Giant lung cavity due to three different pathogens in a patient receiving inhaled salmeterol plus fluticasone propionate for asthma.

INTRODUCTION: High-dose and long-term use of inhaled corticosteroids may cause systemic and local side effects such as opportunistic infections. Here we report a patient with asthma who developed a giant cavity in the lung while using inhaled salmeterol plus fluticasone propionate. CASE STUDY: A 57-year-old female patient presented with a three-week history of cough, hemoptysis, and dyspnea. She had a diagnosis of asthma for 4 years and was using an inhaled salmeterol plus fluticasone treatment intermittently for 2 years. A giant cavity was detected in the patient's chest X-ray. As a result of further investigations, three different microorganisms were isolated from the samples of sputum, bronchial lavage and lung biopsy. RESULTS: Staphylococcus aureus was the first microorganism that was isolated from the sputum and the bronchial lavage. Afterwards, Candida albicans was detected in both the bronchial lavage fluid and the histologic examination of the tissue samples obtained by percutaneous lung biopsy. Appropriate antibiotics and antifungals were prescribed. Moderate clinical and radiological response to the treatment was obtained. During the outpatient follow-up, Mycobacterium tuberculosis growth which was sensitive to all of the major anti-tuberculosis drugs was reported in the mycobacterial culture, and the patient was started on anti-tuberculosis treatment. CONCLUSION: Tuberculosis and other opportunistic infections are a potential consequences of inhaled corticosteroids. Clinicians overseeing such patients need to be vigilant about the need for timely investigations about tuberculosis before and during prescribing medications containing inhaled corticosteroids.

Deep learning for diagnosis of malign pleural effusion on computed tomography images.

BACKGROUND: The pleura is a serous membrane that surrounds the lungs. The visceral surface secretes fluid into the serous cavity and the parietal surface ensures a regular absorption of this fluid. If this balance is disturbed, fluid accumulation occurs in the pleural space called "Pleural Effusion". Today, accurate diagnosis of pleural diseases is becoming more critical, as advances in treatment protocols have contributed positively to prognosis. Our aim is to perform computer-aided numerical analysis of Computed Tomography (CT) images from patients showing pleural effusion images on CT and to examine the prediction of malignant/benign distinction using deep learning by comparing with the cytology results. METHODS: The authors classified 408 CT images from 64 patients whose etiology of pleural effusion was investigated using the deep learning method. 378 of the images were used for the training of the system; 15 malignant and 15 benign CT images, which were not included in the training group, were used as the test. RESULTS: Among the 30 test images evaluated in the system; 14 of 15 malignant patients and 13 of 15 benign patients were estimated with correct diagnosis (PPD: 93.3%, NPD: 86.67%, Sensitivity: 87.5%, Specificity: 92.86%). CONCLUSION: Advances in computer-aided diagnostic analysis of CT images and obtaining a pre-diagnosis of pleural fluid may reduce the need for interventional procedures by guiding physicians about which patients may have malignancies. Thus, it is cost and time-saving in patient management, allowing earlier diagnosis and treatment.

Perceived Need for Mental Health Services Among Healthcare Workers During the Coronavirus Disease-19 Pandemic in Turkey: A Multicenter Cross-sectional Study

Background: The coronavirus disease-2019 pandemic has contributed to work-related psychosocial risks in healthcare workers. Aims: To evaluate the perceived need for mental health services and related factors in Turkish healthcare workers practicing in pandemic hospitals. Study Design: Cross-sectional study. Methods: Data were collected from face-to-face interviews with healthcare workers at 19 pandemic hospitals in 13 provinces between September and November 2021. The study survey included the evaluation of the perceived need for and utilization of mental health services in the previous year, as well as sociodemographic, health-related, and work-related characteristics, the General Health Questionnaire-12, the World Health Organization Quality of Life-BREF (WHOQoL-BREF) questionnaire, and the Fear of coronavirus disease-2019 scale (FCV-19S). Results: Of 1,556 participants, 522 (33.5%) reported a perceived need for mental health services, but only 133 (8.5%) reported receiving these services. Multiple logistic regression analysis of the perceived need for mental health services revealed significant relationships with lower age, female sex, being a current smoker, having a chronic disease, having a mental disorder, coronavirus disease-2019 contact within the last three months in settings other than the home or workplace, a positive coronavirus disease-2019 vaccination history, being a physician, being a non-physician healthcare professional, and coronavirus disease-2019 contact within the last three months at work. After adjustment for these characteristics, higher General Health Questionnaire-12 and FCV-19S scores and lower WHOQoL-BREF domain scores were related to the perceived need for mental health services in logistic regression analyses. Conclusion: The findings indicate a substantial need for mental health services amongst Turkish healthcare workers during the pandemic and outline participants' characteristics regarding high-priority groups for the intervention. Future research may focus on developing actions and evaluating their efficiency.