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

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.

Revisiting Post-ICU Admission Fluid Balance Across Pediatric Sepsis Mortality Risk Strata: A Secondary Analysis of a Prospective Observational Cohort Study.

OBJECTIVES: Post-ICU admission cumulative positive fluid balance (PFB) is associated with increased mortality among critically ill patients. We sought to test whether this risk varied across biomarker-based risk strata upon adjusting for illness severity, presence of severe acute kidney injury (acute kidney injury), and use of continuous renal replacement therapy (CRRT) in pediatric septic shock. DESIGN: Ongoing multicenter prospective observational cohort. SETTING: Thirteen PICUs in the United States (2003-2023). PATIENTS: Six hundred and eighty-one children with septic shock. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Cumulative percent PFB between days 1 and 7 (days 1-7 %PFB) was determined. Primary outcome of interest was complicated course defined as death or persistence of greater than or equal to two organ dysfunctions by day 7. Pediatric Sepsis Biomarker Risk Model (PERSEVERE)-II biomarkers were used to assign mortality probability and categorize patients into high mortality (n = 91), intermediate mortality (n = 134), and low mortality (n = 456) risk strata. Cox proportional hazard regression models with adjustment for PERSEVERE-II mortality probability, presence of sepsis-associated acute kidney injury on day 3, and use of CRRT, demonstrated that time-dependent variable days 1-7%PFB was independently associated with an increased hazard of complicated course. Risk-stratified analyses revealed that each 10% increase in days 1-7 %PFB was associated with increased hazard of complicated course only among patients with high mortality risk strata (adjusted hazard ratio 1.24 (95% CI, 1.08-1.43), p = 0.003). However, this association was not causally mediated by PERSEVERE-II biomarkers. CONCLUSIONS: Our data demonstrate the influence of cumulative %PFB on the risk of complicated course in pediatric septic shock. Contrary to our previous report, this risk was largely driven by patients categorized as having a high mortality risk based on PERSEVERE-II biomarkers. Incorporation of such prognostic enrichment tools in randomized trials of restrictive fluid management or early initiation of de-escalation strategies may inform targeted application of such interventions among at-risk patients.

SERUM HUMANIN IN PEDIATRIC SEPTIC SHOCK-ASSOCIATED MULTIPLE-ORGAN DYSFUNCTION SYNDROME.

ABSTRACT: Background: Multiple-organ dysfunction syndrome disproportionately contributes to pediatric sepsis morbidity. Humanin (HN) is a small peptide encoded by mitochondrial DNA and thought to exert cytoprotective effects in endothelial cells and platelets. We sought to test the association between serum HN (sHN) concentrations and multiple-organ dysfunction syndrome in a prospectively enrolled cohort of pediatric septic shock. Methods: Human MT-RNR2 ELISA was used to determine sHN concentrations on days 1 and 3. The primary outcome was thrombocytopenia-associated multiorgan failure (TAMOF). Secondary outcomes included individual organ dysfunctions on day 7. Associations across pediatric sepsis biomarker (PERSEVERE)-based mortality risk strata and correlation with platelet and markers of endothelial activation were tested. Results: One hundred forty subjects were included in this cohort, of whom 39 had TAMOF. The concentration of sHN was higher on day 1 relative to day 3 and among those with TAMOF phenotype in comparison to those without. However, the association between sHN and TAMOF phenotype was not significant after adjusting for age and illness severity in multivariate models. In secondary analyses, sHN was associated with presence of day 7 sepsis-associated acute kidney injury ( P = 0.049). Furthermore, sHN was higher among those with high PERSEVERE-mortality risk strata and correlated with platelet counts and several markers of endothelial activation. Conclusion: Future investigation is necessary to validate the association between sHN and sepsis-associated acute kidney injury among children with septic shock. Furthermore, mechanistic studies that elucidate the role of HN may lead to therapies that promote organ recovery through restoration of mitochondrial homeostasis among those critically ill.

Machine learning-driven identification of the gene-expression signature associated with a persistent multiple organ dysfunction trajectory in critical illness.

BACKGROUND: Multiple organ dysfunction syndrome (MODS) disproportionately drives morbidity and mortality among critically ill patients. However, we lack a comprehensive understanding of its pathobiology. Identification of genes associated with a persistent MODS trajectory may shed light on underlying biology and allow for accurate prediction of those at-risk. METHODS: Secondary analyses of publicly available gene-expression datasets. Supervised machine learning (ML) was used to identify a parsimonious set of genes associated with a persistent MODS trajectory in a training set of pediatric septic shock. We optimized model parameters and tested risk-prediction capabilities in independent validation and test datasets, respectively. We compared model performance relative to an established gene-set predictive of sepsis mortality. FINDINGS: Patients with a persistent MODS trajectory had 568 differentially expressed genes and characterized by a dysregulated innate immune response. Supervised ML identified 111 genes associated with the outcome of interest on repeated cross-validation, with an AUROC of 0.87 (95% CI: 0.85-0.88) in the training set. The optimized model, limited to 20 genes, achieved AUROCs ranging from 0.74 to 0.79 in the validation and test sets to predict those with persistent MODS, regardless of host age and cause of organ dysfunction. Our classifier demonstrated reproducibility in identifying those with persistent MODS in comparison with a published gene-set predictive of sepsis mortality. INTERPRETATION: We demonstrate the utility of supervised ML driven identification of the genes associated with persistent MODS. Pending validation in enriched cohorts with a high burden of organ dysfunction, such an approach may inform targeted delivery of interventions among at-risk patients. FUNDING: H.R.W.'s NIHR35GM126943 award supported the work detailed in this manuscript. Upon his death, the award was transferred to M.N.A. M.R.A., N.S.P, and R.K were supported by NIHR21GM151703. R.K. was supported by R01GM139967.

Derivation, validation, and transcriptomic assessment of pediatric septic shock phenotypes identified through latent profile analyses: Results from a prospective multi-center observational cohort.

Background: Sepsis poses a grave threat, especially among children, but treatments are limited due to clinical and biological heterogeneity among patients. Thus, there is an urgent need for precise subclassification of patients to guide therapeutic interventions. Methods: We used clinical, laboratory, and biomarker data from a prospective multi-center pediatric septic shock cohort to derive phenotypes using latent profile analyses. Thereafter, we trained a support vector machine model to assign phenotypes in a hold-out validation set. We tested interactions between phenotypes and common sepsis therapies on clinical outcomes and conducted transcriptomic analyses to better understand the phenotype-specific biology. Finally, we compared whether newly identified phenotypes overlapped with established gene-expression endotypes and tested the utility of an integrated subclassification scheme. Findings: Among 1,071 patients included, we identified two phenotypes which we named 'inflamed' (19.5%) and an 'uninflamed' phenotype (80.5%). The 'inflamed' phenotype had an over 4-fold risk of 28-day mortality relative to those 'uninflamed'. Transcriptomic analysis revealed overexpression of genes implicated in the innate immune response and suggested an overabundance of developing neutrophils, pro-T/NK cells, and NK cells among those 'inflamed'. There was no significant overlap between endotypes and phenotypes. However, an integrated subclassification scheme demonstrated varying survival probabilities when comparing endophenotypes. Interpretation: Our research underscores the reproducibility of latent profile analyses to identify clinical and biologically informative pediatric septic shock phenotypes with high prognostic relevance. Pending validation, an integrated subclassification scheme, reflective of the different facets of the host response, holds promise to inform targeted intervention among those critically ill.

External validation of the modified sepsis renal angina index for prediction of severe acute kidney injury in children with septic shock.

BACKGROUND: Acute kidney injury (AKI) occurs commonly in pediatric septic shock and increases morbidity and mortality. Early identification of high-risk patients can facilitate targeted intervention to improve outcomes. We previously modified the renal angina index (RAI), a validated AKI prediction tool, to improve specificity in this population (sRAI). Here, we prospectively assess sRAI performance in a separate cohort. METHODS: A secondary analysis of a prospective, multicenter, observational study of children with septic shock admitted to the pediatric intensive care unit from 1/2019 to 12/2022. The primary outcome was severe AKI (≥ KDIGO Stage 2) on Day 3 (D3 severe AKI), and we compared predictive performance of the sRAI (calculated on Day 1) to the original RAI and serum creatinine elevation above baseline (D1 SCr > Baseline +). Original renal angina fulfillment (RAI +) was defined as RAI ≥ 8; sepsis renal angina fulfillment (sRAI +) was defined as RAI ≥ 20 or RAI 8 to < 20 with platelets < 150 × 103/µL. RESULTS: Among 363 patients, 79 (22%) developed D3 severe AKI. One hundred forty (39%) were sRAI + , 195 (54%) RAI + , and 253 (70%) D1 SCr > Baseline + . Compared to sRAI-, sRAI + had higher risk of D3 severe AKI (RR 8.9, 95%CI 5-16, p < 0.001), kidney replacement therapy (KRT) (RR 18, 95%CI 6.6-49, p < 0.001), and mortality (RR 2.5, 95%CI 1.2-5.5, p = 0.013). sRAI predicted D3 severe AKI with an AUROC of 0.86 (95%CI 0.82-0.90), with greater specificity (74%) than D1 SCr > Baseline (36%) and RAI + (58%). On multivariable regression, sRAI + retained associations with D3 severe AKI (aOR 4.5, 95%CI 2.0-10.2, p < 0.001) and need for KRT (aOR 5.6, 95%CI 1.5-21.5, p = 0.01). CONCLUSIONS: Prediction of severe AKI in pediatric septic shock is important to improve outcomes, allocate resources, and inform enrollment in clinical trials examining potential disease-modifying therapies. The sRAI affords more accurate and specific prediction than context-free SCr elevation or the original RAI in this population.

Distinct clinical phenotypes in paediatric cancer patients with sepsis are associated with different outcomes-an international multicentre retrospective study.

Background: Identifying phenotypes in sepsis patients may enable precision medicine approaches. However, the generalisability of these phenotypes to specific patient populations is unclear. Given that paediatric cancer patients with sepsis have different host response and pathogen profiles and higher mortality rates when compared to non-cancer patients, we determined whether unique, reproducible, and clinically-relevant sepsis phenotypes exist in this specific patient population. Methods: We studied patients with underlying malignancies admitted with sepsis to one of 25 paediatric intensive care units (PICUs) participating in two large, multi-centre, observational cohorts from the European SCOTER study (n = 383 patients; study period between January 1, 2018 and January 1, 2020) and the U.S. Novel Data-Driven Sepsis Phenotypes in Children study (n = 1898 patients; study period between January 1, 2012 and January 1, 2018). We independently used latent class analysis (LCA) in both cohorts to identify phenotypes using demographic, clinical, and laboratory data from the first 24 h of PICU admission. We then tested the association of the phenotypes with clinical outcomes in both cohorts. Findings: LCA identified two distinct phenotypes that were comparable across both cohorts. Phenotype 1 was characterised by lower serum bicarbonate and albumin, markedly increased lactate and hepatic, renal, and coagulation abnormalities when compared to phenotype 2. Patients with phenotype 1 had a higher 90-day mortality (European cohort 29.2% versus 13.4%, U.S. cohort 27.3% versus 11.4%, p < 0.001) and received more vasopressor and renal replacement therapy than patients with phenotype 2. After adjusting for severity of organ dysfunction, haematological cancer, prior stem cell transplantation and age, phenotype 1 was associated with an adjusted OR of death at 90-day of 1.9 (1.04-3.34) in the European cohort and 1.6 (1.2-2.2) in the U.S. cohort. Interpretation: We identified two clinically-relevant sepsis phenotypes in paediatric cancer patients that are reproducible across two international, multicentre cohorts with prognostic implications. These results may guide further research regarding therapeutic approaches for these specific phenotypes. Funding: Part of this study is funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development.

A MACHINE LEARNING MODEL DERIVED FROM ANALYSIS OF TIME-COURSE GENE-EXPRESSION DATASETS REVEALS TEMPORALLY STABLE GENE MARKERS PREDICTIVE OF SEPSIS MORTALITY.

ABSTRACT: Sepsis is associated with significant mortality and morbidity among critically ill patients admitted to intensive care units and represents a major health challenge globally. Given the significant clinical and biological heterogeneity among patients and the dynamic nature of the host immune response, identifying those at high risk of poor outcomes remains a critical challenge. Here, we performed secondary analysis of publicly available time-series gene-expression datasets from peripheral blood of patients admitted to the intensive care unit to elucidate temporally stable gene-expression markers between sepsis survivors and nonsurvivors. Using a limited set of genes that were determined to be temporally stable, we derived a dynamical model using a Support Vector Machine classifier to accurately predict the mortality of sepsis patients. Our model had robust performance in a test dataset, where patients' transcriptome was sampled at alternate time points, with an area under the curve of 0.89 (95% CI, 0.82-0.96) upon 5-fold cross-validation. We also identified 7 potential biomarkers of sepsis mortality (STAT5A, CX3CR1, LCP1, SNRPG, RPS27L, LSM5, SHCBP1) that require future validation. Pending prospective testing, our model may be used to identify sepsis patients with high risk of mortality accounting for the dynamic nature of the disease and with potential therapeutic implications.

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

Precision medicine aims to identify treatments that are most likely to result in favorable outcomes for subgroups of patients with similar clinical and biological characteristics. The gaps for the development and implementation of precision medicine strategies in the critical care setting are many, but the advent of data science and multi-omics approaches, combined with the rich data ecosystem in the intensive care unit, offer unprecedented opportunities to realize the promise of precision critical care. In this article, the authors review the data-driven and technology-based approaches being leveraged to discover and implement precision medicine strategies in the critical care setting.

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

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.

Prognostic and predictive value of endothelial dysfunction biomarkers in sepsis-associated acute kidney injury: risk-stratified analysis from a prospective observational cohort of pediatric septic shock.

BACKGROUND: Sepsis-associated acute kidney injury (SA-AKI) is associated with high morbidity, with no current therapies available beyond continuous renal replacement therapy (CRRT). Systemic inflammation and endothelial dysfunction are key drivers of SA-AKI. We sought to measure differences between endothelial dysfunction markers among children with and without SA-AKI, test whether this association varied across inflammatory biomarker-based risk strata, and develop prediction models to identify those at highest risk of SA-AKI. METHODS: Secondary analyses of prospective observational cohort of pediatric septic shock. Primary outcome of interest was the presence of ≥ Stage II KDIGO SA-AKI on day 3 based on serum creatinine (D3 SA-AKI SCr). Biomarkers including those prospectively validated to predict pediatric sepsis mortality (PERSEVERE-II) were measured in Day 1 (D1) serum. Multivariable regression was used to test the independent association between endothelial markers and D3 SA-AKI SCr. We conducted risk-stratified analyses and developed prediction models using Classification and Regression Tree (CART), to estimate risk of D3 SA-AKI among prespecified subgroups based on PERSEVERE-II risk. RESULTS: A total of 414 patients were included in the derivation cohort. Patients with D3 SA-AKI SCr had worse clinical outcomes including 28-day mortality and need for CRRT. Serum soluble thrombomodulin (sTM), Angiopoietin-2 (Angpt-2), and Tie-2 were independently associated with D3 SA-AKI SCr. Further, Tie-2 and Angpt-2/Tie-2 ratios were influenced by the interaction between D3 SA-AKI SCr and risk strata. Logistic regression demonstrated models predictive of D3 SA-AKI risk performed optimally among patients with high- or intermediate-PERSEVERE-II risk strata. A 6 terminal node CART model restricted to this subgroup of patients had an area under the receiver operating characteristic curve (AUROC) 0.90 and 0.77 upon tenfold cross-validation in the derivation cohort to distinguish those with and without D3 SA-AKI SCr and high specificity. The newly derived model performed modestly in a unique set of patients (n = 224), 84 of whom were deemed high- or intermediate-PERSEVERE-II risk, to distinguish those patients with high versus low risk of D3 SA-AKI SCr. CONCLUSIONS: Endothelial dysfunction biomarkers are independently associated with risk of severe SA-AKI. Pending validation, incorporation of endothelial biomarkers may facilitate prognostic and predictive enrichment for selection of therapeutics in future clinical trials among critically ill children.

SERUM SOLUBLE ENDOGLIN IN PEDIATRIC SEPTIC SHOCK-ASSOCIATED MULTIPLE ORGAN DYSFUNCTION SYNDROME.

ABSTRACT: Background: Endothelial activation is a key driver of multiple organ dysfunction syndrome (MODS). Soluble endoglin (sENG) is expressed by mature and progenitor endothelial cells and thought to have angiogenic properties. We sought to determine the association between sENG and pediatric sepsis-associated MODS. Methods: Prospective observational study of pediatric septic shock. Primary outcome of interest was complicated course-a composite of death by (or) MODS on day 7 of illness. Secondary outcomes included individual organ dysfunctions. Endothelial biomarkers including sENG were measured using multiplex Luminex assays among patients with existing data on the Pediatric Sepsis Biomarker Risk Model (PERSEVERE-II) data. Multivariable regression was used to test the independent association between sENG and clinical outcomes. Serum sENG concentrations across PERSEVERE-II mortality risk strata and correlations with established markers of endothelial dysfunction were determined. Results: Three hundred six critically ill children with septic shock were included. Serum sENG concentrations were higher among those with primary and secondary outcomes of interest, with the exception of acute neurological dysfunction. Soluble endoglin was independently associated with increased odds of complicated course (adjusted odds ratio, 1.53; 95% confidence interval, 1.02-2.27; P = 0.038) and acute renal dysfunction (adjusted odds ratio, 1.84; 95% confidence interval, 1.18-2.876; P = 0.006). Soluble endoglin demonstrated graded responses across PERSEVERE-II risk strata and was positively correlated with endothelial biomarkers, except angiopoietin-1. Conclusions: Serum sENG is independently associated with complicated course and acute renal dysfunction in pediatric septic shock. Future studies are required to validate our observational data, and mechanistic studies are necessary to elucidate whether endoglin plays an organ-specific role in the development or resolution of acute renal dysfunction in sepsis.

Revisiting post-ICU admission fluid balance across pediatric sepsis mortality risk strata: A secondary analyses from a prospective observational cohort study.

Introduction: Post-ICU admission cumulative positive fluid balance (PFB) is associated with increased mortality among critically ill patients. We sought to test whether this risk varied across biomarker-based risk strata upon adjusting for illness severity, presence of severe acute kidney injury (AKI), and use of renal replacement therapy (CRRT) in pediatric septic shock. Design: Ongoing multi-center prospective observational cohort. Setting: Thirteen pediatric ICUs in the United States (2003-2023). Patients: Six hundred and eighty-one children with septic shock. Interventions: None. Measurements and Main Results: Cumulative percent positive fluid balance between day 1-7 (Day 1-7%PFB) was determined. Primary outcome of interest was complicated course defined as death or persistence of ≥ 2 organ dysfunctions by day 7. PERSEVERE-II biomarkers were used to assign mortality probability and categorize patients into high (n = 91), intermediate (n = 134), and low (n = 456) mortality risk strata. Cox proportional hazard regression models with adjustment for PERSEVERE-II mortality probability, presence of sepsis associated acute kidney injury (SA-AKI) on Day 3, and any use of CRRT, demonstrated that time-dependent variable Day 1-7%PFB was independently associated with increased hazard of complicated course in the cohort. Risk stratified analyses revealed that each 10% increase in Day 1-7%PFB was independently associated with increased hazard of complicated course among patients with high mortality risk strata (adj HR of 1.24 (95%CI: 1.08-1.42), p = 0.002), but not among those categorized as intermediate- or low- mortality risk. Conclusions: Our data demonstrate the independent influence of cumulative %PFB on the risk of complicated course. Contrary to our previous report, this risk was largely driven by patients categorized as having a high-mortality risk based on PERSEVERE-II biomarkers. Further research is necessary to determine whether this subset of patients may benefit from targeted deployment of restrictive fluid management or early initiation of de-escalation therapies upon resolution of shock.

Derivation, Validation, and Clinical Relevance of a Pediatric Sepsis Phenotype With Persistent Hypoxemia, Encephalopathy, and Shock.

OBJECTIVES: Untangling the heterogeneity of sepsis in children and identifying clinically relevant phenotypes could lead to the development of targeted therapies. Our aim was to analyze the organ dysfunction trajectories of children with sepsis-associated multiple organ dysfunction syndrome (MODS) to identify reproducible and clinically relevant sepsis phenotypes and determine if they are associated with heterogeneity of treatment effect (HTE) to common therapies. DESIGN: Multicenter observational cohort study. SETTING: Thirteen PICUs in the United States. PATIENTS: Patients admitted with suspected infections to the PICU between 2012 and 2018. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We used subgraph-augmented nonnegative matrix factorization to identify candidate trajectory-based phenotypes based on the type, severity, and progression of organ dysfunction in the first 72 hours. We analyzed the candidate phenotypes to determine reproducibility as well as prognostic, therapeutic, and biological relevance. Overall, 38,732 children had suspected infection, of which 15,246 (39.4%) had sepsis-associated MODS with an in-hospital mortality of 10.1%. We identified an organ dysfunction trajectory-based phenotype (which we termed persistent hypoxemia, encephalopathy, and shock) that was highly reproducible, had features of systemic inflammation and coagulopathy, and was independently associated with higher mortality. In a propensity score-matched analysis, patients with persistent hypoxemia, encephalopathy, and shock phenotype appeared to have HTE and benefit from adjuvant therapy with hydrocortisone and albumin. When compared with other high-risk clinical syndromes, the persistent hypoxemia, encephalopathy, and shock phenotype only overlapped with 50%-60% of patients with septic shock, moderate-to-severe pediatric acute respiratory distress syndrome, or those in the top tier of organ dysfunction burden, suggesting that it represents a nonsynonymous clinical phenotype of sepsis-associated MODS. CONCLUSIONS: We derived and validated the persistent hypoxemia, encephalopathy, and shock phenotype, which is highly reproducible, clinically relevant, and associated with HTE to common adjuvant therapies in children with sepsis.

Detrimental effects of PCSK9 loss-of-function in the pediatric host response to sepsis are mediated through independent influence on Angiopoietin-1.

BACKGROUND: Sepsis is associated with significant mortality. Yet, there are no efficacious therapies beyond antibiotics. PCSK9 loss-of-function (LOF) and inhibition, through enhanced low-density lipoprotein receptor (LDLR) mediated endotoxin clearance, holds promise as a potential therapeutic approach among adults. In contrast, we have previously demonstrated higher mortality in the juvenile host. Given the potential pleiotropic effects of PCSK9 on the endothelium, beyond canonical effects on serum lipoproteins, both of which may influence sepsis outcomes, we sought to test the influence of PCSK9 LOF genotype on endothelial dysfunction. METHODS: Secondary analyses of a prospective observational cohort of pediatric septic shock. Genetic variants of PCSK9 and LDLR genes, serum PCSK9, and lipoprotein concentrations were determined previously. Endothelial dysfunction markers were measured in day 1 serum. We conducted multivariable linear regression to test the influence of PCSK9 LOF genotype on endothelial markers, adjusted for age, complicated course, and low- and high-density lipoproteins (LDL and HDL). Causal mediation analyses to test impact of select endothelial markers on the association between PCSK9 LOF genotype and mortality. Juvenile Pcsk9 null and wildtype mice were subject to cecal slurry sepsis and endothelial markers were quantified. RESULTS: A total of 474 patients were included. PCSK9 LOF was associated with several markers of endothelial dysfunction, with strengthening of associations after exclusion of those homozygous for the rs688 LDLR variant that renders it insensitive to PCSK9. Serum PCSK9 was not correlated with endothelial dysfunction. PCSK9 LOF influenced concentrations of Angiopoietin-1 (Angpt-1) upon adjusting for potential confounders including lipoprotein concentrations, with false discovery adjusted p value of 0.042 and 0.013 for models that included LDL and HDL, respectively. Causal mediation analysis demonstrated that the effect of PCSK9 LOF on mortality was mediated by Angpt-1 (p = 0.0008). Murine data corroborated these results with lower Angpt-1 and higher soluble thrombomodulin among knockout mice with sepsis relative to the wildtype. CONCLUSIONS: We present genetic and biomarker association data that suggest a potential direct role of the PCSK9-LDLR pathway on Angpt-1 in the developing host with septic shock and warrant external validation. Further, mechanistic studies on the role of PCSK9-LDLR pathway on vascular homeostasis may lead to the development of pediatric-specific sepsis therapies.

Biomarker-based risk model to predict persistent multiple organ dysfunctions after congenital heart surgery: a prospective observational cohort study.

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.

Detrimental effects of PCSK9 loss-of-function in the pediatric host response to sepsis are mediated through independent influence on Angiopoietin-1.

Background: Sepsis is associated with significant mortality, yet there are no efficacious therapies beyond antibiotics and supportive care. In adult sepsis studies, PCSK9 loss-of-function (LOF) and inhibition has shown therapeutic promise, likely through enhanced low-density lipoprotein receptor (LDLR) mediated endotoxin clearance. In contrast, we previously demonstrated higher mortality in septic juvenile hosts with PCSK9 LOF. In addition to direct influence on serum lipoprotein levels, PCSK9 likely exerts pleiotropic effects on vascular endothelium. Both mechanisms may influence sepsis outcomes. We sought to test the influence of PCSK9 LOF genotype on endothelial dysfunction in pediatric sepsis. Methods: Secondary analyses of a prospective observational cohort of pediatric septic shock. Single nucleotide polymorphisms of PCSK9 and LDLR genes were assessed. Serum PCSK9, lipoprotein, and endothelial marker concentrations were measured. Multivariable linear regression tested the influence of PCSK9 LOF genotype on endothelial markers, adjusted for age, complicated course, and low- and high-density lipoproteins (LDL and HDL). Causal mediation analyses assessed impact of select endothelial markers on the association between PCSK9 LOF genotype and mortality. Juvenile Pcsk9 null and wildtype mice were subject to cecal slurry sepsis and endothelial markers were quantified. Results: 474 patients were included. PCSK9 LOF was associated with several markers of endothelial dysfunction, with strengthening of associations after exclusion of patients homozygous for the rs688 LDLR variant that renders it insensitive to PCSK9. Serum PCSK9 levels did not correlate with endothelial dysfunction. PCSK9 LOF significantly influenced concentrations of Angiopoietin-1 (Angpt-1) and Vascular Cell Adhesion Molecule-1 (VCAM-1). However, upon adjusting for LDL and HDL, PCSK9 LOF remained significantly associated with low Angpt-1 alone. Causal Mediation Analysis demonstrated that the effect of PCSK9 LOF on mortality was partially mediated by Angpt-1 (p=0.0008). Murine data corroborated these results with lower Angpt-1 and higher soluble thrombomodulin among knockout mice with sepsis relative to the wildtype. Conclusions: PCSK9 LOF independently influences serum Angpt-1 levels in pediatric septic shock. Angpt-1 likely contributes mechanistically to the effect of PCSK9 LOF on mortality in juvenile hosts. Mechanistic studies on the role of PCSK9-LDLR pathway on vascular homeostasis may lead to the development of novel pediatric-specific sepsis therapies.

Biomarker-based risk model to predict persistent multiple organ dysfunctions after congenital heart surgery â€" A prospective observational cohort study.

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 hours after CPB. Classification and Regression Tree methodology was 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. 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. Clinical Trial Registration Number: This study does not meet criteria for a clinical trial per the WHO International Clinical Trials Registry Platform as no intervention was performed.

Integrated PERSEVERE and endothelial biomarker risk model predicts death and persistent MODS in pediatric septic shock: a secondary analysis of a prospective observational study.

BACKGROUND: Multiple organ dysfunction syndrome (MODS) is a critical driver of sepsis morbidity and mortality in children. Early identification of those at risk of death and persistent organ dysfunctions is necessary to enrich patients for future trials of sepsis therapeutics. Here, we sought to integrate endothelial and PERSEVERE biomarkers to estimate the composite risk of death or organ dysfunctions on day 7 of septic shock. METHODS: We measured endothelial dysfunction markers from day 1 serum among those with existing PERSEVERE data. TreeNet® classification model was derived incorporating 22 clinical and biological variables to estimate risk. Based on relative variable importance, a simplified 6-biomarker model was developed thereafter. RESULTS: Among 502 patients, 49 patients died before day 7 and 124 patients had persistence of MODS on day 7 of septic shock. Area under the receiver operator characteristic curve (AUROC) for the newly derived PERSEVEREnce model to predict death or day 7 MODS was 0.93 (0.91-0.95) with a summary AUROC of 0.80 (0.76-0.84) upon tenfold cross-validation. The simplified model, based on IL-8, HSP70, ICAM-1, Angpt2/Tie2, Angpt2/Angpt1, and Thrombomodulin, performed similarly. Interaction between variables-ICAM-1 with IL-8 and Thrombomodulin with Angpt2/Angpt1-contributed to the models' predictive capabilities. Model performance varied when estimating risk of individual organ dysfunctions with AUROCS ranging from 0.91 to 0.97 and 0.68 to 0.89 in training and test sets, respectively. CONCLUSIONS: The newly derived PERSEVEREnce biomarker model reliably estimates risk of death or persistent organ dysfunctions on day 7 of septic shock. If validated, this tool can be used for prognostic enrichment in future pediatric trials of sepsis therapeutics.