Clostridioides difficile and Vancomycin-Resistant Enterococci in COVID-19 Patients with Severe Pneumonia.
Kateřina BogdanováLenka DoubravskáIva VágnerováKristýna HricováVendula PudováMagdaléna RöderováJan PapajkRadovan UvízlKateřina LangováMilan KolářPublished in: Life (Basel, Switzerland) (2021)
Broad-spectrum antibiotics administered to patients with severe COVID-19 pneumonia pose a risk of infection caused by Clostridioides difficile. This risk is reduced mainly by strict hygiene measures and early de-escalation of antibiotic therapy. Recently, oral vancomycin prophylaxis (OVP) has also been discussed. This retrospective study aimed to assess the prevalence of C. difficile in critical COVID-19 patients staying in an intensive care unit of a tertiary hospital department of anesthesiology, resuscitation, and intensive care from November 2020 to May 2021 and the rates of vancomycin-resistant enterococci (VRE) after the introduction of OVP and to compare the data with those from controls in the pre-pandemic period (November 2018 to May 2019). During the COVID-19 pandemic, there was a significant increase in toxigenic C. difficile rates to 12.4% of patients, as compared with 1.6% in controls. The peak rates were noted in February 2021 (25% of patients), immediately followed by initiation of OVP, changes to hygiene precautions, and more rapid de-escalation of antibiotic therapy. Subsequently, toxigenic C. difficile detection rates started to fall. There was a nonsignificant increase in VRE detected in non-gastrointestinal tract samples to 8.9% in the COVID-19 group, as compared to 5.3% in the control group. Molecular analysis confirmed mainly clonal spread of VRE.
Keyphrases
- clostridium difficile
- sars cov
- coronavirus disease
- intensive care unit
- end stage renal disease
- methicillin resistant staphylococcus aureus
- ejection fraction
- newly diagnosed
- chronic kidney disease
- prognostic factors
- cardiac arrest
- stem cells
- risk factors
- open label
- early onset
- clinical trial
- peritoneal dialysis
- deep learning
- patient reported outcomes
- patient reported
- data analysis
- tertiary care
- electronic health record
- artificial intelligence