Abstract

The previous research reported the results of a prospect cohort study that used logistic regression analysis to construct a risk prediction model for skin tears in individuals aged over 65 years. The model identified three baseline individual characteristics (male gender, history of STs, and history of falls) and two baseline skin manifestations (purpura and elastosis) that predicted the risk of dorsal forearm skin tears. This paper outlines the relationships between baseline skin manifestations and the risk of skin tears. Univariable logistic regression analysis was conducted of all the baseline data collected from the same-study participants to identify variables that significantly predicted purpura and elastosis at baseline. Amongst the 173 participants, 71 (41%) developed one or more skin tears, and in these participants, 52 (73.2%) displayed purpura, 41 (57.8%) had elastosis, and 30 (42.3%) exhibited both manifestations of the dorsal forearm at baseline. Four individual characteristics (age, history of skin tears, history of falls, and antiplatelet therapy) and three skin properties (pH, subepidermal low echogenicity band of the forearms, and skin thickness) were found to predict the risk of purpura. Conversely, three individual variables (age, gender, and smoking), three clinical skin variables (uneven skin pigmentation, cutis rhomboidalis nuchae, and history of actinic keratosis) and one skin property variable (collagen type IV) predicted the risk of skin elastosis. Progressive changes to the skin's structural and mechanical properties from the underlying effects of chronological ageing, and environmental and lifestyle-related influences increased the risk of purpura and elastotic skin manifestations and concomitantly increased risk of skin tears amongst participants.

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