tetano
Editor, Senior Moderator
Acta Anaesthesiol Scand
. 2021 Jun 4.
doi: 10.1111/aas.13934. Online ahead of print.
COVID-19 vs influenza A/B supeRInfectionS in the IntenSive care unit (CRISIS): Protocol for a Danish nationwide cohort study
Vibe Sommer Mikkelsen[SUP] 1 [/SUP], Marie Helleberg[SUP] 2 [/SUP], Nicolai Haase[SUP] 1 [/SUP], Morten Hylander Møller[SUP] 1 [/SUP], Anders Granholm[SUP] 1 [/SUP], Merete Storgaard[SUP] 3 [/SUP], Andreas Bender Jonsson[SUP] 1 [/SUP], Kristian Schønning[SUP] 4 [/SUP], Nanna Reiter[SUP] 5 [/SUP], Sigurður Þór Sigurðsson[SUP] 6 [/SUP], Marianne Voldstedlund[SUP] 7 [/SUP], Steffen Christensen[SUP] 8 [/SUP], Anders Perner[SUP] 1 [/SUP]
Affiliations
Abstract
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[SUP]st[/SUP] , 2014 to April 30[SUP]th[/SUP] , 2019 and from March 10[SUP]th[/SUP] , 2020 to March 1[SUP]st[/SUP] , 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.
. 2021 Jun 4.
doi: 10.1111/aas.13934. Online ahead of print.
COVID-19 vs influenza A/B supeRInfectionS in the IntenSive care unit (CRISIS): Protocol for a Danish nationwide cohort study
Vibe Sommer Mikkelsen[SUP] 1 [/SUP], Marie Helleberg[SUP] 2 [/SUP], Nicolai Haase[SUP] 1 [/SUP], Morten Hylander Møller[SUP] 1 [/SUP], Anders Granholm[SUP] 1 [/SUP], Merete Storgaard[SUP] 3 [/SUP], Andreas Bender Jonsson[SUP] 1 [/SUP], Kristian Schønning[SUP] 4 [/SUP], Nanna Reiter[SUP] 5 [/SUP], Sigurður Þór Sigurðsson[SUP] 6 [/SUP], Marianne Voldstedlund[SUP] 7 [/SUP], Steffen Christensen[SUP] 8 [/SUP], Anders Perner[SUP] 1 [/SUP]
Affiliations
- PMID: 34086975
- DOI: 10.1111/aas.13934
Abstract
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[SUP]st[/SUP] , 2014 to April 30[SUP]th[/SUP] , 2019 and from March 10[SUP]th[/SUP] , 2020 to March 1[SUP]st[/SUP] , 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.