Inflammation Biomarkers and Correlation to Wound Status After Full-Thickness Skin Grafting
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- fmed-06-00159
Final published version, 2.54 MB, PDF document
Background: A surgical site infection (SSI) is believed to be the result of an exaggerated inflammatory response.
Objective: Examine the relationship between clinical status and inflammation biomarkers in full-thickness skin grafting wounds.
Methods: Twenty patients planned for facial full-thickness skin grafting were enrolled. A week after surgery, all graft wounds were clinically assessed using a 3-step scale for inflammation (low, moderate, high). All wounds were swabbed for routine microbiological analysis and assessment of numbers of aerobic bacteria. Tie-over dressings from all patients were collected and used for wound fluid extraction and subsequent analysis of MMPs, cytokines, and NF-kappa B inducing activity.
Results: Wounds with a high degree of inflammation contained increased total MMP activity (P <= 0.05) in their corresponding fluids. Likewise, the level of the cytokines IL-1 beta, IL-8, IL-6, TNF-alpha was analyzed, and particularly IL-1 beta was discriminatory for highly inflamed wounds (P <= 0.01). Moreover, bacterial loads were increased in highly inflamed wounds compared to wounds with a low degree of inflammation (P <= 0.01). NF-kappa B activation in the monocytic cell line THP-1 was significantly higher when these cells were stimulated by wound fluids with a high degree of inflammation (P <= 0.01). Growth of S. aureus in wounds did not vary between wounds with different degrees of inflammation (chi-square 3.8, P = 0.144).
Conclusion: Biomarkers analyzed from tie-over dressings correlated to clinical wound healing in full-thickness skin grafting.
Keywords
Original language | English |
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Article number | 159 |
Journal | Frontiers in Medicine |
Volume | 6 |
Number of pages | 10 |
ISSN | 2296-858X |
DOIs | |
Publication status | Published - 2019 |
- dermatologic surgery, wound healing, surgical site infection, full-thickness skin grafting, inflammation biomarkers
Research areas
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ID: 225668552