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BackgroundThe COVID-19 pandemic increased the use of broad-spectrum antibiotics due to diagnostic uncertainty, particularly in critical care. Multi-professional communication became more difficult, weakening stewardship activities.AimTo determine changes in bacterial co-/secondary infections and antibiotics used in COVID-19 patients in critical care, and mortality rates, between the first and second waves.MethodsProspective audit comparing bacterial co-/secondary infections and their treatment during the first two waves of the pandemic in a single-centre teaching hospital intensive care unit. Data on demographics, daily antibiotic use, clinical outcomes, and culture results in patients diagnosed with COVID-19 infection were collected over 11 months.FindingsFrom March 9th, 2020 to September 2nd, 2020 (Wave 1), there were 156 patients and between September 3rd, 2020 and February 1st, 2021 (Wave 2) there were 235 patients with COVID-19 infection admitted to intensive care. No significant difference was seen in mortality or positive blood culture rates between the two waves. The proportion of patients receiving antimicrobial therapy (93.0% vs 81.7%; P < 0.01) and the duration of meropenem use (median (interquartile range): 5 (2-7) vs 3 (2-5) days; P = 0.01) was lower in Wave 2. However, the number of patients with respiratory isolates of Pseudomonas aeruginosa (4/156 vs 21/235; P < 0.01) and bacteraemia from a respiratory source (3/156 vs 20/235; P < 0.01) increased in Wave 2, associated with an outbreak of infection. There was no significant difference between waves with respect to isolation of other pathogens.ConclusionReduced broad-spectrum antimicrobial use in the second wave of COVID-19 compared with the first wave was not associated with significant change in mortality.

Original publication

DOI

10.1016/j.jhin.2022.03.007

Type

Journal

The Journal of hospital infection

Publication Date

23/03/2022

Volume

124

Pages

37 - 46

Addresses

Department of Clinical Microbiology, University College London NHS Foundation Trust, London, UK; Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK.