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.
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.
Authors: Megan SooHoo; Benjamin Griffin; Anna Jovanovich; Danielle E Soranno; Emily Mack; Sonali S Patel; Sarah Faubel; Katja M Gist Journal: Pediatr Nephrol Date: 2018-03-05 Impact factor: 3.714
Authors: Michaël Levy; Nolwenn Le Sache; Mostafa Mokhtari; Guy Fagherazzi; Gaelle Cuzon; Benjamin Bueno; Virginie Fouquet; Alexandra Benachi; Sergio Eleni Dit Trolli; Pierre Tissieres Journal: Ann Intensive Care Date: 2017-03-21 Impact factor: 6.925