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

Central or Peripheral Venoarterial Extracorporeal Membrane Oxygenation for Pediatric Sepsis: Outcomes Comparison in the Extracorporeal Life Support Organization Dataset, 2000-2021

OBJECTIVES

Small studies of extracorporeal membrane oxygenation (ECMO) support for children with refractory septic shock (RSS) suggest that high-flow (≥ 150 mL/kg/min) venoarterial ECMO and a central cannulation strategy may be associated with lower odds of mortality. We therefore aimed to examine a large, international dataset of venoarterial ECMO patients for pediatric sepsis to identify outcomes associated with flow and cannulation site.

DESIGN

Retrospective analysis of the Extracorporeal Life Support Organization (ELSO) database from January 1, 2000, to December 31, 2021.

SETTING

International pediatric ECMO centers.

PATIENTS

Patients 18 years old young or younger without congenital heart disease (CHD) cannulated to venoarterial ECMO primarily for a diagnosis of sepsis, septicemia, or septic shock.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Of 1242 pediatric patients undergoing venoarterial ECMO runs in the ELSO dataset, overall mortality was 55.6%. We used multivariable logistic regression analyses to evaluate explanatory factors associated with adjusted odds ratios (aORs) and 95% CI of mortality. In the regression analysis of data 4 hours after ECMO initiation, logarithm of the aOR, plotted against ECMO flow as a continuous variable, showed that higher flow was associated with lower aOR of mortality ( p = 0.03). However, at 24 hours, we failed to find such a relationship. Finally, peripheral cannulation, as opposed to central cannulation, was independently associated with greater odds of mortality (odds ratio, 1.7 [95% CI, 1.1-2.6]).

CONCLUSIONS

In this 2000-2021 international cohort of venoarterial ECMO for non-CHD children with sepsis, we have found that higher ECMO flow at 4 hours after support initiation, and central- rather than peripheral-cannulation, were both independently associated with lower odds of mortality. Therefore, flow early in the ECMO run and cannula location are two important factors to consider in future research in pediatric patients requiring cannulation to venoarterial ECMO for RSS.

Pediatric Sepsis Phenotype in a Single-Center Cohort Covering 2010-2020: Evolution in Day 1-Day 3 Trajectory and Potential Prognostic Value

OBJECTIVES

To examine the utility of day 3 sepsis phenotype classifications compared with day 1 and whether these could be reliably identified using routine clinical data on day 1.

DESIGN

Retrospective cohort study of pediatric patients managed 2010-2014 and 2018-2020.

SETTING

Academic children's hospital.

PATIENTS

One thousand eight hundred twenty-eight children (1 mo to 18 yr old) admitted to the PICU with suspected infection who received a minimum of 7 days of systemic antibiotics.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Subjects showed significant evolution of phenotype from day 1 to day 3, with 31.7-60.9% remaining the same type. Outcomes were worst in those classifying as type D on day 3, with mortality as high as 16.6% in those that were classified as type D on both days 1 and 3, as well as 11.3% in those initially classified as type C (a lower mortality type) on day 1 but type D on day 3. Accurate statistical prediction of day 3 types using multinomial logistic regression and random forest and day 1 data was poor, despite attempts to improve performance.

CONCLUSIONS

In our retrospective cohort of patients with sepsis, we identified significant evolution in phenotype over the first 3 days of illness. Day 3 phenotypes may provide more accurate statistical prediction of outcomes, but identification of day 3 phenotypes using data available early in the course of illness is challenging. New methods will likely be required to improve performance in this area.

Phoenix Sepsis Criteria in Critically Ill Children: Retrospective Validation Using a United States Nine-Center Dataset, 2012-2018

OBJECTIVES

To perform: 1) external validation of the Phoenix Sepsis Score and Phoenix sepsis criteria in a multicenter cohort of critically ill children with infection and a comparison with the 2005 International Pediatric Sepsis Consensus Conference (IPSCC) criteria; 2) a study of Phoenix sepsis criteria performance in patient subgroups based on age and comorbidities; 3) an assessment of microbiological profile of children with Phoenix sepsis; and 4) a study of the performance of the Phoenix-8 score.

DESIGN

Secondary, retrospective analysis of a multicenter cohort study from 2012 to 2018.

SETTING

Nine PICUs in the United States.

PATIENTS

PICU admissions with suspected infection.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Among 25,680 encounters of children with suspected or confirmed infection on PICU admission (4.6% in-hospital mortality), 11,168 (43%) met Phoenix criteria for sepsis or septic shock (9% in-hospital mortality). The Phoenix criteria generally outperformed the IPSCC criteria at discriminating mortality in all critically ill children with infections and across all subgroup analyses, including age group, malignancy, or technology dependence. Of 11,168 patients who met Phoenix criteria, 28% were negative for IPSCC criteria for sepsis and these had higher in-hospital mortality than those who met IPSCC sepsis criteria but not Phoenix criteria (4.7% vs.1.7%; p < 0.001), which was similar to the mortality of patients without sepsis (1.3%). Sepsis was associated with respiratory or bloodstream infection, most commonly Pseudomonas aeruginosa or Staphylococcus aureus. The Phoenix-8 score had good discrimination of mortality in children with infections, comparable to or better than validated and widely used severity of illness and organ dysfunction scores.

CONCLUSIONS

In 2012-2018, among U.S. patients with suspected or confirmed infection admitted to nine PICUs, those with the highest risk of mortality can be identified using the Phoenix sepsis criteria, including in children of different age groups and those with major comorbidities.

Severe Pneumonia in PICU Admissions: The Pediatric Acute and Critical Care Medicine Asian Network (PACCMAN) Observational Cohort Study, 2020-2022

OBJECTIVES

Mortality from pneumonia is three times higher in Asia compared with industrialized countries. We aimed to determine the epidemiology, microbiology, and outcome of severe pneumonia in PICUs across the Pediatric Acute and Critical Care Medicine Asian Network (PACCMAN).

DESIGN

Prospective multicenter observational study from June 2020 to September 2022.

SETTING

Fifteen PICUs in PACCMAN.

PATIENTS

All children younger than 18 years old diagnosed with pneumonia and admitted to the PICU.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Clinical, microbiologic, and outcome data were recorded. The primary outcome was PICU mortality. Univariate and multivariable logistic regression was performed to investigate associations between PICU mortality and explanatory risk factors on presentation to the PICU. Among patients screened, 846 of 11,778 PICU patients (7.2%) with a median age of 1.2 years (interquartile range, 0.4-3.7 yr) had pneumonia. Respiratory syncytial virus was detected in 111 of 846 cases (13.1%). The most common bacteria were Staphylococcus species (71/846 [8.4%]) followed by Pseudomonas species (60/846 [7.1%]). Second-generation cephalosporins (322/846 [38.1%]) were the most common broad-spectrum antibiotics prescribed, followed by carbapenems (174/846 [20.6%]). Invasive mechanical ventilation and noninvasive respiratory support was provided in 438 of 846 (51.8%) and 500 of 846 (59.1%) patients, respectively. PICU mortality was 65 of 846 (7.7%). In the multivariable logistic regression model, age (adjusted odds ratio [aOR], 1.08; 95% CI, 1.00-1.16), Pediatric Index of Mortality 3 score (aOR, 1.03; 95% CI, 1.02-1.05), and drowsiness (aOR, 2.73; 95% CI, 1.24-6.00) were associated with greater odds of mortality.

CONCLUSIONS

In the PACCMAN contributing PICUs, pneumonia is a frequent cause for admission (7%) and is associated with a greater odds of mortality.

Association between the lactate-albumin ratio and microcirculation changes in Pediatric Septic patients

A lactate/albumin ratio (LAR) greater than 0.5 measured early in the course of pediatric critical illness is associated with greater mortality. Whether the elevated LAR can be explained by microcirculation disorders in children with sepsis is not known. In this longitudinal retrospective study (January 2021-January 2024), serum albumin and lactate were measured on admission to the pediatric intensive care unit (PICU), with sublingual video microscopy performed simultaneously to measure microcirculation. A total of 178 children were included, 37% of whom had septic shock measured with the Phoenix Sepsis Score. Patients with remote sepsis had greater odds of an elevated LAR (aOR 6.87: 95% CI 1.98-23.73; p < 0.01). Children with an elevated LAR had more microvascular blood flow abnormalities (aOR 1.31 95% CI 1.08-1.58; p < 0.01), lower 4-6-micron capillary density (aOR 1.03 95% CI 1.01-1.05; p < 0.01) and greater odds of dying (aOR 3.55 95% CI 1.21-10.38; p = 0.02) compared to those with a low LAR. We found no association between LAR and endothelial glycocalyx degradation. A normal LAR is associated with less risk of microcirculatory injury (aOR 0.77 95% CI 0.65-0.93; p < 0.01). In children with sepsis, an elevated LAR is associated with microcirculation abnormalities (microvascular density and flow). The lactate/albumin ratio is a potentially useful biomarker for microcirculatory injury in sepsis.

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

The digitisation of health care is offering the promise of transforming the management of paediatric sepsis, which is a major source of morbidity and mortality in children worldwide. Digital technology is already making an impact in paediatric sepsis, but is almost exclusively benefiting patients in high-resource health-care settings. However, digital tools can be highly scalable and cost-effective, and-with the right planning-have the potential to reduce global health disparities. Novel digital solutions, from wearable devices and mobile apps, to electronic health record-embedded decision support tools, have an unprecedented opportunity to transform paediatric sepsis research and care. In this Series paper, we describe the current state of digital solutions in paediatric sepsis around the world, the advances in digital technology that are enabling the development of novel applications, and the potential effect of advances in artificial intelligence in paediatric sepsis research and clinical care.

Diagnostic Identification of Acute Brain Dysfunction in Pediatric Sepsis and Septic Shock in the Electronic Health Record: A Comparison of Four Definitions in a Reference Dataset

OBJECTIVES

Acute brain dysfunction (ABD) in pediatric sepsis has a prevalence of 20%, but can be difficult to identify. Our previously validated ABD computational phenotype (CP ABD ) used variables obtained from the electronic health record indicative of clinician concern for acute neurologic or behavioral change. We tested whether the CP ABD has better diagnostic performance to identify confirmed ABD than other definitions using the Glasgow Coma Scale or delirium scores.

DESIGN

Diagnostic testing in a curated cohort of pediatric sepsis/septic shock patients.

SETTING

Quaternary freestanding children's hospital.

SUBJECTS

The test dataset comprised 527 children with sepsis/septic shock managed between 2011 and 2021 with a prevalence (pretest probability) of confirmed ABD of 30% (159/527).

MEASUREMENTS AND MAIN RESULTS

CP ABD was based on use of neuroimaging, electroencephalogram, and/or administration of new antipsychotic medication. We compared the performance of the CP ABD with three GCS/delirium-based definitions of ABD-Proulx et al, International Pediatric Sepsis Consensus Conference, and Pediatric Organ Dysfunction Information Update Mandate. The posttest probability of identifying ABD was highest in CP ABD (0.84) compared with other definitions. CP ABD also had the highest sensitivity (83%; 95% CI, 76-89%) and specificity (93%; 95% CI, 90-96%). The false discovery rate was lowest in CP ABD (1-in-6) as was the false omission rate (1-in-14). Finally, the prevalence threshold for the definitions varied, with the CP ABD being the definition closest to 20%.

CONCLUSIONS

In our curated dataset of pediatric sepsis/septic shock, CP ABD had favorable characteristics to identify confirmed ABD compared with GCS/delirium-based definitions. The CP ABD can be used to further study the impact of ABD in studies using large electronic health datasets.

Characteristics and Risk Factors for Pediatric Sepsis

OBJECTIVE

Sepsis is considered a major cause of health loss in children and had high mortality and morbidity. Currently, there is no reliable model for predicting the prognosis of pediatric patients with sepsis. This study aimed to analyze the clinical characteristics of sepsis in children and assess the risk factors associated with poor prognosis in pediatric sepsis patients to identify timely interventions and improve their outcomes.

METHODS

This study analyzed the clinical indicators and laboratory results of septic patients hospitalized in the Pediatric Intensive Care Unit of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, China, from January 1, 2019, to December 31, 2021. Risk factors for sepsis were identified by logistic regression analyses.

RESULTS

A total of 355 children with sepsis were enrolled, with 333 children (93.8%) in the good prognosis group, and 22 children (6.2%) in the poor prognosis group. Among them, there were 255 patients (71.8%) in the sepsis group, and 100 patients (28.2%) in the severe sepsis group. The length of hospital stay in the poor prognosis group was longer than that in the good prognosis group (P<0.01). The levels of interleukin 1β (IL-1β) in the poor prognosis group were higher than those in the good prognosis group (P>0.05), and the platelet (PLT), albumin (ALB), and hemoglobin (Hb) levels were lower in the poor prognosis group (P<0.01). The IL-8 levels in the severe sepsis group were higher than those in the sepsis group (P<0.05). Multiple logistic regression analysis suggested that lower Hb levels, ALB levels, peak PLT counts, and higher IL-1β levels were independent risk factors for poor prognosis in children with sepsis.

CONCLUSION

Lower Hb, ALB, and PLT counts and elevated IL-1β are independent risk factors for poor prognosis in children with sepsis.

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.

Host gene expression signatures to identify infection type and organ dysfunction in children evaluated for sepsis: a multicentre cohort study

BACKGROUND

Sepsis is defined as dysregulated host response to infection that leads to life-threatening organ dysfunction. Biomarkers characterising the dysregulated host response in sepsis are lacking. We aimed to develop host gene expression signatures to predict organ dysfunction in children with bacterial or viral infection.

METHODS

This cohort study was done in emergency departments and intensive care units of four hospitals in Queensland, Australia, and recruited children aged 1 month to 17 years who, upon admission, underwent a diagnostic test, including blood cultures, for suspected sepsis. Whole-blood RNA sequencing of blood was performed with Illumina NovaSeq (San Diego, CA, USA). Samples with completed phenotyping, monitoring, and RNA extraction by March 31, 2020, were included in the discovery cohort; samples collected or completed thereafter and by Oct 27, 2021, constituted the Rapid Paediatric Infection Diagnosis in Sepsis (RAPIDS) internal validation cohort. An external validation cohort was assembled from RNA sequencing gene expression count data from the observational European Childhood Life-threatening Infectious Disease Study (EUCLIDS), which recruited children with severe infection in nine European countries between 2012 and 2016. Feature selection approaches were applied to derive novel gene signatures for disease class (bacterial vs viral infection) and disease severity (presence vs absence of organ dysfunction 24 h post-sampling). The primary endpoint was the presence of organ dysfunction 24 h after blood sampling in the presence of confirmed bacterial versus viral infection. Gene signature performance is reported as area under the receiver operating characteristic curves (AUCs) and 95% CI.

FINDINGS

Between Sept 25, 2017, and Oct 27, 2021, 907 patients were enrolled. Blood samples from 595 patients were included in the discovery cohort, and samples from 312 children were included in the RAPIDS validation cohort. We derived a ten-gene disease class signature that achieved an AUC of 94·1% (95% CI 90·6-97·7) in distinguishing bacterial from viral infections in the RAPIDS validation cohort. A ten-gene disease severity signature achieved an AUC of 82·2% (95% CI 76·3-88·1) in predicting organ dysfunction within 24 h of sampling in the RAPIDS validation cohort. Used in tandem, the disease class and disease severity signatures predicted organ dysfunction within 24 h of sampling with an AUC of 90·5% (95% CI 83·3-97·6) for patients with predicted bacterial infection and 94·7% (87·8-100·0) for patients with predicted viral infection. In the external EUCLIDS validation dataset (n=362), the disease class and disease severity predicted organ dysfunction at time of sampling with an AUC of 70·1% (95% CI 44·1-96·2) for patients with predicted bacterial infection and 69·6% (53·1-86·0) for patients with predicted viral infection.

INTERPRETATION

In children evaluated for sepsis, novel host transcriptomic signatures specific for bacterial and viral infection can identify dysregulated host response leading to organ dysfunction.

FUNDING

Australian Government Medical Research Future Fund Genomic Health Futures Mission, Children's Hospital Foundation Queensland, Brisbane Diamantina Health Partners, Emergency Medicine Foundation, Gold Coast Hospital Foundation, Far North Queensland Foundation, Townsville Hospital and Health Services SERTA Grant, and Australian Infectious Diseases Research Centre.

Pediatric Sepsis Phenotypes and Outcome: 5-Year Retrospective Cohort Study in a Single Center in India (2017-2022)

OBJECTIVES

To describe mortality associated with different clinical phenotypes of sepsis in children.

DESIGN

Retrospective study.

SETTING

PICU of a tertiary care center in India from 2017 to 2022.

PATIENTS

Six hundred twelve children (from 2 mo to 17 yr old) with a retrospectively applied diagnosis of sepsis using 2020 guidance.

METHODS

The main outcome was mortality associated with sepsis subtypes. Other analyses included assessment of risk factors, requirement for organ support, and PICU resources used by sepsis phenotype. Clinical data were recorded on a predesigned proforma.

INTERVENTIONS

None.

MEASUREMENTS AND RESULTS

Of the 612 children identified, there were 382 (62%) with sepsis but no multiple organ failure (NoMOF), 48 (8%) with thrombocytopenia-associated MOF (TAMOF), 140 (23%) with MOF without thrombocytopenia, and 40 (6.5%) with sequential MOF (SMOF). Mortality was higher in the SMOF (20/40 [50%]), MOF (62/140 [44%]) and TAMOF (20/48 [42%]) groups, compared with NoMOF group (82/382 [21%] [ p < 0.001]). The requirement for organ support and PICU resources was higher in all phenotypes with MOF as compared with those without MOF. On multivariable analysis elevated lactate and having MOF were associated with greater odds of mortality.

CONCLUSIONS

In this single-center experience of sepsis in India, we found that sepsis phenotypes having MOF were associated with mortality and the requirement of PICU resources. Prospective studies in different regions of the world will help identify a classification of pediatric sepsis that is more widely applicable.

The Pediatric Data Science and Analytics Subgroup of the Pediatric Acute Lung Injury and Sepsis Investigators Network: Use of Supervised Machine Learning Applications in Pediatric Critical Care Medicine Research

OBJECTIVE

Perform a scoping review of supervised machine learning in pediatric critical care to identify published applications, methodologies, and implementation frequency to inform best practices for the development, validation, and reporting of predictive models in pediatric critical care.

DESIGN

Scoping review and expert opinion.

SETTING

We queried CINAHL Plus with Full Text (EBSCO), Cochrane Library (Wiley), Embase (Elsevier), Ovid Medline, and PubMed for articles published between 2000 and 2022 related to machine learning concepts and pediatric critical illness. Articles were excluded if the majority of patients were adults or neonates, if unsupervised machine learning was the primary methodology, or if information related to the development, validation, and/or implementation of the model was not reported. Article selection and data extraction were performed using dual review in the Covidence tool, with discrepancies resolved by consensus.

SUBJECTS

Articles reporting on the development, validation, or implementation of supervised machine learning models in the field of pediatric critical care medicine.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Of 5075 identified studies, 141 articles were included. Studies were primarily (57%) performed at a single site. The majority took place in the United States (70%). Most were retrospective observational cohort studies. More than three-quarters of the articles were published between 2018 and 2022. The most common algorithms included logistic regression and random forest. Predicted events were most commonly death, transfer to ICU, and sepsis. Only 14% of articles reported external validation, and only a single model was implemented at publication. Reporting of validation methods, performance assessments, and implementation varied widely. Follow-up with authors suggests that implementation remains uncommon after model publication.

CONCLUSIONS

Publication of supervised machine learning models to address clinical challenges in pediatric critical care medicine has increased dramatically in the last 5 years. While these approaches have the potential to benefit children with critical illness, the literature demonstrates incomplete reporting, absence of external validation, and infrequent clinical implementation.

Editor's Choice Articles for September

The September 2023 issue and this year has already proven to be important for improving our understanding of pediatric acute respiratory distress syndrome (PARDS); Pediatric Critical Care Medicine (PCCM) has published 16 articles so far. Therefore, my three Editor's Choice articles this month highlight yet more PCCM material about PARDS by covering the use of noninvasive ventilation (NIV), the trajectory in cytokine profile during illness, and a new look at lung mechanics. The PCCM Connections for Readers give us the opportunity to focus on some clinical biomarkers of severity and mortality risk during critical illness.

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.