BACKGROUND Negative pressure wound therapy (NPWT) has revolutionised the management of complex wounds via mechanisms such as microdeformation, angiogenesis and exudate control. However, its clinical effect has historically only been evaluated by qualitative and visual parameters. This study integrates near-infrared spectroscopy (NIRS) as a biofeedback tool to quantify physiological response to NPWT in real time. OBJECTIVE This study aimed to quantitatively demonstrate the physiological and structural changes induced by an NPWT system in patients with complex wounds, measured using NIRS. METHODS A prospective real-world observational study was conducted with a cohort of 23 patients with 33 wounds. Structural and physiological parameters were documented before and after NPWT treatment. Random-intercept mixed-effect statistical models and pre-post comparison tests were used to assess clinical and physiological significance. RESULTS The data showed a progressive reduction in wound area and volume, accompanied by an increase in tissue oxygen saturation and a sustained decrease in deoxygenated haemoglobin. These findings, objectively quantified through NIRS as a real-time biofeedback tool, highlight the improvement in oxygenation and wound-bed perfusion and support the hypothesis of tissue biomodulation induced by NPWT. CONCLUSION The integration of NIRS redefines the clinical role of NPWT, allowing therapy to be customised based on specific physiological data. This combination represents a new frontier in precision wound medicine. The results of this study provide a foundation for a new generation of clinical decisions in advanced wound management.
Structure-guided negative pressure wound therapy (NPWT): personalised tissue biomodulation with an NPWT system in adults and older adults.
Published 2025 in Journal of Wound Care
ABSTRACT
PUBLICATION RECORD
- Publication year
2025
- Venue
Journal of Wound Care
- Publication date
2025-11-01
- Fields of study
Medicine, Engineering
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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