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Clinical effectiveness of carbapenems versus alternative antibiotics for treating ESBL-producing Enterobacteriaceae bacteraemia: a systematic review and meta-analysis

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JOURNAL OF ANTIMICROBIAL CHEMOTHERAPY
卷 73, 期 10, 页码 2631-2642

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OXFORD UNIV PRESS
DOI: 10.1093/jac/dky168

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  1. National Evidence-based Healthcare Collaborating Agency (NECA), in Korea [NA15-001]

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Objectives: The widespread administration of carbapenems to patients with ESBL-producing Enterobacteriaceae bacteraemia (ESBL-B) has accelerated the emergence of carbapenem-resistant Enterobacteriaceae. This study aimed to systematically review recently published data to evaluate the clinical effectiveness of carbapenems, compared with other antibiotics, in the treatment of ESBL-B. Methods: We searched the Ovid-Medline, Ovid-Embase, Cochrane Library and five Korean local databases until January 2016. We selected studies that reported overall mortality in patients with ESBL-B who had been treated with carbapenems and alternatives. Overall mortality was assessed as the primary outcome and sepsis-related mortality and adverse events were analysed as secondary outcomes. Results: Thirty-five publications fulfilled the inclusion criteria. Regarding empirical therapy, there were no significant differences between the groups that received carbapenems and those that received non-carbapenems in relation to overall mortality. Regarding definitive therapy, overall mortality was lower for patients administered carbapenems compared with those administered non-carbapenems [risk ratio (RR) 0.78, 95% CI 0.61-0.98], non-Vactam/Vactamase inhibitor combinations (non-BL/BLI) (RR 0.71, 95% CI 0.56-0.90) and cephalosporins (RR 0.56, 95% CI 0.42-0.74). There were no differences between the carbapenems and the other antibiotics, namely BL/BLIs, guinolones and aminoglycosides. Conclusions: This meta-analysis showed that BL/BLIs may be promising alternative antibiotics for definitive therapy in patients with ESBL-B. However, the lack of robust data derived from randomized controlled trials limits the conclusions and inferences from the pooled data.

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