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The contribution of a directional preference of stiffness to the efficacy of prophylactic sacral dressings in protecting healthy and diabetic tissues from pressure injury: computational modelling studies.

The sacral region is the most common site for pressure injuries (PIs) associated with lying in bed, and such sacral PIs often commence as deep tissue injuries (DTIs) that later present as open wounds. In complex patients, diabetes is common. Because, among other factors, diabetes affects connective tissue stiffness properties, making these tissues less able to dissipate mechanical loads through physiological deformations, diabetes is an additional biomechanical risk factor for PIs and DTIs. A preventive measure with established successful clinical outcomes is the use of sacral prophylactic dressings. The objective of this study has been to expand our previous work regarding the modes of action and biomechanical efficacy of prophylactic dressings in protecting the soft tissues adjacent to the sacrum by specifically examining the role of a directional stiffness preference (anisotropy) of the dressing while further accounting for diabetic tissue conditions. Multiple three-dimensional anatomically detailed finite element (FE) model variants representing diabetic tissue conditions were used, and tissue loading state data were compared with healthy tissue simulations. We specifically compared soft tissue exposures to elevated internal shear stresses and strain energy densities (SED) near the sacrum during supine weight bearing on a standard (foam) hospital mattress without a dressing, with a prophylactic dressing lacking directional stiffness preferences and with an anisotropic dressing. Our results have clearly shown that an anisotropic dressing design reduces the peak tissue stresses and exposure to sustained tissue deformations in both healthy and diabetic cases. The present study provides additional important insights regarding the optimal structural and material design of prophylactic dressings, which in turn, informs clinicians and decision makers regarding beneficial features.

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