Leveraging Data Science and Novel Technologies to Develop and Implement Precision Medicine Strategies in Critical Care

Sanchez-Pinto, L. Nelson; Bhavani, Sivasubramanium V.; Atreya, Mihir R.; Sinha, Pratik

doi:10.1016/j.ccc.2023.03.002

Cited by 4 publications

(1 citation statement)

References 107 publications

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“…Several recent studies have used trajectory-based approaches that leverage EHR data to characterize high-risk phenotypes of sepsis (9,10). To the best of our knowledge our study is the first to directly compare outputs of trajectory-based phenotypes with biomarker-based risk-stratification approaches.…”

Section: Discussionmentioning

confidence: 99%

External validation and biomarker assessment of a high-risk, data-driven pediatric sepsis phenotype characterized by persistent hypoxemia, encephalopathy, and shock.

Atreya

Bennett

Geva

et al. 2023

Preprint

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Objective 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.

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Section: Discussionmentioning

confidence: 99%

External validation and biomarker assessment of a high-risk, data-driven pediatric sepsis phenotype characterized by persistent hypoxemia, encephalopathy, and shock.

Atreya

Bennett

Geva

et al. 2023

Preprint

Self Cite

View full text Add to dashboard Cite

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Digital solutions in paediatric sepsis: current state, challenges, and opportunities to improve care around the world

Sanchez-Pinto,

del Pilar Arias López,

Scott

et al. 2024

The Lancet Digital Health

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Biomarker Assessment of a High-Risk, Data-Driven Pediatric Sepsis Phenotype Characterized by Persistent Hypoxemia, Encephalopathy, and Shock

Atreya,

Bennett,

Geva

et al. 2024

Pediatric Critical Care Medicine

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Objectives: Identification of children with sepsis-associated multiple organ dysfunction syndrome (MODS) at risk for poor outcomes remains a challenge. We sought to the determine reproducibility of 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 retrained and validated a random forest classifier using organ dysfunction subscores in the 2012–2018 electronic health record (EHR) dataset used to derive the PHES phenotype. We used this classifier to assign phenotype membership in a test set consisting of prospectively (2003–2023) enrolled pediatric septic shock patients. We compared profiles of the PERSEVERE family of biomarkers among those with and without the PHES phenotype and determined the association with established biomarker-based mortality and MODS risk strata. Setting: Twenty-five PICUs across the United States. Patients: EHR data from 15,246 critically ill patients with sepsis-associated MODS split into derivation and validation sets and 1,270 pediatric septic shock patients in the test set of whom 615 had complete biomarker data. Interventions: None. Measurements and Main Results: The area under the receiver operator characteristic curve of the modified classifier to predict PHES phenotype membership was 0.91 (95% CI, 0.90–0.92) in the EHR validation set. In the test set, PHES phenotype membership was associated with both increased adjusted odds of complicated course (adjusted odds ratio [aOR] 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 immunocompromised status. Patients belonging to the PHES phenotype were characterized by greater degree of systemic inflammation and endothelial activation, and were more likely to be stratified as high risk 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 overlapped with higher risk strata based on prospectively validated biomarker approaches.

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Leveraging Data Science and Novel Technologies to Develop and Implement Precision Medicine Strategies in Critical Care

Cited by 4 publications

References 107 publications

External validation and biomarker assessment of a high-risk, data-driven pediatric sepsis phenotype characterized by persistent hypoxemia, encephalopathy, and shock.

External validation and biomarker assessment of a high-risk, data-driven pediatric sepsis phenotype characterized by persistent hypoxemia, encephalopathy, and shock.

Digital solutions in paediatric sepsis: current state, challenges, and opportunities to improve care around the world

Biomarker Assessment of a High-Risk, Data-Driven Pediatric Sepsis Phenotype Characterized by Persistent Hypoxemia, Encephalopathy, and Shock

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