BIOMARKERS IN VASCULAR SURGERY: PREDICTING GRAFT FAILURE AND RESTENOSIS

Vascular diseases are a major source of global morbidity and mortality, often requiring surgical intervention, but the long-term outcomes are frequently compromised by complications like graft failure and restenosis. Since traditional imaging methods often detect these issues only at an advanced stage, there is a critical need for more precise and earlier risk prediction tools. This comprehensive narrative review synthesizes existing literature on the predictive value of circulating and tissue-based biomarkers for these adverse outcomes. The study systematically examined major electronic databases including PubMed, Scopus, and Web of Science, utilizing keywords related to vascular surgery, outcomes (e.g., graft failure, restenosis), and biomarkers. The identified biomarkers were categorized into four principal groups: inflammatory, lipid-related, genetic, and novel/emerging markers. The review found that elevated levels of inflammatory markers—such as high-sensitivity C-reactive protein (hs-CRP) and various interleukins (IL-6, IL-1β, TNF-α, IL-18, IL-33)—are strongly associated with an increased risk of graft failure and restenosis. Conversely, anti-inflammatory interleukins like IL-10 and IL-19 were found to correlate with a reduced risk. Furthermore, an unfavorable lipid profile (high LDL, low HDL, or an elevated LDL/HDL ratio) was consistently linked to a higher incidence of these complications. The review also highlights the promising potential of genetic markers, such as specific single nucleotide polymorphisms (SNPs), and novel biomarkers like non-coding RNAs in developing personalized treatment strategies. The findings suggest that incorporating biomarker panels into routine clinical practice could significantly enhance preoperative risk stratification, enabling tailored perioperative therapy and more effective postoperative surveillance. By allowing for the early detection of biological evidence of graft compromise, this precision-medicine model has the potential to substantially improve long-term patient outcomes in vascular surgery.