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Hoedl, M; Eglseer, D.
Which Characteristics of Fecal Incontinence Predispose Incontinence-Associated Dermatitis? A Classification and Regression Tree Analysis.
Adv Skin Wound Care. 2021; 34(2):103-108 Doi: 10.1097/01.ASW.0000722752.86631.af
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Leading authors Med Uni Graz: Eglseer Doris; Hödl Manuela
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Abstract:: To investigate which characteristics of fecal incontinence (FI) are predictors for incontinence-associated dermatitis (IAD) using the Classification and Regression Tree method. Data collected from 2014 to 2016 during the Austrian Nursing Quality Measurement 2.0, an annually conducted, cross-sectional, multicenter prevalence study, were merged and analyzed. The duration, frequency, and amount of FI were used as predictors for IAD. Nurses were asked if the participants suffered from IAD based on their clinical judgment (yes/no). In total, 1,513 participants with FI were included in this analysis. More than 75% of the participants with FI were to a great extent or completely care dependent. Of all FI participants, nearly 6% suffered from IAD, and more than 70% received special skin care for IAD prevention. Participants with FI had the highest risk of developing IAD if they experienced FI every day, had FI for less than 3 months, and had developed the FI in their current institution. Nurses face many challenges while helping patients with FI maintain healthy skin. Knowledge of the results of this study and accumulated knowledge about the specific characteristics of FI that are associated with the development of IAD can help healthcare personnel prevent IAD. Based on these results, improving patient education for persons with newly diagnosed FI to prevent IAD is recommended. Research studies should use the definition of FI established by the International Continence Society. Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.
Find related publications in this database (Keywords): characteristics; classification and regression tree; fecal incontinence; incontinence; incontinence-associated dermatitis; nursing; predictors