Renal replacement therapy for critically ill patients with COVID-19-associated acute kidney injury: A review of current knowledge.
Rasha Samir ShemiesEman NagyDalia YounisHussein SheashaaPublished in: Therapeutic apheresis and dialysis : official peer-reviewed journal of the International Society for Apheresis, the Japanese Society for Apheresis, the Japanese Society for Dialysis Therapy (2021)
The outbreak of coronavirus disease 2019 (COVID-19) has rapidly evolved into a global pandemic. A significant proportion of COVID-19 patients develops severe symptoms, which may include acute respiratory distress syndrome and acute kidney injury as manifestations of multi-organ failure. Acute kidney injury (AKI) necessitating renal replacement therapy (RRT) is increasingly prevalent among critically ill patients with COVID-19. However, few studies have focused on AKI treated with RRT. Many questions are awaiting answers as regards AKI in the setting of COVID-19; whether patients with COVID-19 commonly develop AKI, what are the underlying pathophysiologic mechanisms? What is the best evidence regarding treatment approaches? Identification of the potential indications and the preferred modalities of RRT in this context, is based mainly on clinical experience. Here, we review the current approaches of RRT, required for management of critically ill patients with COVID-19 complicated by severe AKI as well as the precautions that should be adopted by health care providers in dealing with these cases. Electronic search was conducted in MEDLINE, PubMed, ISI Web of Science, and Scopus scientific databases. We searched the terms relevant to this review to identify the relevant studies. We also searched the conference proceedings and ClinicalTrials.gov database.
Keyphrases
- acute kidney injury
- coronavirus disease
- sars cov
- acute respiratory distress syndrome
- cardiac surgery
- healthcare
- respiratory syndrome coronavirus
- extracorporeal membrane oxygenation
- mechanical ventilation
- early onset
- emergency department
- climate change
- deep learning
- adverse drug
- bioinformatics analysis
- electronic health record