Dissemin is shutting down on January 1st, 2025

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Oxford University Press, JAC-Antimicrobial Resistance, 4(5), 2023

DOI: 10.1093/jacamr/dlad096

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Risk factors for carbapenem-resistant Acinetobacter baumannii (CRAB) bloodstream infections and related mortality in critically ill patients with CRAB colonization

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Data provided by SHERPA/RoMEO

Abstract

Abstract Background Among MDR bacteria, carbapenem-resistant Acinetobacter baumannii (CRAB) is a major concern due to the limited therapeutic options. During the COVID-19 pandemic, a worrying increase in the spread of CRAB infections was reported. Objectives The study assessed the risk factors for CRAB bloodstream infection (BSI) in patients admitted to the ICU with CRAB colonization, and the related mortality risk factors. Methods We conducted a single-centre, observational, prospective study; all consecutive patients with CRAB colonization admitted to the ICU of a tertiary hospital in Rome from January 2021 to September 2022 were included in the study. Univariate and multivariate analyses were performed to investigate BSI and mortality risk factors. Results Overall, 129 patients were included in the study; 57 (44%) out of these developed BSI. In our study population, at the multivariable analysis the Charlson comorbidity index (CCI) (P = 0.026), COVID-19 (P < 0.001), multisite colonization (P = 0.016) and the need for mechanical ventilation (P = 0.024) were risk factors independently associated with BSI development. Furthermore, age (P = 0.026), CCI (P < 0.001), septic shock (P = 0.001) and Pitt score (P < 0.001) were independently associated with mortality in the BSI patients. Instead, early appropriate therapy (P = 0.002) and clinical improvement within 72 h (P = 0.011) were shown to be protective factors. Conclusions In critically ill patients colonized by CRAB, higher CCI, multisite colonization and the need for mechanical ventilation were identified as risk factors for BSI onset. These predictors could be useful to identify patients at highest risk of BSI.