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Supervised Machine Learning Models Predicting Postoperative Low Cardiac Output Syndrome In Neonates.
Orkun Baloglu1, Xiaofeng Wang2, Bradley S Marino3
1Division of Pediatric Critical Care, Department of Integrated Hospital Care, Children's Institute, Cleveland Clinic Children's. Cleveland Clinic Children's Center for Artificial Intelligence (C4AI), Cleveland, OH.
Critical Care Explorations
|October 7, 2025
Summary
Supervised machine learning models accurately predict low cardiac output syndrome (LCOS) in neonates after cardiothoracic surgery. These models offer high interpretability and can enhance postoperative critical cardiac care.
Area of Science:
- Cardiovascular Surgery
- Neonatal Intensive Care
- Machine Learning in Medicine
Background:
- Low cardiac output syndrome (LCOS) is a critical complication in neonates post-cardiothoracic surgery.
- Early prediction of LCOS is essential for timely intervention and improved patient outcomes.
Purpose of the Study:
- To develop and validate supervised machine learning (ML) models for predicting LCOS in neonates within 48 hours of cardiothoracic surgery.
- To identify key clinical and laboratory variables that predict LCOS development.
Main Methods:
- A retrospective observational study involving 181 neonates undergoing cardiothoracic surgery.
- Development of LightGBM ML models using hourly clinical and laboratory data from the first 48 postoperative hours.
- SHapley Additive exPlanations (SHAP) analysis for feature importance assessment.
Main Results:
- The ML models achieved high predictive performance, with AUC values ranging from 0.91 to 0.98.
- Key predictors for LCOS included higher vasoactive inotrope score, lower urine output, and higher serum lactate.
- 14.9% of neonates in the study experienced LCOS.
Conclusions:
- Supervised ML models can accurately predict LCOS in neonates, providing high interpretability.
- Findings support the integration of these models into clinical workflows for enhanced postoperative care.
- Further multicenter validation is recommended.
