Pseudomonas aeruginosa Community-Onset Bloodstream Infections: Characterization, Diagnostic Predictors, and Predictive Score Development-Results from the PRO-BAC Cohort

Antibiotics (Basel). 2022 May 24;11(6):707. doi: 10.3390/antibiotics11060707.

Abstract

Community-onset bloodstream infections (CO-BSI) caused by gram-negative bacilli are common and associated with significant mortality; those caused by Pseudomonas aeruginosa are associated with worse prognosis and higher rates of inadequateempirical antibiotic treatment. The aims of this study were to describe the characteristics of patients with CO-BSI caused by P. aeruginosa, to identify predictors, and to develop a predictive score for P. aeruginosa CO-BSI. Materials/methods: PROBAC is a prospective cohort including patients >14 years with BSI from 26 Spanish hospitals between October 2016 and May 2017. Patients with monomicrobial P. aeruginosa CO-BSI and monomicrobial Enterobacterales CO-BSI were included. Variables of interest were collected. Independent predictors of Pseudomonas aeruginosa CO-BSI were identified by logistic regression and a prediction score was developed. Results: A total of 78patients with P. aeruginosa CO-BSI and 2572 with Enterobacterales CO-BSI were included. Patients with P. aeruginosa had a median age of 70 years (IQR 60−79), 68.8% were male, median Charlson score was 5 (IQR 3−7), and 30-daymortality was 18.5%. Multivariate analysis identified the following predictors of CO-BSI-PA [adjusted OR (95% CI)]: male gender [1.89 (1.14−3.12)], haematological malignancy [2.45 (1.20−4.99)], obstructive uropathy [2.86 (1.13−3.02)], source of infection other than urinary tract, biliary tract or intra-abdominal [6.69 (4.10−10.92)] and healthcare-associated BSI [1.85 (1.13−3.02)]. Anindex predictive of CO-BSI-PA was developed; scores ≥ 3.5 showed a negative predictive value of 89% and an area under the receiver operator curve (ROC) of 0.66. Conclusions: We did not find a good predictive score of P. aeruginosa CO-BSI due to its relatively low incidence in the overall population. Our model includes variables that are easy to collect in real clinical practice and could be useful to detect patients with very low risk of P. aeruginosa CO-BSI.

Keywords: Pseudomonas aeruginosa; bacteraemia; bloodstream infection; community-onset; epidemiology.