Invasive Fungal Breakthrough Infections under Targeted Echinocandin Prophylaxis in High-Risk Liver Transplant Recipients.
Robert BreitkopfBenedikt TremlThomas SenonerZoran BukumirićZoran BukumiricPublished in: Journal of fungi (Basel, Switzerland) (2023)
Invasive fungal infections (IFIs) are frequent and outcome-relevant complications in the early postoperative period after orthotopic liver transplantation (OLT). Recent guidelines recommend targeted antimycotic prophylaxis (TAP) for high-risk liver transplant recipients (HR-LTRs). However, the choice of antimycotic agent is still a subject of discussion. Echinocandins are increasingly being used due to their advantageous safety profile and the increasing number of non-albicans Candida infections. However, the evidence justifying their use remains rather sparse. Recently published data on breakthrough IFI (b-IFI) raise concerns about echinocandin efficacy, especially in the case of intra-abdominal candidiasis (IAC), which is the most common infection site after OLT. In this retrospective study, we analyzed 100 adult HR-LTRs undergoing first-time OLT and receiving echinocandin prophylaxis between 2017 and 2020 in a tertiary university hospital. We found a breakthrough incidence of 16%, having a significant impact on postoperative complications, graft survival, and mortality. The reasons for this may be multifactorial. Among the pathogen-related factors, we identified the breakthrough of Candida parapsilosis in 11% of patients and one case of persistent IFI due to the development of a secondary echinocandin resistance of an IAC caused by Candida glabrata . Consequently, the efficacy of echinocandin prophylaxis in liver transplantation should be questioned. Further studies are necessary to clarify the matter of breakthrough infections under echinocandin prophylaxis.
Keyphrases
- candida albicans
- biofilm formation
- risk factors
- end stage renal disease
- patients undergoing
- chronic kidney disease
- cancer therapy
- cardiovascular events
- electronic health record
- type diabetes
- cystic fibrosis
- systematic review
- big data
- cardiovascular disease
- coronary artery disease
- neural network
- artificial intelligence
- meta analyses