American journal of translational research · 2026
A nomogram for predicting incontinence-associated dermatitis in Chinese patients with severe acute pancreatitis: a retrospective analysis.
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Feng Qian, Chen Heyu, Du Aiping, Xu Yu, Liu Huan
Аннотация
OBJECTIVE: To identify the incidence of and risk factors for incontinence-associated dermatitis (IAD) among Chinese patients with severe acute pancreatitis (SAP) to facilitate the development of a predictive risk assessment model.
METHODS: A prediction model was constructed using data from 302 SAP patients treated at West China Hospital, Sichuan University, from January 2020 to December 2022. The dataset was divided into training (n=183), testing (n=79), and external validation (n=40) sets. Predictors for incontinence-associated dermatitis were identified through univariate and multivariate logistic regression analyses. A nomogram was established to predict the occurrence of incontinence-associated dermatitis. Receiver operating characteristic (ROC) curves and the Hosmer-Lemeshow test were used to evaluate the model's performance.
RESULTS: A total of 302 SAP patients showed a 57% incidence of IAD. Independent predictors included acute physiology and chronic health evaluation II scores of 15 or higher, fecal incontinence, stool frequency greater than 3 times per day, watery stool, and the use of herbal enemas. In the training set, the model showed an area under the ROC curve (AUC) of 0.836 (95% CI: 0.779-0.894), with sensitivity and specificity values of 86.5% and 66.7%, respectively. The testing set yielded an AUC of 0.825 (95% CI: 0.728-0.921), with sensitivity of 82.0% and specificity of 72.4%. External validation using an independent dataset produced an AUC of 0.788 (95% CI: 0.644-0.933), with a sensitivity of 92.9% and a specificity of 57.7%.
CONCLUSION: The nomogram provides a simple and accurate tool for the prompt identification of patients with incontinence-associated dermatitis.
METHODS: A prediction model was constructed using data from 302 SAP patients treated at West China Hospital, Sichuan University, from January 2020 to December 2022. The dataset was divided into training (n=183), testing (n=79), and external validation (n=40) sets. Predictors for incontinence-associated dermatitis were identified through univariate and multivariate logistic regression analyses. A nomogram was established to predict the occurrence of incontinence-associated dermatitis. Receiver operating characteristic (ROC) curves and the Hosmer-Lemeshow test were used to evaluate the model's performance.
RESULTS: A total of 302 SAP patients showed a 57% incidence of IAD. Independent predictors included acute physiology and chronic health evaluation II scores of 15 or higher, fecal incontinence, stool frequency greater than 3 times per day, watery stool, and the use of herbal enemas. In the training set, the model showed an area under the ROC curve (AUC) of 0.836 (95% CI: 0.779-0.894), with sensitivity and specificity values of 86.5% and 66.7%, respectively. The testing set yielded an AUC of 0.825 (95% CI: 0.728-0.921), with sensitivity of 82.0% and specificity of 72.4%. External validation using an independent dataset produced an AUC of 0.788 (95% CI: 0.644-0.933), with a sensitivity of 92.9% and a specificity of 57.7%.
CONCLUSION: The nomogram provides a simple and accurate tool for the prompt identification of patients with incontinence-associated dermatitis.