Estimating the risk of bacteraemia in hospitalised patients with pneumococcal pneumonia. Issue 6 (December 2022)

• Record Type: Journal Article
• Authors: Serrano, Leyre; Ruiz, Luis Alberto; Pérez, Silvia; España, Pedro Pablo; Gomez, Ainhoa; Cilloniz, Catia; Uranga, Ane; Torres, Antoni; Zalacain, Rafael
• Is Part Of: Journal of infection. Volume 85:Issue 6(2022)
• Page Start: 644
• Page End: 651
• Publication Date: 2022-12
• Subjects: Pneumococcal pneumonia -- Bacteraemia -- Prediction model; Infection -- Periodicals; Bacterial Infections -- Periodicals; Communicable Diseases -- Periodicals; Electronic journals; 616.905
• DOI: 10.1016/j.jinf.2022.09.017
• Languages: English
• ISSNs: 0163-4453

Abstract

Highlights: Bacteraemic pneumococcal pneumonia is an invasive infection related to early mortality. Nine predictive factors for bacteraemia easy to obtain at admission were identified. The predictive rule was internally and externally validated. Early identification of bacteraemia could help to guide diagnostic decisions. Summary: Objective: To construct a prediction model for bacteraemia in patients with pneumococcal community-acquired pneumonia (P-CAP) based on variables easily obtained at hospital admission. Methods: This prospective observational multicentre derivation-validation study was conducted in patients hospitalised with P-CAP between 2000 and 2020. All cases were diagnosed based on positive urinary antigen tests in the emergency department and had blood cultures taken on admission. A risk score to predict bacteraemia was developed. Results: We included 1783 patients with P-CAP (1195 in the derivation and 588 in the validation cohort). A third (33.3%) of the patients had bacteraemia. In the multivariate analysis, the following were identified as independent factors associated with bacteraemia: no influenza vaccination the last year, no pneumococcal vaccination in the last 5 years, blood urea nitrogen (BUN) ≥30 mg/dL, sodium <130 mmol/L, lymphocyte count <800/µl, C-reactive protein ≥200 mg/L, respiratory failure, pleural effusion and no antibiotic treatment before admission. The score yielded good discrimination (AUC 0.732; 95% CI: 0.695–0.769) and calibration (Hosmer-Lemeshow p-value 0.801), with similar performance in the validation cohort (AUC 0.764; 95% CI:0.719–0.809). Conclusions: We found nine predictive factors easily obtained on hospital admission that could help achieve early identification of bacteraemia. The prediction model provides a useful tool to guide diagnostic decisions.