Clinical predictors and clinical prediction rules to estimate initial patient risk for infective endocarditis in Staphylococcus aureus bacteraemia: a systematic review and meta-analysis

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Abstract

Objectives We conducted a meta-analysis to summarize diagnostic properties of risk factors and clinical prediction rules for diagnosing infective endocarditis (IE) in Staphylococcus aureus bacteraemia (SAB). Methods We searched MEDLINE, Embase, and the Cochrane Database from inception to 6 January 2016 to identify studies evaluating risk factors and clinical prediction rules for IE in SAB patients. Pooled estimates of diagnostic properties for main risk factors were calculated using a bivariate random effects model. Results Of 962 articles identified, 30 studies were included. These involved 16 538 SAB patients including 1572 IE cases. Risk factors with positive likelihood ratio (PLR) greater than 5 included embolic events (PLR 12.7, 95% CI 9.2–17.7), pacemakers (PLR 9.7, 95% CI 3.7–21.2), history of previous IE (PLR 8.2, 95% CI 3.1–22.0), prosthetic valves (PLR 5.7, 95% CI 3.2–9.5), and intravenous drug use (PLR 5.2, 95% CI 3.8–6.9). The only clinical factor with negative likelihood ratio (NLR) less than 0.5 was documented clearance of bacteraemia within 72 hours (NLR range 0.32–0.35). Of the nine published clinical prediction rules for ruling out IE, five had an NLR below 0.1. Conclusions SAB patients with high-risk features (embolic events, pacemakers, prosthetic valves, previous IE, or intravenous drug use) should undergo a trans-esophageal echocardiography (TEE) for IE. Clinical prediction rules show promise in safely ruling out endocarditis, but require validation in future studies.

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Bai, A. D., Agarwal, A., Steinberg, M., Showler, A., Burry, L., Tomlinson, G. A., … Morris, A. M. (2017, December 1). Clinical predictors and clinical prediction rules to estimate initial patient risk for infective endocarditis in Staphylococcus aureus bacteraemia: a systematic review and meta-analysis. Clinical Microbiology and Infection. Elsevier B.V. https://doi.org/10.1016/j.cmi.2017.04.025

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