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This study aims to identify patient characteristics associated with the development of Incontinence-Associated Dermatitis (IAD) category 2 (skin erosion due to incontinence).
380 ICU patients suffering of fecal incontinence will be included in the study. Data on 19 possible risk factors will be collected at one point in time by the research team. Different sources and methods will be used to collect patient data: skin assessment, patient record, direct patient observation, routine blood samples.
Full description
Incontinence is a widespread problem in all health care settings. Prevalence figures of incontinence vary around 20.0% of all hospitalized patients. In acute and critical care units the proportion of patients with fecal incontinence may rise up to 33.0%.
One of the main complications of incontinence is inflammation of the skin in the genital and anal region, also known as incontinence-associated dermatitis (IAD). IAD is defined as skin inflammation manifested as redness with or without blistering, erosion, or loss of skin barrier function that occurs as a consequence of chronically or repeated exposure of the skin to urine or faeces.
A range of skin care products and procedures for the prevention of IAD exists. In order to provide cost-effective IAD prevention, it's important to target preventive skin care interventions to patients at risk of IAD.
The aims of this study are:
This study is a matched case control study. The cases are defined as patients with IAD Cat. 2 (red skin with skin breakdown). The controls are defined as patients with IAD Cat. 0 (at risk, no redness and skin intact). The patient will be matched for fecal incontinence.
In total, 380 ICU patients suffering from fecal incontinence will be included. 19 possible risk factors will be studied.
All data will be collected at one point in time by the research team. Different sources and methods will be used to collect patient data: skin assessment, patient record, direct patient observation, routine blood samples.
Specific IAD risk factors will be determined by applying univariate and multivariate binary logistic regression modeling.
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206 participants in 2 patient groups
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Data sourced from clinicaltrials.gov
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