A Nomogram of Predicting Healthcare-Associated Infections in Burned Children

Abstract

Background: Healthcare-associated infections (HAIs) are a common clinical concern associated with adverse prognosis and mortality in burned children. This study aimed to construct a predictive nomogram of the risk of HAIs in burned children. Methods: Children admitted to the burn unit of Wuhan Third Hospital between 2020 and 2022 were included. The univariate and multivariate logistic regression analyses were adopted to ascertain predictors of HAIs. A nomogram was developed to predict the HAI risk of each patient, with receiver operating characteristic curves and calibration curves being generated to assess its predictive ability. Furthermore, decision and impact curves were used to assess the clinical utility. Results: Of 1122 burned children, 61 (5.5%) patients experienced HAIs. The multivariate analysis indicated that total burn surface area, length of stay, surgery, central venous catheter use and urinary catheter use were the independent risk factors of HAIs. Using these variables, we developed a predictive nomogram of the occurrence of HAIs in burned children, and the internal validation results demonstrated good discrimination and calibration of the nomogram. The area under the curve values of the nomogram was 0.926 (95% CI, 0.896–0.957). The calibration curve showed high consistency between the actual and predicted HAIs. The decision and impact curve indicated that the nomogram was of good clinical utility and more credible net clinical benefits in predicting HAIs. Conclusions: The present study constructed a nomogram for predicting the risk of HAIs in burned children. This nomogram may strengthen the effective screening of patients at high risk of HAIs.