Performance of Risk Scores in Predicting Infective Endocarditis in Patients with Staphylococcus aureus Bacteraemia in a Prospective Asian Cohort

3Citations
Citations of this article
6Readers
Mendeley users who have this article in their library.

Abstract

Background: Several risk scores have been derived to predict the risk of infective endocarditis (IE) amongst patients with Staphylococcus aureus bacteraemia (SAB), which helps to guide clinical management. Methods: We prospectively studied 634 patients admitted with SAB. The cohort was stratified into those with or without IE, and the PREDICT Day 1, Day 5 and VIRSTA scores were tabulated. Area under the receiver operating characteristic (AUC) curves were constructed to compare the performance of each score. Results: Of the 634 patients examined, 36 (5.7%) had IE. These patients were younger (51.6 ± 20.1 vs. 59.2 ± 18.0 years, p = 0.015), tended to have community acquisition of bacteraemia (41.7% vs. 17.9%, p < 0.001), and had persistent bacteraemia beyond 72 h (19.4% vs. 6.0%, p = 0.002). The VIRSTA score had the best performance in predicting IE (AUC 0.76, 95%CI 0.66–0.86) compared with PREDICT Day 1 and Day 5. A VIRSTA score of <3 had the best negative predictive value (97.5%), compared with PREDICT Day 1 (<4) and Day 5 (<2) (94.3% and 96.6%, respectively). Conclusions: Overall, the risk scores performed well in our Asian cohort. If applied, 23.5% of the cohort with a VIRSTA ≥ 3 would require TEE, and a score of <3 had an excellent negative predictive value.

Cite

CITATION STYLE

APA

Ngiam, J. N., Koh, M. C. Y., Archuleta, S., Fisher, D., Chai, L. Y. A., Sia, C. H., … Tambyah, P. A. (2024). Performance of Risk Scores in Predicting Infective Endocarditis in Patients with Staphylococcus aureus Bacteraemia in a Prospective Asian Cohort. Journal of Clinical Medicine, 13(10). https://doi.org/10.3390/jcm13102947

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free