The Role of Negative Pressure Wound Therapy and Regenerative Approaches in Severe Pressure Ulcers

Pressure ulcers (PUs) represent a significant healthcare burden, affecting approximately 12.8% of hospitalized patients globally, with severe stage III and IV ulcers posing substantial therapeutic challenges. Traditional management strategies often prove insufficient for complex wounds, necessitating advanced treatment modalities. This comprehensive review examines the current evidence regarding negative pressure wound therapy (NPWT) and regenerative medicine approaches in the treatment of severe pressure ulcers, evaluating their mechanisms of action, clinical efficacy, safety profiles, and potential synergistic applications. A systematic literature search was conducted across PubMed, Cochrane Library, and international guideline databases, focusing on randomized controlled trials, systematic reviews, and clinical practice guidelines published between 2010 and 2026. NPWT demonstrates significant efficacy in promoting granulation tissue formation and reducing wound dimensions through mechanical forces, enhanced perfusion, and inflammatory exudate removal. Multiple randomized controlled trials confirm superior outcomes compared to conventional dressings, with 54% increased granulation tissue formation and reduced hospitalization rates. Regenerative approaches including mesenchymal stem cells, platelet-rich plasma, growth factors, and bioengineered skin substitutes show promising results as adjunctive therapies. Combination strategies, particularly NPWT with basic fibroblast growth factor or stem cells, demonstrate synergistic effects on wound healing parameters. NPWT represents an evidence-based modality for managing severe pressure ulcers when applied according to established protocols and contraindications. Emerging regenerative medicine approaches offer additional therapeutic options, particularly when combined with NPWT. Future directions include personalized medicine strategies, advanced biomaterials, and artificial intelligence-guided treatment algorithms to optimize outcomes in this challenging patient population.