operator dependence, and challenges in detecting microcalcifications. Automatic breast ultrasound (ABUS) addresses some issues but faces constraints like potential inaccuracies and limited microcalcification detection. The analysis underscores the need for a comprehensive approach to breast cancer screening, emphasizing international collaboration and addressing limitations, especially in resource-constrained settings. Despite advancements, notably with ABUS, the primary goal is to contribute insights for optimizing breast cancer screening globally, improving outcomes, and mitigating the impact of this debilitating disease.

Bronchoalveolar lavage (BAL), a noninvasive, well-tolerated procedure is an important diagnostic tool that can facilitate the diagnosis of various lung diseases. This procedure allows the assessmen...

Interstitial lung diseases are a diverse group of disorders that involve inflammation and fibrosis of interstitium, with clinical, radiological, and pathological overlapping features. These are an important cause of morbidity and mortality among lung diseases. This review describes computer-aided diagnosis systems centered on deep learning approaches that improve the diagnostic of interstitial lung diseases. We highlighted the challenges and the implementation of important daily practice, especially in the early diagnosis of idiopathic pulmonary fibrosis (IPF). Developing a convolutional neuronal network (CNN) that could be deployed on any computer station and be accessible to non-academic centers is the next frontier that needs to be crossed. In the future, early diagnosis of IPF should be possible. CNN might not only spare the human resources but also will reduce the costs spent on all the social and healthcare aspects of this deadly disease.Key Points• Deep learning algorithms are used in pattern recognition of different interstitial lung diseases.• High-resolution computed tomography plays a central role in the diagnosis and in the management of all interstitial lung diseases, especially fibrotic lung disease.• Developing an accessible algorithm that could be deployed on any computer station and be used in non-academic centers is the next frontier in the early diagnosis of idiopathic pulmonary fibrosis.

Universal COVID-19 immunization is seen as a critical approach for limiting the spread of SARS-CoV-2 and reducing the danger of new variations emerging in the general population, especially in pregnant women. The literature and accessible research data indicate that vaccination intentions vary greatly by country, with Romania ranking among the European nations with the lowest vaccination rates. Thus, we aimed to investigate the prevalence and extent of COVID-19 vaccine hesitancy among pregnant women in Romania and the factors influencing their decision. A cross-sectional study was conducted on pregnant women referred to the Obstetrics and Gynecology Clinic of the Timisoara Municipal Emergency Hospital in Romania. Participants were asked to complete the validated VAX scale about vaccine hesitancy and to report their willingness to receive a COVID-19 vaccine and their reasons for hesitancy. The group of 184 pregnant women who completed the survey recorded significantly more hesitant respondents than the non-pregnant group with 161 respondents (52.2% vs. 40.3%). They had significantly higher average scores in all VAX scale subsections, while 78.1% of them gave credits to social media for their COVID-19 vaccination decision, compared with 63.0% of non-pregnant women. The independent risk factors for hesitancy were determined as not being afraid of COVID-19 OR = 1.89, below-average income OR = 2.06, trusting social media rumors OR = 2.38, not believing in SARS-CoV-2 existence OR = 2.67, and being a vaccination non-believer OR = 3.15. We advocate for pregnant women to get vaccinated against COVID-19 and for the development of targeted campaigns to address the factors of hesitation. This research emphasizes the critical need for delivering the COVID-19 immunization to the whole community, including pregnant women who may have vaccine-related concerns.

CT-guided transthoracic core-needle biopsy (CT-TTNB) is a minimally invasive procedure that plays a crucial role in diagnosing pulmonary nodules. With high diagnostic yield and low complication rates, CT-TTNB is favored over traditional surgical biopsies, providing accuracy in detecting both malignant and benign conditions. This literature review aims to present a comprehensive overview of CT-TTNB, focusing on its indications, procedural techniques, diagnostic yield, and safety considerations. Studies published between 2013 and 2024 were systematically reviewed from PubMed, Web of Science, Scopus, and Cochrane Library using the SANRA methodology. The results highlight that CT-TTNB has a diagnostic yield of 85–95% and sensitivity rates for detecting malignancies between 92 and 97%. Several factors, including nodule size, lesion depth, needle passes, and imaging techniques, influence diagnostic success. Complications such as pneumothorax and pulmonary hemorrhage were noted, with incidence rates varying from 12 to 45% for pneumothorax and 4 to 27% for hemorrhage. Preventative strategies and management algorithms are essential for minimizing and addressing these risks. In conclusion, CT-TTNB remains a reliable and effective method for diagnosing pulmonary nodules, particularly in peripheral lung lesions. Advancements such as PET/CT fusion imaging, AI-assisted biopsy planning, and robotic systems further enhance precision and safety. This review emphasizes the importance of careful patient selection and procedural planning to maximize outcomes while minimizing risks, ensuring that CT-TTNB continues to be an indispensable tool in pulmonary diagnostics.