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Summary: 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 NIH R35GM126943 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 NIH R21GM151703. R.K. was supported by R01GM139967.

BackgroundInfluenza virus is responsible for a large global burden of disease, especially in children. Multiple Organ Dysfunction Syndrome (MODS) is a life-threatening and fatal complication of severe influenza infection.MethodsWe measured RNA expression of 469 biologically plausible candidate genes in children admitted to North American pediatric intensive care units with severe influenza virus infection with and without MODS. Whole blood samples from 191 influenza-infected children (median age 6.4 years, IQR: 2.2, 11) were collected a median of 27 hours following admission; for 45 children a second blood sample was collected approximately seven days later. Extracted RNA was hybridized to NanoString mRNA probes, counts normalized, and analyzed using linear models controlling for age and bacterial co-infections (FDR q

Abstract Background Severe critical illness-induced immune suppression, termed immunoparalysis, is associated with longer duration of organ dysfunction in septic children. mRNA studies have suggested differential benefit of hydrocortisone in septic children based on their immune phenotype, but this has not been shown using a functional readout of the immune response. This study represents a secondary analysis of a prospectively conducted immunophenotyping study of pediatric severe sepsis to test the hypothesis that hydrocortisone will be differentially associated with clinical outcomes in children with or without immunoparalysis. Methods Children with severe sepsis/septic shock underwent blood sampling within 48 h of sepsis onset. Immune function was measured by quantifying whole blood ex vivo LPS-induced TNFα production capacity, with a TNFα response

Background: Multisystem inflammatory syndrome in children (MIS-C) consensus criteria were designed for maximal sensitivity and therefore capture patients with acute COVID-19 pneumonia. Methods: We performed unsupervised clustering on data from 1,526 patients (684 labeled MIS-C by clinicians)

BackgroundSevere innate immune suppression, termed immunoparalysis, is associated with increased risks of nosocomial infection and mortality in children with septic shock. Currently, immunoparalysis cannot be clinically diagnosed in children, and mechanisms remain unclear. Transcriptomic studies identify subsets of septic children with downregulation of genes within adaptive immune pathways, but assays of immune function have not been performed as part of these studies, and little is known about transcriptomic profiles of children with immunoparalysis.MethodsWe performed a nested case-control study to identify differences in RNA expression patterns between children with septic shock with immunoparalysis (defined as lipopolysaccharide (LPS)-induced tumor necrosis factor (TNF)α response < 200 pg/ml) vs those with normal LPS-induced TNFα response. Children were enrolled within 48 hours of the onset of septic shock and divided into two groups based on LPS-induced TNFα response. RNA was extracted from whole blood for RNAseq, differential expression analyses using DESeq2 software, and pathway analyses using Ingenuity Pathway Analysis.Results32 children were included in analyses. Comparing those with immunoparalysis (n =19) to those with normal TNFα response (n = 13), 2,303 transcripts were differentially expressed with absolute value fold change ≥ 1.5 and false discovery rate ≤ 0.05. The majority of downregulated pathways in children with immunoparalysis were pathways that involved interactions between innate and adaptive immune cells necessary for cell-mediated immunity, crosstalk between dendritic cells and natural killer cells, and natural killer cell signaling pathways. Upregulated pathways included those involved in humoral immunity (T helper cell type 2), corticotropin signaling, platelet activation (GP6 signaling), and leukocyte migration and extravasation.ConclusionsOur study suggests that gene expression data might be useful to identify children with immunoparalysis and identifies several key differentially regulated pathways involved in both innate and adaptive immunity. Our ongoing work in this area aims to dissect interactions between innate and adaptive immunity in septic children and to more fully elucidate patient-specific immunologic pathophysiology to guide individualized immunotherapeutic targets.

Background: Although some pediatric sepsis survivors experience worsening health-related quality of life (HRQL), many return to their pre-illness HRQL. Whether children can improve beyond baseline is not known. We examined a cohort of pediatric sepsis survivors to determine if those with baseline HRQL scores below the population mean could exhibit ≥10% improvement and evaluated factors associated with improvement.Methods: In this secondary analysis of the Life After Pediatric Sepsis Evaluation prospective study, children aged 1 month to 18 years admitted to 12 academic PICUs in the United States with community-acquired septic shock who survived to 3 months and had baseline HRQL scores ≤ 80 (i.e., excluding those with good baseline HRQL to allow for potential improvement) were included. HRQL was measured using the Pediatric Quality of Life Inventory or Stein-Jessop Functional Status Scale.Findings: One hundred and seventeen children were eligible. Sixty-one (52%) had ≥ 10% improvement in HRQL by 3 months. Lower pre-sepsis HRQL was associated with increased odds of improvement at 3 months [aOR = 1.08, 95% CI (1.04–1.11), p < 0.001] and 12 months [OR = 1.05, 95% CI (1.02–1.11), p = 0.005]. Improvement in HRQL was most prevalent at 3 month follow-up; at 12 month follow-up, improvement was more sustained among children without severe developmental delay compared to children with severe developmental delay.Interpretation: More than half of these children with community acquired septic shock experienced at least a 10% improvement in HRQL from baseline to 3 months. Children with severe developmental delay did not sustain this improvement at 12 month follow-up.

Background:. Influenza virus is a major cause of acute hypoxemic respiratory failure. Early identification of patients who will suffer severe complications can help stratify patients for clinical trials and plan for resource use in case of pandemic. Objective:. We aimed to identify which clinical variables best predict prolonged acute hypoxemic respiratory failure in influenza-infected critically ill children. Acute hypoxemic respiratory failure was defined using hypoxemia cutoffs from international consensus definitions of acute respiratory distress syndrome in patients with ventilatory support. Prolonged acute hypoxemic respiratory failure was defined by acute hypoxemic respiratory failure criteria still present at PICU day 7. Derivation Cohort:. In this prospective multicenter study across 34 PICUs from November 2009 to April 2018, we included children (< 18 yr) without comorbid risk factors for severe disease. Validation Cohort:. We used a Monte Carlo cross validation method with N2 random train-test splits at a 70–30% proportion per model. Prediction Model:. Using clinical data at admission (day 1) and closest to 8 am on PICU day 2, we calculated the area under the receiver operating characteristic curve using random forests machine learning algorithms and logistic regression. Results:. We included 258 children (median age = 6.5 yr) and 11 (4.2%) died. By day 2, 65% (n = 165) had acute hypoxemic respiratory failure dropping to 26% (n = 67) with prolonged acute hypoxemic respiratory failure by day 7. Those with prolonged acute hypoxemic respiratory failure had a longer ICU stay (16.5 vs 4.0 d; p < 0.001) and higher mortality (13.4% vs 1.0%). A multivariable model using random forests with 10 admission and eight day 2 variables performed best (0.93 area under the receiver operating characteristic curve; 95 CI%: 0.90–0.95) where respiratory rate, Fio2, and pH on day 2 were the most important factors. Conclusions:. In this prospective multicentric study, most children with influenza virus–related respiratory failure with prolonged acute hypoxemic respiratory failure can be identified early in their hospital course applying machine learning onto routine clinical data. Further validation is needed prior to bedside implementation.

Objectives:. Sepsis is responsible for a substantial proportion of global childhood morbidity and mortality. However, evidence demonstrates major inaccuracies in the use of the term “sepsis” in clinical practice, coding, and research. Current and previous definitions of sepsis have been developed using expert consensus but the specific criteria used to identify children with sepsis have not been rigorously evaluated. Therefore, as part of the Society of Critical Care Medicine’s Pediatric Sepsis Definition Taskforce, we will conduct a systematic review to synthesize evidence on individual factors, clinical criteria, or illness severity scores that may be used to identify children with infection who have or are at high risk of developing sepsis-associated organ dysfunction and separately those factors, criteria, and scores that may be used to identify children with sepsis who are at high risk of progressing to multiple organ dysfunction or death. Data Sources:. We will identify eligible studies by searching the following databases: MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials. Study Selection:. We will include all randomized trials and cohort studies published between January 1, 2004, and March 16, 2020. Data Extraction:. Data extraction will include information related to study characteristics, population characteristics, clinical criteria, and outcomes. Data Synthesis:. We will calculate sensitivity and specificity of each criterion for predicting sepsis and conduct a meta-analysis if the data allow. We will also provide pooled estimates of overall hospital mortality. Conclusions:. The potential risk factors, clinical criteria, and illness severity scores from this review which identify patients with infection who are at high risk of developing sepsis-associated organ dysfunction and/or progressing to multiple organ dysfunction or death will be used to inform the next steps of the Pediatric Sepsis Definition Taskforce.

The inflammatory response in pediatric sepsis is highly dynamic and includes both pro- and anti-inflammatory elements that involve the innate and adaptive immune systems. While the pro-inflammatory response is responsible for the initial clinical signs and symptoms of sepsis, a concurrent compensatory anti-inflammatory response often results in an occult, but highly clinically relevant, form of acquired immunodeficiency. When severe, this is termed “immunoparalysis” and is associated with increased risks for nosocomial infection, prolonged organ dysfunction, and death. This review focuses on the pathophysiology and clinical implications of both over- and under-active immune function in septic children. Host-, disease-, and treatment-specific risk factors for immunoparalysis are reviewed along with immune phenotype-specific approaches for immunomodulation in pediatric sepsis which are currently the subject of clinical trials.

Background: Mannose-binding lectin (MBL) is an innate immune protein with strong biologic plausibility for protecting against influenza virus-related sepsis and bacterial co-infection. In an autopsy cohort of 105 influenza-infected young people, carriage of the deleterious MBL gene MBL2_Gly54Asp(“B”) mutation was identified in 5 of 8 individuals that died from influenza-methicillin-resistant Staphylococcus aureus (MRSA) co-infection. We evaluated MBL2 variants known to influence MBL levels with pediatric influenza-related critical illness susceptibility and/or severity including with bacterial co-infections.Methods: We enrolled children and adolescents with laboratory-confirmed influenza infection across 38 pediatric intensive care units from November 2008 to June 2016. We sequenced MBL2 “low-producer” variants rs11003125(“H/L”), rs7096206(“Y/X”), rs1800450Gly54Asp(“B”), rs1800451Gly57Glu(“C”), rs5030737Arg52Cys(“D”) in patients and biologic parents. We measured serum levels and compared complement activity in low-producing homozygotes (“B/B,” “C/C”) to HYA/HYA controls. We used a population control of 1,142 healthy children and also analyzed family trios (PBAT/HBAT) to evaluate disease susceptibility, and nested case-control analyses to evaluate severity.Results: We genotyped 420 patients with confirmed influenza-related sepsis: 159 (38%) had acute lung injury (ALI), 165 (39%) septic shock, and 30 (7%) died. Although bacterial co-infection was diagnosed in 133 patients (32%), only MRSA co-infection (n = 33, 8% overall) was associated with death (p < 0.0001), present in 11 of 30 children that died (37%). MBL2 variants predicted serum levels and complement activation as expected. We found no association between influenza-related critical illness susceptibility and MBL2 variants using family trios (633 biologic parents) or compared to population controls. MBL2 variants were not associated with admission illness severity, septic shock, ALI, or bacterial co-infection diagnosis. Carriage of low-MBL producing MBL2 variants was not a risk factor for mortality, but children that died did have higher carriage of one or more B alleles (OR 2.3; p = 0.007), including 7 of 11 with influenza MRSA-related death (vs. 2 of 22 survivors: OR 14.5, p = 0.0002).Conclusions:MBL2 variants that decrease MBL levels were not associated with susceptibility to pediatric influenza-related critical illness or with multiple measures of critical illness severity. We confirmed a prior report of higher B allele carriage in a relatively small number of young individuals with influenza-MRSA associated death.

RationaleEffective immunomodulatory therapies for children with life-threatening “cytokine storm” triggered by acute influenza infection are lacking. Understanding the immune profiles of children progressing to severe lung injury and/or septic shock could provide insight into pathogenesis.ObjectivesTo compare the endotracheal and serum cytokine profiles of children with influenza-related critical illness and to identify their associations with severe influenza-associated complications.MethodsChildren with influenza-related critical illness were enrolled across 32 hospitals in development (N = 171) and validation (N = 73) cohorts (December 2008 through May 2016). Concentrations of 42 cytokines were measured in serum and endotracheal samples and clustered into modules of covarying cytokines. Relative concentrations of cytokines and cytokine modules were tested for associations with acute lung injury (ALI), shock requiring vasopressors, and death/ECMO.Measurements and main resultsModules of covarying cytokines were more significantly associated with disease severity than individual cytokines. In the development cohort, increased levels of a serum module containing IL6, IL8, IL10, IP10, GCSF, MCP1, and MIP1α [shock odds ratio (OR) = 3.37, family-wise error rate (FWER) p

Summary: Background: Lower respiratory tract infections (LRTI) are a leading cause of critical illness and mortality in mechanically ventilated children; however, the pathogenic microbes frequently remain unknown. We combined traditional diagnostics with metagenomic next generation sequencing (mNGS) to evaluate the cause of LRTI in critically ill children. Methods: We conducted a prospective, multicentre cohort study of critically ill children aged 31 days to 17 years with respiratory failure requiring mechanical ventilation (>72 h) in the USA. By combining bacterial culture and upper respiratory viral PCR testing with mNGS of tracheal aspirate collected from all patients within 24 h of intubation, we determined the prevalence, age distribution, and seasonal variation of viral and bacterial respiratory pathogens detected by either method in children with or without LRTI. Findings: Between Feb 26, 2015, and Dec 31, 2017, of the 514 enrolled patients, 397 were eligible and included in the study (276 children with LRTI and 121 with no evidence of LRTI). A presumptive microbiological cause was identified in 255 (92%) children with LRTI, with respiratory syncytial virus (127 [46%]), Haemophilus influenzae (70 [25%]), and Moraxella catarrhalis (65 [24%]) being most prevalent. mNGS identified uncommon pathogens including Ureaplasma parvum and Bocavirus. Co-detection of viral and bacterial pathogens occurred in 144 (52%) patients. Incidental carriage of potentially pathogenic microbes occurred in 82 (68%) children without LRTI, with rhinovirus (30 [25%]) being most prevalent. Respiratory syncytial virus (p

Critical illness comprises a heterogeneous group of serious medical conditions that typically involve an initial proinflammatory process. A compensatory anti-inflammatory response may occur that, if severe and persistent, places the patient at high risk for adverse outcomes including secondary infection and death. Monitoring strategies can identify these patients through measurement of innate and adaptive immune function. Reductions in monocyte HLA-DR expression, reduced cytokine production capacity, increased inhibitory cell surface molecule expression, and lymphopenia have all been associated with this immune-suppressed state. Intriguing data suggest that critical illness-induced immune suppression may be reversible with agents such as interferon-γ, granulocyte macrophage colony-stimulating factor, interleukin 7, or anti-programmed death-1 therapy. Future approaches for characterization of patient-specific immune derangements and individualized treatment could revolutionize how we recognize and prevent complications in critically ill patients., (©2016 American Association of Critical-Care Nurses.)