Spread of Carbapenem-Resistant Gram-Negatives and Candida auris during the COVID-19 Pandemic in Critically Ill Patients: One Step Back in Antimicrobial Stewardship?
Laura MagnascoMalgorzata MikulskaDaniele Roberto GiacobbeLucia TaramassoPatricia MuñozChiara DentoneSilvia DettoriStefania TutinoLaura LabateVincenzo di PilatoFrancesca CreaErika CoppoGiulia CoddaChiara RobbaLorenzo BallNicolo' PatronitiAnna MarchesePaolo PelosiMatteo BassettiPublished in: Microorganisms (2021)
The possible negative impact of severe adult respiratory distress caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection (COVID-19) on antimicrobial stewardship and infection control has been postulated, but few real-life data are available. The aim of this study was to report our experience with colonization/infection of carbapenem-resistant Pseudomonas aeruginosa (CRPA), carbapenem-resistant Klebsiella pneumoniae (CR-Kp) and Candida auris among critically ill COVID-19 patients admitted to the intensive care unit (ICU). All COVID-19 patients admitted to the ICUs at San Martino Policlinico Hospital-IRCCS in Genoa, Italy, were screened from 28 February to 31 May 2020. One-hundred and eighteen patients admitted to COVID-19 ICUs were included in the study. Among them, 12 (10.2%) became colonized/infected with CRPA, 6 (5.1%) with C. auris and 2 (1.6%) with CR-Kp. All patients with CRPA received prior treatment with meropenem, and in 11 (91.7%) infection was not preceded by colonization. Four patients (66.7%) developed C. auris candidemia. A significant spread of resistant pathogens was observed among critically ill COVID-19 patients. Dedicated strategies are warranted to prevent horizontal spread and maintain effective antimicrobial stewardship programs in the setting of COVID-19 care.
Keyphrases
- sars cov
- coronavirus disease
- respiratory syndrome coronavirus
- klebsiella pneumoniae
- pseudomonas aeruginosa
- healthcare
- escherichia coli
- gram negative
- end stage renal disease
- biofilm formation
- candida albicans
- ejection fraction
- cystic fibrosis
- machine learning
- chronic kidney disease
- quality improvement
- chronic pain
- big data
- peritoneal dialysis
- mechanical ventilation
- deep learning