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http://dx.doi.org/10.1016/j.ajem.2011.04.015 | DOI Listing |
Ann Card Anaesth
January 2025
Department of Anaesthesiology, Lilavati Hospital and Research Centre, Mumbai, Maharashtra, India.
We report a case of a 74-year-old female with a retrosternal goiter undergoing video-assisted thoracic surgery (VATS) for a left lung lower lobectomy, necessitating one-lung ventilation (OLV). We encountered a highly unusual complication: contralateral tension pneumothorax. Forty-five minutes into the surgical procedure, a sudden cardiovascular collapse occurred.
View Article and Find Full Text PDFTrauma Surg Acute Care Open
January 2025
Trauma and Acute Care Surgery, Inova Health System, Falls Church, Virginia, USA.
BMJ Case Rep
January 2025
Department of Respiratory and Critical Care Medicine, The Eighth Affiliated Hospital of Sun Yat-Sen University, Shenzhen, China
Birt-Hogg-Dubé syndrome (BHDS) is a rare autosomal dominant genetic disorder. This case report aims to increase awareness of pulmonary cystic lesions and BHDS in China by providing insights into the clinical features of this syndrome. We present two cases of BHDS from the same family.
View Article and Find Full Text PDFTrauma Surg Acute Care Open
December 2024
Department of Surgery, Division of Trauma & Acute Care Surgery, Medical College of Wisconsin, Milwaukee, Wisconsin, USA.
Background: Bedside thoracic ultrasound (US) offers numerous advantages over chest X-ray (CXR) for identification of recurrent pneumothoraces (PTX) after tube thoracostomy (TT) removal. Technologic advancements have led to the development of hand-held devices capable of producing high-quality images termed ultra-portable US (UPUS). We hypothesized that UPUS would be as successful as CXR in detecting post-TT removal PTX and would be preferred by patients.
View Article and Find Full Text PDFIntroduction: A chest X-ray (CXR) is the most common imaging investigation performed worldwide. Advances in machine learning and computer vision technologies have led to the development of several artificial intelligence (AI) tools to detect abnormalities on CXRs, which may expand diagnostic support to a wider field of health professionals. There is a paucity of evidence on the impact of AI algorithms in assisting healthcare professionals (other than radiologists) who regularly review CXR images in their daily practice.
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