Wound management, healing, and early prosthetic rehabilitation: Part 3 - A scoping review of chemical biomarkers.

Abstract

Background: Poor post-amputation healing delays prosthetic fitting, adversely affecting mortality, quality of life, and cardiovascular health. Current residual limb assessments are subjective and lack standardized guidelines, emphasizing the need for objective biomarkers to improve healing and prosthesis readiness assessments.

Objectives: This review aimed to identify predictive, diagnostic, and indicative chemical biomarkers of healing of the tissues and structures found in the residual limbs of adults with amputation.

Methodology: This scoping review followed Joanna Briggs Institute (JBI) and PRISMA-ScR guidelines. Searches using the terms "biomarkers," "wound healing," and "amputation" were performed across Web of Science, Ovid Medline, Ovid Embase, Scopus, Cochrane, PubMed, and CINAHL databases. Inclusion criteria were: 1) References to chemical biomarkers and healing; 2) Residuum tissue healing; 3) Repeatable methodology with ethical approval. Included articles were evaluated for quality of evidence (QualSyst tool) and level of evidence (JBI classification). Sources were categorized by study (e.g., randomized controlled trial or bench research), wound (diabetic, amputation, other), and model (human, murine, other) type. Chemical biomarkers repeated across study categories, and quantification methods were reported on.

Findings: From 3,306 titles and abstracts screened, 646 underwent full-text review, and 203 met the criteria for data extraction, with 76% classified as strong quality. 38 chemical biomarkers were identified across 4 to 50 sources, with interleukins (predictive, indicative, and diagnostic) and HbA1c (predictive) most prevalent, appearing in 50 and 48 sources, respectively. Other biomarkers included predictive blood markers (e.g., cholesterol, white blood cell counts), indicative growth factors, bacteria presence (predictive), proteins (predictive, indicative, and diagnostic, e.g., matrix metalloproteinases), and cellular markers (indicative and diagnostic, e.g., Ki-67, alpha-smooth muscle actin [α-SMA]).

Conclusion: Predictive biomarkers identify comorbidities that may hinder healing, aiding in pre-amputation risk assessment for poor recovery. Indicative biomarkers monitor key biological healing processes, such as angiogenesis (the formation of new blood vessels), wound contraction, and inflammation. Diagnostic biomarkers provide direct insights into tissue composition and cellular-level healing. Integrating these biomarkers into post-amputation assessments enables continuous monitoring of the healing process while accounting for comorbidities, enhancing the objectivity of post-surgical healing management and ensuring more effective, personalized rehabilitation strategies.