Challenges in Biofilm Identification in Diabetic Foot Infections: Review of Literature.
Adam AstradaGojiro NakagamiHiromi SanadaPublished in: The international journal of lower extremity wounds (2024)
Foot ulcerations are one of the most common complications of diabetes and one of the major initial causes of amputations. The formation of biofilms on wounds significantly contributes to infections and delayed healing. While existing methods for identifying these biofilms have limitations, there is a need for a convenient tool for its clinical application. This literature review aimed to address the problem with current clinical biofilm identification in wound care and a proposal for biofilm-detection-based wound care in diabetic foot ulcer patients. Identifying biofilms is particularly vital due to the absence of typical signs of infection in DFUs. However, current approaches, although effective, often prove invasive and technically intricate. The wound blotting technique, involving attaching a nitrocellulose membrane and subsequent staining, presents an alternative that is swift and non-invasive. Research highlights the applicability of wound blotting with alcian blue staining in clinical scenarios, consistently producing sensitive outcomes. By addressing the critical need for early biofilm detection, wound blotting holds promise for enhancing DFU management and contributing to strategies aimed at preventing amputations.
Keyphrases
- candida albicans
- pseudomonas aeruginosa
- staphylococcus aureus
- biofilm formation
- surgical site infection
- wound healing
- healthcare
- end stage renal disease
- palliative care
- quality improvement
- chronic kidney disease
- ejection fraction
- type diabetes
- newly diagnosed
- cystic fibrosis
- cardiovascular disease
- risk factors
- loop mediated isothermal amplification
- climate change
- pain management
- prognostic factors
- machine learning
- glycemic control
- peritoneal dialysis
- bioinformatics analysis
- adipose tissue
- skeletal muscle
- insulin resistance
- sensitive detection