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Derivation and Validation of a Clinical and Endothelial Biomarker Risk Model to Predict Persistent Pediatric
James G Williams1, Jane E Whitney2, Scott L Weiss3
1Division of Critical Care Medicine and Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, AR.
Insights
Predicting persistent acute respiratory dysfunction in children with sepsis is challenging. New models using clinical data and endothelial biomarkers can identify high-risk pediatric patients early, aiding targeted interventions.
Area of Science:
- Pediatric critical care medicine
- Sepsis research
- Acute respiratory distress syndrome (ARDS) pathophysiology
Background:
- Sepsis-associated ARDS in children leads to significant morbidity and mortality.
- Identifying children at risk for persistent acute respiratory dysfunction is difficult due to patient heterogeneity.
- Endothelial dysfunction is a critical factor in sepsis-induced lung injury.
Purpose of the Study:
- To determine if early clinical variables and endothelial biomarkers can predict persistent acute respiratory dysfunction in critically ill children with sepsis.
- To develop and validate predictive models for sepsis-associated ARDS risk.
Main Methods:
- Multicenter prospective cohort study involving derivation and testing cohorts.
- Clinical and endothelial biomarkers were measured on day 1 of septic shock.
- TreeNet and classification and regression tree (CART) models were trained to predict sepsis-associated ARDS on day 3.
Main Results:
- The CART model identified SA ARD on day 1, Pao2/FiO2 ratio < 250, soluble thrombomodulin, and VCAM-1 as key predictors.
- The model demonstrated good predictive performance with an AUC of 0.88 in training and 0.78-0.83 in validation/test cohorts.
- Children with day 3 SA ARD had higher mortality and longer hospital/ICU stays.
Conclusions:
- Validated predictive models incorporating clinical and endothelial biomarkers can identify pediatric patients with septic shock at high risk for persistent acute respiratory dysfunction.
- These models may aid in enriching patient populations for clinical trials and guiding targeted interventions.
Background:
Sepsis-associated ARDS results in high morbidity and mortality in children. However, heterogeneity among patients makes identifying those at risk of persistent acute respiratory dysfunction challenging. Endothelial dysfunction is a key feature of ARDS pathophysiologic characteristics, contributing to lung injury in sepsis. Incorporating endothelial biomarkers into risk models may enhance prediction of those with persistent acute respiratory dysfunction.
Research Question:
Can clinical variables and endothelial biomarkers measured early in the course of sepsis predict risk of persistent acute respiratory dysfunction among critically ill children?
Study Design And Methods:
This was a multicenter derivation and single center test cohort study of prospectively enrolled children with sepsis. The derivation cohort was split into training and holdout validation sets. We trained TreeNet (Minitab, LLC) and classification and regression tree (CART) models using clinical and endothelial biomarkers measured on day 1 of septic shock to predict risk of sepsis-associated acute respiratory dysfunction (SA ARD) on day 3. The performance of the CART model was tested in the holdout validation data set and in the independent test cohort.
Results:
In the derivation (n = 625) and test (n = 162) cohorts, children with day 3 SA ARD showed increased mortality, length of mechanical ventilation, and PICU length of stay compared with those without. The TreeNet and CART models yielded comparable results. The variables included in the final CART model were presence of SA ARD on day 1, Pao2 to Fio2 ratio of < 250, soluble thrombomodulin, and vascular cell adhesion molecule 1 concentrations. This model showed an area under the receiver operating characteristic curve (AUC) of 0.88 in the training data set, sensitivity of 0.91 (95% CI, 0.86-0.94), specificity of 0.76 (95% CI, 0.68-0.82), and demonstrated reproducibility in validation data set and test cohort (AUC range, 0.78-0.83).
Interpretation:
We derived and validated predictive models incorporating clinical and endothelial biomarkers to identify pediatric patients with septic shock at high risk of persistent acute respiratory dysfunction. Pending prospective validation, such models may facilitate enrichment and targeted intervention in future clinical trials.
