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Biomarker-based risk model to predict persistent multiple organ dysfunctions after congenital heart surgery: a
Alexis L Benscoter1, Jeffrey A Alten2, Mihir R Atreya3
1Division of Cardiology, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, 3333 Burnet Ave, MLC 2003, Cincinnati, OH, 45229, USA. alexis.benscoter@cchmc.org.
Insights
A new model using IL-8, CCL3, and age can predict persistent multiple organ dysfunction syndrome (MODS) after pediatric cardiac surgery. This tool helps identify high-risk children for early intervention.
Area of Science:
- Pediatric Cardiac Surgery
- Critical Care Medicine
- Inflammatory Biomarkers
Background:
- Multiple organ dysfunction syndrome (MODS) is a significant complication following pediatric cardiac surgery with cardiopulmonary bypass (CPB).
- Inflammation plays a crucial role in MODS development, sharing pathways with septic shock.
- The PERSEVERE model, using seven protein biomarkers, predicts mortality in pediatric septic shock.
Purpose of the Study:
- To develop a novel risk prediction model for persistent CPB-related MODS in children post-cardiac surgery.
- To evaluate the utility of PERSEVERE biomarkers and clinical data in assessing early post-operative MODS risk.
- To identify high-risk pediatric patients for targeted interventions.
Main Methods:
- A cohort of 306 pediatric patients (<18 years) undergoing cardiac surgery with CPB was studied.
- Persistent MODS was defined as dysfunction in two or more organ systems on postoperative day 5.
- Classification and regression tree methodology was used to derive the risk model using PERSEVERE biomarkers (IL-8, CCL3) and age.
Main Results:
- The optimal model incorporated IL-8, CCL3, and age, achieving an AUROC of 0.86 (0.81-0.91) for differentiating MODS.
- The model demonstrated a high negative predictive value of 99% (95-100) for identifying patients without persistent MODS.
- Cross-validation yielded a corrected AUROC of 0.75 (0.68-0.84).
Conclusions:
- A novel risk prediction model for MODS after pediatric cardiac surgery requiring CPB has been developed.
- This model, utilizing IL-8, CCL3, and age, shows promise in identifying at-risk children.
- Further prospective validation is needed to facilitate early interventions and improve patient outcomes.
Background:
Multiple organ dysfunction syndrome (MODS) is an important cause of post-operative morbidity and mortality for children undergoing cardiac surgery requiring cardiopulmonary bypass (CPB). Dysregulated inflammation is widely regarded as a key contributor to bypass-related MODS pathobiology, with considerable overlap of pathways associated with septic shock. The pediatric sepsis biomarker risk model (PERSEVERE) is comprised of seven protein biomarkers of inflammation and reliably predicts baseline risk of mortality and organ dysfunction among critically ill children with septic shock. We aimed to determine if PERSEVERE biomarkers and clinical data could be combined to derive a new model to assess the risk of persistent CPB-related MODS in the early post-operative period.
Methods:
This study included 306 patients < 18 years old admitted to a pediatric cardiac ICU after surgery requiring cardiopulmonary bypass (CPB) for congenital heart disease. Persistent MODS, defined as dysfunction of two or more organ systems on postoperative day 5, was the primary outcome. PERSEVERE biomarkers were collected 4 and 12 h after CPB. Classification and regression tree methodology were used to derive a model to assess the risk of persistent MODS.
Results:
The optimal model containing interleukin-8 (IL-8), chemokine ligand 3 (CCL3), and age as predictor variables had an area under the receiver operating characteristic curve (AUROC) of 0.86 (0.81-0.91) for differentiating those with or without persistent MODS and a negative predictive value of 99% (95-100). Ten-fold cross-validation of the model yielded a corrected AUROC of 0.75 (0.68-0.84).
Conclusions:
We present a novel risk prediction model to assess the risk for development of multiple organ dysfunction after pediatric cardiac surgery requiring CPB. Pending prospective validation, our model may facilitate identification of a high-risk cohort to direct interventions and studies aimed at improving outcomes via mitigation of post-operative organ dysfunction.
