Nomogram identifies burned children at risk of infections

A newly developed nomogram demonstrates its ability to predict the risk of healthcare-associated infections (HAIs) in burned children. This prediction model is based on factors such as larger burns, longer length of stay (LOS), and use of central venous catheter (CVC), among others.

“Early identification of patients at risk for HAIs and establishing potential preventive and therapeutic strategies could reduce morbidity and mortality among burned children,” the investigators said. 

The study included 1,122 children admitted to the burn unit of Wuhan Third Hospital between 2020 and 2022. Predictors of HAIs were ascertained via univariate and multivariate logistic regression analyses. The investigators then developed a nomogram to predict the HAI risk of each patient.

Receiver operating characteristic curves and calibration curves were used to assess the predictive ability of the nomogram, and decision and impact curves were generated to evaluate its clinical utility.

Of the burned children, 61 (5.5 percent) acquired HAIs. In multivariate analysis, the following factors independently predicted HAI risk: total burn surface area (TBSA), LOS, surgery, CVC use, and urinary catheter use. [Pediatr Infec Dis J 2024;43:1147-1151]

“Increasing TBSA and depth of burn correlates with excessive risk of infectious complications,” according to the investigators. [Burns 2017;43:642-653; Clin Infect Dis 2003;37:543-550]

TBSA, a critical component in assessing burn severity, was found to be significantly associated with infection among burned children in previous studies. [Arch Argent Pediatr 2013;111:303-308; J Hosp Infect 2002;52:161-165]

These variables were then used to create a predictive nomogram for the occurrence of HAIs in burned children. Based on internal validation results, the prediction model demonstrated good discrimination and calibration, with AUC values of 0.926 (95 percent confidence interval, 0.896–0.957).

The calibration curve revealed high consistency between the actual and predicted HAIs, while the decision and impact curve showed good clinical utility of the nomogram and more credible net clinical benefits in predicting HAIs.

“Altogether, the nomogram has good performance in predicting the in-hospital HAI risk of these burned children,” the investigators said.

Prevention and control

Preventive measures at present are not capable of preventing all HAIs, but earlier studies have established the importance of current effective infection prevention and control strategies to avert a large proportion of these infections. 

“The nomogram prediction model can identify high-risk patients and independent risk factors, reducing the incidence of HAIs. It could transform the sophisticated regression equation into an intuitive graph, making the patients’ prediction risk readable,” they added. [Nat Clin Pract Urol 2007;4:638-639; Cancer 2009;115(13 Suppl):3107-3111]

The current study, however, had several limitations. First, the information on the variables was not comprehensive enough. “Therefore, we should enrich the content of variables in the future to explore the relationship between different types of variables and HAIs,” the investigators said. 

Second, an independent external validation cohort was lacking. “In the future, we will focus on implementing multicentre prospective studies and strengthen collaboration between hospitals for external validation of the model,” they added.