Evidence Hub

Comparison of prognostic factors between bacteraemic and non-bacteraemic critically ill immunocompetent patients in community-acquired severe pneumococcal pneumonia: a STREPTOGENE sub-study

Hugo Bellut, Raphaël Porcher, Emmanuelle Varon, Pierre Asfar, Yves Le Tulzo, Bruno Mégarbane, Armelle Mathonnet, Anthony Dugard et al.

Annals of Intensive Care, 2021

614 participants · 8 citations

Abstract

BACKGROUND: The presence of bacteraemia in pneumococcal pneumonia in critically ill patients does not appear to be a strong independent prognostic factor in the existing literature. However, there may be a specific pattern of factors associated with mortality for ICU patients with bacteraemic pneumococcal community-acquired pneumonia (CAP). We aimed to compare the factors associated with mortality, according to the presence of bacteraemia or not on admission, for patients hospitalised in intensive care for severe pneumococcal CAP. METHODS: This was a post hoc analysis of data from the prospective, observational, multicentre STREPTOGENE study in immunocompetent Caucasian adults admitted to intensive care in France between 2008 and 2012 for pneumococcal CAP. Patients were divided into two groups based on initial blood culture (positive vs. negative) for Streptococcus pneumoniae. The primary outcome was hospital mortality, which was compared between the two groups using odds ratios according to predefined variables to search for a prognostic interaction present in bacterial patients but not non-bacteraemic patients. Potential differences in the distribution of serotypes between the two groups were assessed. The prognostic consequences of the presence or not of initial bi-antibiotic therapy were assessed, specifically in bacteraemic patients. RESULTS: Among 614 included patients, 274 had a blood culture positive for S. pneumoniae at admission and 340 did not. The baseline…

Read the paper

Related studies

Go deeper in Evidence Hub

Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.

Open this study Sign up free