Objective: Follow-up chest radiographs are frequently recommended by radiologists to document the clearing of radiographically suspected pneumonia. However, the clinical utility of follow-up radiography is not well understood. The purpose of this study was to examine the incidence of important pulmonary pathology revealed during follow-up imaging of suspected pneumonia on outpatient chest radiography.
Materials And Methods: Reports of 29,138 outpatient chest radiography examinations performed at an academic medical center in 2008 were searched to identify cases in which the radiologist recommended follow-up chest radiography for presumed community-acquired pneumonia (n = 618). Descriptions of index radiographic abnormalities were recorded. Reports of follow-up imaging (radiography and CT) performed during the period from January 2008 to January 2010 were reviewed to assess the outcome of the index abnormality. Clinical history, demographics, microbiology, and pathology reports were reviewed and recorded.
Results: Compliance with follow-up imaging recommendations was 76.7%. In nine of 618 cases (1.5%), a newly diagnosed malignancy corresponded to the abnormality on chest radiography initially suspected to be pneumonia. In 23 of 618 cases (3.7%), an alternative nonmalignant disease corresponded with the abnormality on chest radiography initially suspected to be pneumonia. Therefore, in 32 of 618 patients (5.2%), significant new pulmonary diagnoses were established during follow-up imaging of suspected pneumonia.
Conclusion: Follow-up imaging of radiographically suspected pneumonia leads to a small number of new diagnoses of malignancy and important nonmalignant diseases, which may alter patient management.
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http://dx.doi.org/10.2214/AJR.13.10888 | DOI Listing |
Georgian Med News
October 2024
6Clinical Nurse Specialist, Heart Hospital, Hamad Medical Corporation, Doha, Qatar.
The corona virus disease-19 (COVID-19) epidemic, the whole globe is suffering from a medical condition catastrophe that is unprecedented in scale. As the coronavirus spreads, scientists are worried about offering or helping in the supply of remedies to preserve lives and end the epidemic. Artificial intelligence (AI), for example, has occurred altered to deal with the difficulties raised by pandemics.
View Article and Find Full Text PDFInvest Radiol
October 2024
From the Department of Radiology and Nuclear Medicine, UKSH Lübeck, Lübeck, Germany (J.S., M.M., L.B., Y.E., J.B., M.M.S.); Institute of Medical Informatics, University of Lübeck, Lübeck, Germany (L.H., M.P.H.); Philips Research Hamburg, Hamburg, Germany (A.S., H.S.); and Institute of Interventional Radiology, UKSH Lübeck, Lübeck, Germany (M.M.S.).
Purpose: Accurate detection of central venous catheter (CVC) misplacement is crucial for patient safety and effective treatment. Existing artificial intelligence (AI) often grapple with the limitations of label inaccuracies and output interpretations that lack clinician-friendly comprehensibility. This study aims to introduce an approach that employs segmentation of support material and anatomy to enhance the precision and comprehensibility of CVC misplacement detection.
View Article and Find Full Text PDFCureus
November 2024
Internal Medicine/Pulmonary Critical Care, Appalachian Regional Healthcare, Harlan, USA.
Hodgkin's lymphoma (HL) is a malignancy of the lymphocytes in the lymph nodes and presents with non-specific systemic symptoms like fever, night sweats, and weight loss. While HL often involves the mediastinum, it rarely causes superior vena cava (SVC) syndrome, and eosinophilia is noted in approximately 15% of cases. Here, we report a unique presentation of HL in a 52-year-old male with a history of chronic pruritus, chronic kidney disease, and inactive hepatitis B.
View Article and Find Full Text PDFInfect Drug Resist
December 2024
Department of Intensive Care Medicine, Hunan University of Medicine General Hospital, Huaihua, Hunan Province, People's Republic of China.
Background: Our objective was to analyze the clinical and imaging features of pneumonia to enhance its diagnostic accuracy.
Methods: We systematically reviewed the cases of Chlamydia psittaci diagnosed by next-generation sequencing at the Hunan University of Medicine General Hospital between March 2019 and June 2024, summarizing and analyzing their clinical characteristics and imaging features.
Results: A total of 50 cases that met the inclusion criteria were ultimately included in the study analysis.
Chin Med J (Engl)
December 2024
State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers and National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi'an, Shaanxi 710032, China.
Large language models (LLMs) such as ChatGPT, Claude, Llama, and Qwen are emerging as transformative technologies for the diagnosis and treatment of various diseases. With their exceptional long-context reasoning capabilities, LLMs are proficient in clinically relevant tasks, particularly in medical text analysis and interactive dialogue. They can enhance diagnostic accuracy by processing vast amounts of patient data and medical literature and have demonstrated their utility in diagnosing common diseases and facilitating the identification of rare diseases by recognizing subtle patterns in symptoms and test results.
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