Door-to-antibiotic time and mortality in patients with sepsis: Systematic review and meta-analysis
Leung, Ling Yan, Huang, Hsi-Lan, Hung, Kevin KC, Leung, Chi Yan, Lam, Cherry CY, Lo, Ronson SL, Yeung, Chun Yu, Tsoi, Peter Joseph, Lai, Michael, Brabrand, Mikkel, Walline, Joseph H, and Graham, Colin A (2024) Door-to-antibiotic time and mortality in patients with sepsis: Systematic review and meta-analysis. European Journal of Internal Medicine, 129. pp. 48-61.
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Abstract
Objectives To evaluate whether the timing of initial antibiotic administration in patients with sepsis in hospital affects mortality.
Methods This systematic review and meta-analysis included studies from inception up to 19 May 2022. Interventional and observational studies including adult human patients with suspected or confirmed sepsis and reported time of antibiotic administration with mortality were included. Data were extracted by two independent reviewers. Summary estimates were calculated by using random-effects model. The primary outcome was mortality.
Results We included 42 studies comprising 190,896 patients with sepsis. Pooled data showed that the OR for patient mortality who received antibiotics ≤1 hr was 0.83 (95 %CI: 0.67 to 1.04) when compared with patients who received antibiotics >1hr. Significant reductions in the risk of death in patients with earlier antibiotic administration were observed in patients ≤3 hrs versus >3 hrs (OR: 0.80, 95 %CI: 0.68 to 0.94) and ≤6 hrs vs 6 hrs (OR: 0.57, 95 %CI: 0.39 to 0.82).
Conclusions Our findings show an improvement in mortality in sepsis patients with early administration of antibiotics at <3 and <6 hrs. Thus, these results suggest that antibiotics should be administered within 3 hrs of sepsis recognition or ED arrival regardless of the presence or absence of shock.
Item ID: | 85397 |
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Item Type: | Article (Research - C1) |
ISSN: | 1879-0828 |
Copyright Information: | © 2024 European Federation of Internal Medicine. Published by Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies. |
Date Deposited: | 13 May 2025 02:37 |
FoR Codes: | 32 BIOMEDICAL AND CLINICAL SCIENCES > 3214 Pharmacology and pharmaceutical sciences > 321402 Clinical pharmacology and therapeutics @ 100% |
SEO Codes: | 28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280103 Expanding knowledge in the biomedical and clinical sciences @ 100% |
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