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Risk of endocarditis in patients with bacteraemia by coagulase-negative staphylococci; a multicenter retrospective
Virgile Zimmermann1, Nicolas Fourré1, Bruno Ledergerber2
1Infectious Diseases Service, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
Background:
Infective endocarditis (IE) is a serious and under-recognized complication of coagulase-negative staphylococci (CoNS) bacteraemia. The aim was to identify predictors of IE in patients with CoNS bacteraemia and to compare the diagnostic performance of different Duke criteria versions.
Methods:
We retrospectively included adult patients with CoNS bacteraemia (January 2015-June 2024) from two Swiss university hospitals. Each episode was classified according to the 2015 European Society of Cardiology (ESC), 2023 ESC, and 2023 International Society of Cardiovascular Infectious Diseases (ISCVID) Duke criteria. IE diagnoses were established by the Endocarditis Teams or expert clinicians.
Results:
Among 466 episodes, Staphylococcus epidermidis was the most frequent pathogen (360; 77 %), followed by S. lugdunensis (47; 10 %). IE was diagnosed in 106 (23 %) episodes. Multivariable logistic regression identified non-nosocomial acquisition (aOR 6.43; 95 % CI 2.97-13.9), presence of intracardiac prosthetic material (15.4; 6.77-34.8), sepsis (2.34; 1.10-5.00), S. lugdunensis (2.99; 1.06-8.43), persistent bacteraemia for ≥48 h (6.88; 3.14-15.1), and embolic events (58.3; 21.2-160.5) as predictors of IE. The 2023 Duke-ISCVID criteria demonstrated the highest sensitivity (76 %) but lower specificity (61 %) than the 2015 Duke-ESC (sensitivity 21 %, specificity 98 %) and 2023 Duke-ESC (sensitivity 25 %, specificity 96 %) criteria.
Conclusions:
In episodes with CoNS bacteraemia, IE should be strongly suspected in those with persistent bacteraemia, prosthetic intracardiac material, non-nosocomial onset, S. lugdunensis bacteraemia, embolic complications. While the 2023 ISCVID criteria improve sensitivity, their lower specificity highlights the need for further refinement of diagnostic algorithms.
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