Scanning Electron Microscope Examination as an Alternative to Classical Microbiology in the Diagnostics of Catheter-Related Sepsis?
Anna KluzikHanna TomczakMarek NowickiMałgorzata GrześkowiakKrzysztof KuszaPublished in: International journal of environmental research and public health (2023)
Central venous catheters are essential elements enabling the treatment of intensive care unit patients. However, these catheters are sometimes colonised by both bacteria and fungi, and thus, they may become a potential source of systemic infections-catheter-related bloodstream infections (CRBSI). The identification of the pathogen responsible for CRBSI is a time-consuming process. At the same time, the relationship between the quick identification of the pathogen and the implementation of targeted antibiotic therapy is of key importance for controlling the clinical symptoms of sepsis and septic shock in the patient. Quick diagnosis is of key importance to reduce morbidity and mortality in this group of patients. In our study, we attempted to create a catalogue of images of the most commonly cultured pathogens responsible for CRBSI. An FEI Quanta 250 FEG Scanning Electron Microscope (SEM) was used for measurements. SEM images obtained during the analysis were included in this study. Images of SEM are three-dimensional and comparable to the images seen with the human eye and are a tool used for research and measurement whenever it is necessary to analyse the state of the surface and assess its morphology. The method described in our study will not replace the current procedures recognised as the gold standard, i.e., pathogen culturing, determination of the count of microorganisms (CFU -colony forming units), and assessment of drug sensitivity. However, in some cases, the solution proposed in our study may aid the diagnosis of patients with suspected catheter-related bloodstream infections leading to sepsis and septic shock.
Keyphrases
- septic shock
- intensive care unit
- end stage renal disease
- deep learning
- acute kidney injury
- primary care
- convolutional neural network
- ejection fraction
- endothelial cells
- optical coherence tomography
- chronic kidney disease
- candida albicans
- stem cells
- healthcare
- prognostic factors
- multidrug resistant
- high resolution
- drug induced
- peritoneal dialysis
- mesenchymal stem cells
- climate change
- patient reported outcomes
- bone marrow
- cancer therapy
- acute respiratory distress syndrome
- case report
- patient reported
- peripheral blood
- ultrasound guided
- data analysis