Pediatric Sepsis Biomarker Risk Model-II: Redefining the Pediatric Sepsis Biomarker Risk Model With Septic Shock Phenotype. (Patel)

Wong HR, et al. Pediatric Sepsis Biomarker Risk Model-II: Redefining the Pediatric Sepsis Biomarker Risk Model With Septic Shock Phenotype. Crit Care Med. 2016 Nov;44(11):2010-2017.

OBJECTIVE: The Pediatric Sepsis Biomarker Risk Model (PERSEVERE), a pediatric sepsis risk model, uses biomarkers to estimate baseline mortality risk for pediatric septic shock. It is unknown how PERSEVERE performs within distinct septic shock phenotypes. We tested PERSEVERE in children with septic shock and thrombocytopenia-associated multiple organ failure (TAMOF), and in those without new onset thrombocytopenia but with multiple organ failure (MOF).

DESIGN: PERSEVERE-based mortality risk was generated for each study subject (n = 660). A priori, we determined that if PERSEVERE did not perform well in both the TAMOF and the MOF cohorts, we would revise PERSEVERE to incorporate admission platelet counts.

SETTING: Multiple PICUs in the United States.

INTERVENTIONS: Standard care.

MEASUREMENTS AND MAIN RESULTS: PERSEVERE performed well in the TAMOF cohort (areas under the receiver operating characteristic curves [AUC], 0.84 [95% CI, 0.77-0.90]), but less well in the MOF cohort (AUC, 0.71 [0.61-0.80]). PERSEVERE was revised using 424 subjects previously reported in the derivation phase. PERSEVERE-II had an AUC of 0.89 (0.85-0.93) and performed equally well across TAMOF and MOF cohorts. PERSEVERE-II performed well when tested in 236 newly enrolled subjects. Sample size calculations for a clinical trial testing the efficacy of plasma exchange for children with septic shock and TAMOF indicated PERSEVERE-II-based stratification could substantially reduce the number of patients necessary, when compared with no stratification.

CONCLUSIONS: Testing PERSEVERE in the context of septic shock phenotypes prompted a revision incorporating platelet count. PERSEVERE-II performs well upon testing, independent of TAMOF or MOF status. PERSEVERE-II could potentially serve as a prognostic enrichment tool.

Plasma Biomarkers of Brain Injury as Diagnostic Tools and Outcome Predictors After Extracorporeal Membrane Oxygenation. (Patel)

Bembea MM, Rizkalla N, Freedy J, et al. Plasma Biomarkers of Brain Injury as Diagnostic Tools and Outcome  Predictors After Extracorporeal Membrane Oxygenation. Crit Care Med. 2015 Oct;43(10):2202-11.

OBJECTIVE: To determine if elevations in plasma brain injury biomarkers are associated with outcome at hospital discharge in children who require extracorporeal membrane oxygenation.

DESIGN: Prospective observational study.

SETTING: Single tertiary-care academic center.

PARTICIPANTS: Eighty children who underwent extracorporeal membrane oxygenation between June 2010 and December 2013.


MEASUREMENTS AND MAIN RESULTS: We measured six brain injury biomarkers (glial fibrillary acidic protein, monocyte chemoattractant protein 1/chemokine (C-C motif) ligand 2, neuron-specific enolase, S100b, intercellular adhesion molecule-5, and brain-derived neurotrophic factor) daily during extracorporeal membrane oxygenation, using an electrochemiluminescent multiplex assay. We recorded clinical, neuroimaging, and extracorporeal membrane oxygenation course data. We analyzed the association of biomarker concentrations with favorable versus unfavorable outcome at hospital discharge. Favorable outcome was defined as Pediatric Cerebral Performance Category 1, 2, or no change from baseline. Patients had a median age of 3 days (interquartile range, 1 d-10 mo), and 56% were male. Thirty-three of 80 (41%) had unfavorable outcome, and 22 of 70 (31%) had abnormal neuroimaging findings during or after extracorporeal membrane oxygenation. Peak concentrations were significantly higher in patients with unfavorable outcome than in those with favorable outcome for glial fibrillary acidic protein (p = 0.002), monocyte chemoattractant protein 1/chemokine (C-C motif) ligand 2 (p = 0.030), neuron-specific enolase (p = 0.006), and S100b (p = 0.015) and in patients with versus without abnormal neuroimaging findings for glial fibrillary acidic protein (p = 0.001) and intercellular adhesion molecule-5 (p = 0.001). The area under the receiver operator characteristic curve for unfavorable outcome was 0.73 for a noncollinear biomarker combination. After removing collinear biomarkers, the adjusted odds ratios for unfavorable outcome were 2.89 (95% CI, 1.09-7.73) for neuron-specific enolase, using a cutoff of 62.0 ng/mL, and 2.15 (95% CI, 1.06-4.38) for glial fibrillary acidic protein, using a cutoff of 0.46 ng/mL.

CONCLUSIONS: Elevated plasma brain injury biomarker concentrations during the extracorporeal membrane oxygenation course are associated with unfavorable outcome and/or the presence of neuroimaging abnormalities. Combinations of brain-specific proteins increase the sensitivity and specificity for outcome prediction.

Metabolomics as a novel approach for early diagnosis of pediatric septic shock and its mortality. (Fortenberry)

Am J Respir Crit Care Med. 2013 May 1;187(9):967-76. PMID: 23471468

Rationale: Septic shock is a significant cause of morbidity and mortality in the pediatric population. Early recognition of septic shock and appropriate treatment increase survival rate; thus, developing new diagnostic tools may improve patients’ outcomes.

Objectives: To determine whether a metabolomics approach could be useful in the diagnosis and prognosis of septic shock in pediatric intensive care unit (PICUs).

Methods: Serum samples were collected from 60 patients with septic shock, 40 PICU patients with systemic inflammatory response syndrome (not suspected of having an infection), and 40 healthy children. Proton nuclear magnetic resonance spectroscopy spectra were analyzed and quantified using targeted profiling methodology.

Measurements and Main Results: Multivariate statistical analysis was applied to detect specific patterns in metabolic profiles and to highlight differences between patient samples. Supervised analysis afforded good predictive models and managed to separate patient populations. Some of the metabolite concentrations identified in serum samples changed markedly, indicating their influence on the separation between patient groups. These metabolites represent a composite biopattern of the pediatric metabolic response to septic shock and might be considered as the basis for a biomarker panel for the diagnosis of septic shock and its mortality in PICU.

Conclusions: Our results indicate that nuclear magnetic resonance metabolite profiling might serve as a promising approach for the diagnosis and prediction of mortality in septic shock in a pediatric population and that quantitative metabolomics methods can be applied in the clinical evaluations of pediatric septic shock.

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