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Presence of infection in patients with presumed sepsis at the time of ICU admission
© Klouwenberg et al.; licensee BioMed Central Ltd. 2014
Published: 3 December 2014
A clinical suspicion of infection is mandatory for diagnosing sepsis in patients with a systemic inflammatory response syndrome. Yet the accuracy of categorizing critically ill patients presenting to the ICU as being infected or not is unknown. We therefore assessed the likelihood of infection in patients who were treated for sepsis upon admission to the ICU, and quantified the association between plausibility of infection and mortality.
We studied a cohort of critically ill patients admitted with clinically suspected sepsis to two tertiary ICUs in the Netherlands between January 2011 and December 2013. The likelihood of infection was categorized as none, possible, probable or definite by post hoc assessment. We used multivariable competing risks survival analyses to determine the association of the plausibility of infection with mortality.
Among 2,579 patients treated for sepsis, 13% had a post hoc infection likelihood of 'none', and an additional 30% of only 'possible'. These percentages were largely similar for different primary suspected sites of infection. In crude analyses, the likelihood of infection had no impact on ICU mortality, but was associated with increased length of stay and complications. In multivariable analysis, however, patients with an unlikely infection had a higher mortality rate compared to patients with a definite infection (subdistribution hazard ratio 1.23; 95% confidence interval 1.03 to 1.49).
This study is the first prospective analysis to show that the clinical diagnosis of sepsis upon ICU admission corresponds poorly with the presence of infection on post hoc assessment. A higher likelihood of infection does not adversely influence outcome in this population.
This research was performed within the framework of CTMM, the Center for Translational Molecular Medicine (http://www.ctmm.nl), project MARS (grant 04I-201).
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.