Infective endocarditis (IE) is a serious and potentially lethal condition. The diagnostic capacity of the modified Duke criteria is high for native valves, but it declines in the case of EI of prosthetic valves or EI associated with devices. Echocardiography and microbiological findings are essential for diagnosis but may be insufficient in this group of patients. Our objective was to evaluate the usefulness of positron emission tomography and fusion with computed tomography (PET / CT) in patients with suspected IE, carriers of prosthetic valves or intracardiac devices; 32 patients were studied, who underwent PET / CT with 18F-Fluorine deoxyglucose (18F-FDG). Those with intense focal and/or heterogeneous uptake with a Standard Uptake Value SUV) cut-off point greater than or equal to 3.7 were considered suggestive of infection. The initial diagnoses according to the modified Duke criteria were compared with the final diagnosis established by the Institutional Endocarditis Unit. The addition of PET / CT to these criteria, provided a conclusive diagnosis in 22 of the 32 initial cases reclassifying 11 cases in definitive EI; another 5 cases were negative for that diagnosis. EI continues to be a serious clinical problem. In those cases where the Duke criteria are not sufficient to establish the diagnosis and clinical suspicion persists, PET / CT can be a useful complementary tool to increase the diagnostic sensitivity.
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Orthop J Sports Med
January 2025
Department of Orthopaedic Surgery, Carthage Area Hospital, Carthage, New York, USA.
Background: While glenoid bone loss (GBL) after anterior shoulder instability correlates with poor functional outcomes, the specific effects of GBL in posterior and combined-type shoulder instability remain poorly characterized, especially in a high-risk military population.
Purpose/hypothesis: The purpose of this study was to compare GBL between unidirectional anterior or posterior instability versus combined-type instability in active-duty servicemembers. It was hypothesized that total GBL and GBL in the direction of instability would be greater in those with combined-type instability compared with unidirectional instability.
BMC Health Serv Res
January 2025
Department of Veterans Affairs Office of Patient Centered Care & Cultural Transformation, 810 Vermont Avenue NW, Washington D.C., 20420, USA.
Background: Physician well-being and workforce retention within the healthcare system is of critical importance. Understanding physicians' intent to leave the organization will inform efforts on optimizing the physician workforce. In this study, we examine the association of burnout and specific drivers of burnout on turnover intentions.
View Article and Find Full Text PDFJ Am Geriatr Soc
January 2025
Geriatric Research, Education and Clinical Center, James J. Peters VA Medical Center, Bronx, New York, USA.
Background: Existing risk scores assessing geriatric vulnerability in the emergency department (ED) have shown limited predictive power, especially in diverse populations. We investigated the relationship of a quick and easy-to-administer geriatric vulnerability scoring system with functional decline and mortality in older patients admitted to multiple hospitals through the ED in the United States (US) and Brazil (BR).
Method: Federated, international, multicenter observational study of hospitalized ED patients aged ≥ 65 from US and BR.
Sci Adv
January 2025
State Key Laboratory of Environment Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China.
Human health is being threatened by environmental microplastic (MP) pollution. MPs were detected in the bloodstream and multiple tissues of humans, disrupting the regular physiological processes of organs. Nanoscale plastics can breach the blood-brain barrier, leading to neurotoxic effects.
View Article and Find Full Text PDFInj Prev
January 2025
Department of Orthopaedic Surgery, Duke University, Durham, North Carolina, USA
Introduction: Return-to-acute-care metrics, such as early emergency department (ED) visits, are key indicators of healthcare quality, with ED returns following surgery often considered avoidable and costly events. Proactively identifying patients at high risk of ED return can support quality improvement efforts, allowing interventions to target vulnerable patients. With its predictive capabilities, machine learning (ML) has shown potential in forecasting various clinical outcomes but remains underutilised in orthopaedic trauma.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!