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Published on: February 23, 2024
A Nomogram of Predicting Healthcare-associated Infections in Burned Children
Tengfei Long1, Xuejiao Hu2, Ting Liu3
1From the Department of Infection Prevention and Control.
Insights
A new nomogram accurately predicts healthcare-associated infections (HAIs) in burned children. This tool helps identify high-risk patients for early intervention, improving outcomes and reducing mortality.
Area of Science:
- Pediatric Burn Care
- Infectious Disease Epidemiology
- Clinical Prediction Modeling
Background:
- Healthcare-associated infections (HAIs) pose significant risks, including adverse prognosis and mortality, in pediatric burn patients.
- Effective identification of at-risk individuals is crucial for timely intervention and improved patient outcomes.
Purpose of the Study:
- To develop and validate a predictive nomogram for estimating the risk of HAIs in children with burns.
- To provide a clinical tool for early screening and risk stratification of pediatric burn patients.
Main Methods:
- Retrospective analysis of 1122 pediatric burn patients admitted between 2020 and 2022.
- Univariate and multivariate logistic regression to identify independent predictors of HAIs.
- Development and validation of a nomogram using receiver operating characteristic, calibration, decision, and impact curves.
Main Results:
- 61 (5.5%) of 1122 patients developed HAIs.
- Independent risk factors identified: total burn surface area, length of stay, surgery, central venous catheter, and urinary catheter use.
- The developed nomogram demonstrated good predictive ability (AUC=0.926), with strong calibration and clinical utility.
Conclusions:
- A validated nomogram for predicting HAI risk in burned children has been successfully constructed.
- This nomogram serves as a valuable tool for enhancing the screening of high-risk pediatric burn patients.
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.
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