Biological basis of critical illness subclasses: from the bedside to the bench and back again.

Critical illness syndromes including sepsis, acute respiratory distress syndrome, and acute kidney injury (AKI) are associated with high in-hospital mortality and long-term adverse health outcomes among survivors. Despite advancements in care, clinical and biological heterogeneity among patients continues to hamper identification of efficacious therapies. Precision medicine offers hope by identifying patient subclasses based on clinical, laboratory, biomarker and 'omic' data and potentially facilitating better alignment of interventions. Within the previous two decades, numerous studies have made strides in identifying gene-expression based endotypes and clinico-biomarker based phenotypes among critically ill patients associated with differential outcomes and responses to treatment. In this state-of-the-art review, we summarize the biological similarities and differences across the various subclassification schemes among critically ill patients. In addition, we highlight current translational gaps, the need for advanced scientific tools, human-relevant disease models, to gain a comprehensive understanding of the molecular mechanisms underlying critical illness subclasses.

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.

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.

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.

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.

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.

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.

Proprotein Convertase Subtilisin/Kexin Type 9 Loss-of-Function Is Detrimental to the Juvenile Host With Septic Shock.

OBJECTIVES: Proprotein convertase subtilisin/kexin type 9 is a central regulator of lipid metabolism and has been implicated in regulating the host response to sepsis. Proprotein convertase subtilisin/kexin type 9 loss-of-function is associated with improved sepsis outcomes in the adult host through increased hepatic bacterial clearance. Thus, there is interest in leveraging proprotein convertase subtilisin/kexin type 9 inhibitors as a therapeutic strategy in adults with sepsis. We sought to validate this association in children with septic shock and in a juvenile murine model of sepsis. DESIGN: Prospectively enrolled cohort of children with septic shock; experimental mice. SETTING: Seventeen participating institutions; research laboratory. PATIENTS AND SUBJECTS: Five-hundred twenty-two children with septic shock; juvenile (14 d old) and adult (10-14 wk) mice with constitutive proprotein convertase subtilisin/kexin type 9 null and wildtype control mice (C57BL/6). INTERVENTIONS: Proprotein convertase subtilisin/kexin type 9 single-nucleotide polymorphisms, serum proprotein convertase subtilisin/kexin type 9, and lipid profiles in patients. Cecal slurry murine model of sepsis; survival studies in juvenile and adult mice, assessment of lipoprotein fractions, bacterial burden, and inflammation in juvenile mice. MEASUREMENTS AND MAIN RESULTS: PCSK9 loss-of-function genetic variants were independently associated with increased odds of complicated course and mortality in children with septic shock. PCSK9, low-density lipoprotein, and high-density lipoprotein concentrations were lower among patients with complicated course relative to those without. PCSK9 concentrations negatively correlated with proinflammatory cytokine interleukin-8. Proprotein convertase subtilisin/kexin type 9 loss-of-function decreased survival in juvenile mice, but increased survival in adult mice with sepsis. PCSK9 loss-of-function resulted in low lipoproteins and decreased hepatic bacterial burden in juvenile mice. CONCLUSIONS: In contrast to the adult host, proprotein convertase subtilisin/kexin type 9 loss-of-function is detrimental to the juvenile host with septic shock. PCSK9 loss-of-function, in the context of low lipoproteins, may result in reduced hepatic bacterial clearance in the juvenile host with septic shock. Our data indicate that children should be excluded in sepsis clinical trials involving proprotein convertase subtilisin/kexin type 9 inhibitors.

Precision medicine in pediatric sepsis.

PURPOSE OF REVIEW: Pediatric sepsis is a heterogeneous state associated with significant morbidity and mortality, but treatment strategies are limited. Clinical trials of immunomodulators in sepsis have shown no benefit, despite having a strong biological rationale. There is considerable interest in application of a precision medicine approach to pediatric sepsis to identify patients who are more likely to benefit from targeted therapeutic interventions. RECENT FINDINGS: Precision medicine requires a clear understanding of the molecular basis of disease. 'Omics data' and bioinformatics tools have enabled identification of endotypes of pediatric septic shock, with corresponding biological pathways. Further, using a multibiomarker-based approach, patients at highest risk of poor outcomes can be identified at disease onset. Enrichment strategies, both predictive and prognostic, may be used to optimize patient selection in clinical trials and identify a subpopulation in whom therapy of interest may be trialed. A bedside-to-bench-to-bedside model may offer clinicians pragmatic tools to aid in decision-making. SUMMARY: Precision medicine approaches may be used to subclassify, risk-stratify, and select pediatric patients with sepsis who may benefit from new therapies. Application of precision medicine will require robust basic and translational research, rigorous clinical trials, and infrastructure to collect and analyze big data.

Provider Perceptions of Bubble Continuous Positive Airway Pressure and Barriers to Implementation in a Level III Neonatal Unit in South India.

BACKGROUND: Bubble continuous positive airway pressure (bCPAP) is a simple, safe, and cost-effective strategy to provide respiratory support to newborns with respiratory distress syndrome in resource-limited settings. PURPOSE: To understand whether implementation of bCPAP, relative to other modes of respiratory support in the care of newborns with respiratory distress syndrome, increases positive attitudes about its potential for consistent and widespread use among providers in neonatal intensive care units (NICUs) of lower middle-income countries. METHODS: Semistructured qualitative interviews with 14 healthcare providers, including 5 neonatal nurses, 2 respiratory therapists, 5 postgraduate trainees in pediatrics, and 2 attending physicians, were conducted at a level III NICU in south India where bCPAP had been in consistent use for 6 years. Interviews were transcribed and then coded and categorized using NVivo 10 Software (QSR International, Victoria, Australia). FINDINGS: Categories that emerged from our data include (1) perceived indications, (2) learning curve, (3) perceived costs, (4) perceived shortages, and (5) barriers to use. Providers believed that bCPAP was easy to learn and that it helped empower neonatal nurses in decision-making process. Participants provided a nuanced perspective of cost-benefit associated with bCPAP and that it helped make optimal use of limited resources. Participants identified several barriers to the implementation of bCPAP. IMPLICATIONS FOR PRACTICE: Providers of a level III NICU in a lower- to middle-income country viewed the use of bCPAP favorably. Addressing context-specific barriers will be important for the successful widespread implementation of bCPAP. IMPLICATIONS FOR RESEARCH: Further research will need to focus on whether bCPAP can be safely implemented at level II NICUs.Video Abstract Available at https://journals.lww.com/advancesinneonatalcare/Pages/videogallery.aspx.

Racial Differences in the Influence of Interpregnancy Interval on Fetal Growth.

Objectives Assess the influence of maternal race on the association between interpregnancy interval (IPI) and risk of small for gestational age (SGA) and large for gestational age (LGA) births. Methods Statewide population-based cohort study of 380,520 singleton births. We calculated risk of SGA and LGA births following IPIs of 0 to <6, 6 to <12, 12 to <24 (referent), 24 to <60 months, and ≥60 months, by maternal race after adjustment for confounding influences. Results The highest risk for SGA among white women followed short IPI of 0 to <6 months [adjRR 1.14 (95 % CI 1.08-1.21)], and long IPI ≥ 60 months [adjRR 1.37 (95 % CI 1.31-1.43)]. Only long IPI ≥ 60 months increased SGA risk in black women [adjRR 1.22 (95 % CI 1.13-1.32)]. LGA risk in white women was lowest with shortest and longest IPIs, 0 to <6 [adjRR 0.80 (95 % CI 0.76-0.84)] and ≥60 months [adjRR 0.68 (95 % CI 0.66-0.70)]. The crude risk of LGA was directly proportional to longer IPIs in black women. However, after adjusting for confounding effects of age, obesity, excessive gestational weight gain, and gestational diabetes, the effect was reversed to reduced risk following long IPI ≥ 60 months [adjRR 0.82 (95 % CI 0.74-0.91)], similar to that of white women. Conclusions In black and white women, an interpregnancy interval of 1-2 years is associated with optimal fetal growth. In addition to birth spacing, addressing modifiable factors such as pre-pregnancy BMI, monitoring gestational weight gain, and control of gestational diabetes in black women may help optimize fetal growth.

Clinical diagnosis of influenza in the ED.

BACKGROUND: Timely and accurate diagnosis of influenza remains a challenge but is critical for patients who may benefit from antiviral therapy. This study determined the test characteristics of provider diagnosis of influenza, final ED electronic medical record (EMR) diagnosis of influenza, and influenza-like illness (ILI) in patients recommended to receive antiviral treatment according to Centers for Disease Control and Prevention (CDC) guidelines. In addition, we evaluated the compliance with CDC antiviral guidelines. METHODS: A prospective cohort of adults presenting to a tertiary care ED with an acute respiratory illness who met CDC criteria for recommended antiviral treatment were enrolled and tested for influenza. A clinical diagnosis of influenza was assessed by asking the clinician: "Do you think this patient has influenza?" Influenza-like illness was defined according to current CDC criteria. RESULTS: In this cohort of 270 subjects, 42 (16%; 95% confidence interval [CI], 11%-20%) had influenza. Clinician diagnosis had a sensitivity of 36% (95% CI, 22%-52%) and specificity of 78% (95% CI, 72%-83%); EMR final ED diagnosis had a sensitivity of 26% (95% CI, 14%-42%) and specificity of 97% (95% CI, 94%-99%); ILI had a sensitivity of 31% (95% CI, 18%-47%) and specificity of 88% (95% CI, 83%-92%). Only 15 influenza-positive patients (36%) received antiviral treatment. CONCLUSION: Clinician diagnosis, final ED EMR diagnosis, and ILI have low sensitivity for diagnosing influenza, and there is overall poor compliance with CDC antiviral treatment recommendations. Improved methods of influenza diagnosis are needed to help guide management in the clinical setting.

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.

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.

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.

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.

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.