Selected article for: "antibiotic therapy and empirical antibiotic therapy"

Author: Mikkelsen, Vibe Sommer; Helleberg, Marie; Haase, Nicolai; Møller, Morten Hylander; Granholm, Anders; Storgaard, Merete; Bender Jonsson, Andreas; Schønning, Kristian; Reiter, Nanna; Sigurðsson, Sigurður Þór; Voldstedlund, Marianne; Christensen, Steffen; Perner, Anders
Title: COVID‐19 vs influenza A/B supeRInfectionS in the IntenSive care unit (CRISIS): Protocol for a Danish nationwide cohort study
  • Cord-id: tnyl10x8
  • Document date: 2021_6_4
  • ID: tnyl10x8
    Snippet: BACKGROUND: Superinfection following viral infection is a known complication, which may lead to longer hospitalisation and worse outcome. Empirical antibiotic therapy may prevent bacterial superinfections, but may also lead to overuse, adverse effects and development of resistant pathogens. Knowledge about the incidence of superinfections in intensive care unit (ICU) patients with severe Coronavirus Disease 2019 (COVID‐19) is limited. METHODS: We will conduct a nationwide cohort study comparin
    Document: BACKGROUND: Superinfection following viral infection is a known complication, which may lead to longer hospitalisation and worse outcome. Empirical antibiotic therapy may prevent bacterial superinfections, but may also lead to overuse, adverse effects and development of resistant pathogens. Knowledge about the incidence of superinfections in intensive care unit (ICU) patients with severe Coronavirus Disease 2019 (COVID‐19) is limited. METHODS: We will conduct a nationwide cohort study comparing the incidence of superinfections in patients with severe COVID‐19 admitted to the ICU compared with ICU patients with influenza A/B in Denmark. We will include approximately 1000 patients in each group from the time period of October 1(st), 2014 to April 30(th), 2019 and from March 10(th), 2020 to March 1(st), 2021 for patients with influenza and COVID‐19, respectively. The primary outcome is any superinfection within 90 days of admission to the ICU. We will use logistic regression analysis comparing COVID‐19 with influenza A/B after adjustment for relevant predefined confounders. Secondarily, we will use unadjusted and adjusted logistic regression analyses to assess six potential risk factors (sex, age, cancer (including haematological), immunosuppression, use of life support on day 1 in the ICU) for superinfections, and compare outcomes in patients with COVID‐19 with/without superinfections, and present descriptive data regarding the superinfections. CONCLUSION: This study will provide important knowledge about superinfections in ICU patients with severe COVID‐19.

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