Open AccessMeasuring progress to healing: A challenge and an opportunity
Author(s) -
Bull Richard Hillson,
Staines Karen Louise,
Collarte Agnes Juguilon,
Bain Duncan Shirreffs,
Ivins Nicola M.,
Harding Keith Gordon
Publication year - 2022
Publication title -
international wound journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.867
H-Index - 63
eISSN - 1742-481X
pISSN - 1742-4801
DOI - 10.1111/iwj.13669
Subject(s) - medicine , crossover study , randomized controlled trial , crossover , statistical significance , margin (machine learning) , clinical endpoint , wound healing , surgery , physical therapy , physical medicine and rehabilitation , artificial intelligence , computer science , alternative medicine , machine learning , pathology , placebo
Complete healing is problematic as an endpoint for evaluating interventions for wound healing. The great heterogeneity of wounds makes it difficult to match groups, and this is only possible with multivariate stratification and/or very large numbers of subjects. The substantial time taken for wounds to heal necessitates a very lengthy study. Consequently, high quality randomised controlled trials demonstrating an effect of an intervention to a satisfactory level of statistical significance and with a satisfactory level of generalisability are extremely rare. This study determines that the healing of venous leg ulcers receiving multi‐component compression bandaging follows a linear trajectory over a 4‐week period, as measured by gross area healed, percentage area healed, and advance of the wound margin. The linear trajectories of these surrogates make it possible to identify an acceleration in healing resulting from an intervention, and allows self‐controlled or crossover designs with attendant advantages of statistical power and speed. Of the metrics investigated, wound margin advance was the most linear, and was also independent of initial ulcer size.