Background
In pediatric cardiac surgery, infection is a leading cause of morbidity and mortality. We created a model to predict risk of major infection in this population.
Methods
Using the Society of Thoracic Surgeons Congenital Heart Surgery Database, we created a multivariable model in which the primary outcome was major infection (septicemia, mediastinitis, or endocarditis). Candidate independent variables included demographic characteristics, comorbid conditions, preoperative factors, and cardiac surgical procedures. We created a reduced model by backward selection and then created an integer scoring system using a scaling factor with scores corresponding to percent risk of infection.
Results
Of 30,078 children from 48 centers, 2.8% had major infection (2.6% septicemia, 0.3% mediastinitis, and 0.09% endocarditis). Mortality and postoperative length of stay were greater in those with major infection (mortality: 22.2% vs. 3.0%; length of stay > 21 days: 69.9% vs. 10.7%). Young age, high complexity, previous cardiothoracic operation, preoperative length of stay >1 day, preoperative ventilator support, and presence of a genetic abnormality were associated with major infection after backward selection (p<0.001). Estimated infection risk ranged from <0.1% to 13.3%; the model discrimination was good (c-index 0.79).
Conclusions
We created a simple bedside tool to identify children at high risk for major infection after cardiac surgery. These patients may be targeted for interventions to reduce the risk of infection and for inclusion in future clinical trials.