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Major infection after pediatric cardiac surgery: external validation of risk estimation model
Andrzej Kansy1, Jeffrey P Jacobs, Andrzej Pastuszko
1The Children's Memorial Health Institute, Warsaw, Poland. ankansy@wp.pl
Insights
The Society of Thoracic Surgeons (STS) model accurately predicts major infection risk in congenital heart surgery patients. This validation confirms its utility as a preoperative risk stratification tool at the institutional level.
Area of Science:
- Cardiology
- Thoracic Surgery
- Infectious Disease Epidemiology
Background:
- A multivariable risk model for major infection in congenital heart surgery was previously developed using the STS Database.
- This study aimed to validate the STS risk model and identify specific risk factors for major infection within a single institution over 16 years.
Purpose of the Study:
- To externally validate the Society of Thoracic Surgeons (STS) multivariable risk estimation model for major infection in congenital heart surgery.
- To assess the significance of identified STS risk factors in a local patient cohort.
Main Methods:
- A multivariable model was created with major infection (septicemia, mediastinitis, endocarditis) as the primary outcome.
- Patient data included Aristotle Basic Score and Risk Adjustment for Congenital Heart Surgery (RACHS-1) classifications.
- The STS risk model's performance and the significance of its risk factors were evaluated.
Main Results:
- Analysis of 6,314 patients revealed 197 (3.1%) major infections.
- Preoperative risk factors significant for infection included young age, high/medium complexity, prior surgery, and preoperative ventilation (p<0.0001).
- The model demonstrated good discrimination (c-index=0.808), with estimated infection risks from 0.32% to 11.58%.
Conclusions:
- The STS risk model serves as a reliable preoperative risk stratification tool for major infection in congenital heart surgery.
- External validation at the single institutional level confirms the model's applicability and accuracy.
Background:
A multivariable risk estimation model, in which the primary outcome was major infection, was recently developed and published using The Society of Thoracic Surgeons (STS) Congenital Heart Surgery Database. We have applied this risk estimation model to our congenital heart surgery program over a 16-year time interval to validate this risk estimation model and verify its specific risk factors for major infection.
Methods:
Using complete and verified data, we selected patients in whom major procedures had been classified using both Aristotle Basic Score and Risk Adjustment for Congenital Heart Surgery (RACHS-1) and created a multivariable model in which primary outcome was major infection (septicemia, mediastinitis, or endocarditis). We checked the STS risk estimation model for major infection. We also assessed the significance of the STS risk factors in our program.
Results:
A total of 6,314 patients were analyzed. We identified 197 (3.1%) major infections (septicemia 3%, endocarditis 0.015%, mediastinitis 0.09%). Hospital mortality, ventilation time, and length of stay were greater in patients with major infections. The following preoperative risk factors identified by the STS risk estimation model were significant in multivariate analysis in our patients: young age, high complexity, medium complexity, previous operation, and preoperative ventilation (p<0.0001). Estimated infection risk ranged from 0.32% to 11.58%. The model discrimination was good (c index, 0.808). Risks of infections after most common congenital heart surgery procedures were similar in both studies (rs=0.952, p=0.0003).
Conclusions:
Our external validation study confirmed that the STS model can be used as a preoperative risk stratification tool for major infection risk at the single institutional level.
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