Atreya, Mihir R.Bennett, Tellen D.Geva, AlonFaustino, E. Vincent S.Rogerson, Colin M.Lutfi, RiadCvijanovich, Natalie Z.Bigham, Michael T.Nowak, JeffreySchwarz, Adam J.Baines, TorreyHaileselassie, BereketeabThomas, Neal J.Luo, YuanSanchez-Pinto, L. NelsonNovel Data-Driven Sepsis Phenotypes in Children Study and the Genomics of Pediatric Septic Shock Investigators2024-02-272024-02-272023-08-02Atreya MR, Bennett TD, Geva A, et al. External validation and biomarker assessment of a high-risk, data-driven pediatric sepsis phenotype characterized by persistent hypoxemia, encephalopathy, and shock. Preprint. Res Sq. 2023;rs.3.rs-3216613. Published 2023 Aug 2. doi:10.21203/rs.3.rs-3216613/v1https://hdl.handle.net/1805/38904Objective: Identification of children with sepsis-associated multiple organ dysfunction syndrome (MODS) at risk for poor outcomes remains a challenge. Data-driven phenotyping approaches that leverage electronic health record (EHR) data hold promise given the widespread availability of EHRs. We sought to externally validate the data-driven 'persistent hypoxemia, encephalopathy, and shock' (PHES) phenotype and determine its association with inflammatory and endothelial biomarkers, as well as biomarker-based pediatric risk-strata. Design: We trained and validated a random forest classifier using organ dysfunction subscores in the EHR dataset used to derive the PHES phenotype. We used the classifier to assign phenotype membership in a test set consisting of prospectively enrolled pediatric septic shock patients. We compared biomarker profiles of those with and without the PHES phenotype and determined the association with established biomarker-based mortality and MODS risk-strata. Setting: 25 pediatric intensive care units (PICU) across the U.S. Patients: EHR data from 15,246 critically ill patients sepsis-associated MODS and 1,270 pediatric septic shock patients in the test cohort of whom 615 had biomarker data. Interventions: None. Measurements and main results: The area under the receiver operator characteristic curve (AUROC) of the new classifier to predict PHES phenotype membership was 0.91(95%CI, 0.90-0.92) in the EHR validation set. In the test set, patients with the PHES phenotype were independently associated with both increased odds of complicated course (adjusted odds ratio [aOR] of 4.1, 95%CI: 3.2-5.4) and 28-day mortality (aOR of 4.8, 95%CI: 3.11-7.25) after controlling for age, severity of illness, and immuno-compromised status. Patients belonging to the PHES phenotype were characterized by greater degree of systemic inflammation and endothelial activation, and overlapped with high risk-strata based on PERSEVERE biomarkers predictive of death and persistent MODS. Conclusions: The PHES trajectory-based phenotype is reproducible, independently associated with poor clinical outcomes, and overlap with higher risk-strata based on validated biomarker approaches.en-USAttribution 4.0 InternationalBiomarkersCritical careEndothelial dysfunctionMultiple organ dysfunction syndromePediatricsPrecision medicineSepsisSystemic inflammationArticle