Purpose: Growing numbers of patient with advanced imaging being transferred to trauma centers has resulted in increased numbers of outside CT scans received at trauma centers. This study examines the degree of agreement between community radiologists' interpretations of the CT scans of transferred patients and trauma center radiologists' reinterpretation.
Methods: All CT scans of emergency transfer patients received over a 1 month period were reviewed by an emergency radiologist. Patients were classified as trauma or non-trauma and exams as neuro or non-neuro. Interpretive discrepancies between the emergency radiologist and community radiologist were classified as minor, moderate, or major. Major discrepancies were confirmed by review of a second emergency radiologist. Discrepancy rates were calculated on a per-patient and per exam basis.
Results: Six hundred twenty-seven CT scans of 326 patients were reviewed. Major discrepancies were encountered in 52 (16.0%, 95% CI 12.2-20.5) patients and 53 exams (8.5%, 95% CI 6.5-10.5). These were discovered in 46 trauma patients (21.6%, 95% CI 16.4-27.9) compared to six non-trauma patients (5.3%, 95% CI 2.2-11.7) (P < 0.001). A significant difference in the major discrepancy rate was also found between non-neuro and neuro exams (12.4 vs 3.3%, respectively, P < 0.001), primarily due to discrepancies in trauma patients, rather than non-trauma patients.
Conclusions: Potentially management-changing interpretive changes affected 16% of transferred patients and 8.5% of CT exams over a 1 month period. Trauma center reinterpretations of community hospital CT scans of transferred patients provide valuable additional information to the clinical services caring for critically ill patients.
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http://dx.doi.org/10.1007/s10140-017-1573-8 | DOI Listing |
Emerg Radiol
January 2025
Department of Ultrasound, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, Shenzhen, China.
Purpose: Acute abdominal aortic dissection (AD) is a serious disease. Early detection based on ultrasound (US) can improve the prognosis of AD, especially in emergency settings. We explored the ability of deep learning (DL) to diagnose abdominal AD in US images, which may help the diagnosis of AD by novice radiologists or non-professionals.
View Article and Find Full Text PDFCureus
December 2024
First and Emergency Aid, Istanbul Şişli Meslek Yüksekokulu, Istanbul, TUR.
Dr. Esad Feyzi was a pioneering physician who lived in the 19th-century Ottoman Empire and made significant contributions to the field of medicine. Despite passing away at the young age of 28, he achieved notable scientific advancements during his lifetime.
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.
View Article and Find Full Text PDFInsights Imaging
January 2025
Department of Radiology, Charité - Universitätsmedizin Berlin, Freie Universität Berlin and Humboldt- Universität zu Berlin, Charitéplatz 1, Berlin, Germany.
Objectives: To survey physicians' views on the risks and benefits of computed tomography (CT) in the management of septic patients and indications for and contraindications to contrast media use in searching for septic foci.
Methods: A web-based questionnaire was administered to physicians at a large European university medical center in January 2022. A total of 371 questionnaires met the inclusion criteria and were analyzed with physicians' work experience, workplace, and medical specialty as independent variables.
Cureus
December 2024
Radiology, Michigan State University, East Lansing, USA.
Introduction In the emergency department (ED), COVID-19 and influenza are two common viral diseases. They cause similar symptoms in the respiratory system, and most patients' symptoms are relatively mild. We have reported previously that COVID-19 and influenza infections cause similar abnormalities in chest X-ray readings in the ED.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!