Michael T. Bigham

Interleukin-8 as a Stratification Tool for Interventional Trials Involving Pediatric Septic Shock

RATIONALE Interventional clinical trials involving children with septic shock would benefit from an efficient preenrollment stratification strategy. OBJECTIVES To test the predictive value of interleukin (IL)-8 for 28-day mortality in pediatric septic shock. METHODS A training data set (n = 40) identified a serum IL-8 of greater than 220 pg/ml as having a 75% sensitivity and specificity for predicting 28-day mortality. This cutoff was then subjected to a series of validation steps. MEASUREMENTS AND MAIN RESULTS Subjects were drawn from two large, independent pediatric septic shock databases. Prospective application of the IL-8 cutoff to validation data set 1 (n = 139) demonstrated 78% sensitivity and 64% specificity for 28-day mortality. A serum IL-8 level of 220 pg/ml or less, however, had a negative predictive value for 28-day mortality of 95% in validation data set 1, which was subsequently applied to an independently generated data set of children with septic shock (validation set 2, n = 193). A serum IL-8 level of 220 pg/ml or less had a negative predictive value for 28-day mortality of 94% when applied to validation set 2. CONCLUSIONS A serum IL-8 level of 220 pg/ml or less, obtained within 24 hours of admission, predicts a high likelihood of survival in children with septic shock. We propose that IL-8 can be used to exclude such patients from interventional clinical trials and ultimately derive a study population with a more favorable risk to benefit ratio when subjected to a study agent.

Developing a clinically feasible personalized medicine approach to pediatric septic shock.

RATIONALE Using microarray data, we previously identified gene expression-based subclasses of septic shock with important phenotypic differences. The subclass-defining genes correspond to adaptive immunity and glucocorticoid receptor signaling. Identifying the subclasses in real time has theranostic implications, given the potential for immune-enhancing therapies and controversies surrounding adjunctive corticosteroids for septic shock. OBJECTIVES To develop and validate a real-time subclassification method for septic shock. METHODS Gene expression data for the 100 subclass-defining genes were generated using a multiplex messenger RNA quantification platform (NanoString nCounter) and visualized using gene expression mosaics. Study subjects (n = 168) were allocated to the subclasses using computer-assisted image analysis and microarray-based reference mosaics. A gene expression score was calculated to reduce the gene expression patterns to a single metric. The method was tested prospectively in a separate cohort (n = 132). MEASUREMENTS AND MAIN RESULTS The NanoString-based data reproduced two septic shock subclasses. As previously, one subclass had decreased expression of the subclass-defining genes. The gene expression score identified this subclass with an area under the curve of 0.98 (95% confidence interval [CI95] = 0.96-0.99). Prospective testing of the subclassification method corroborated these findings. Allocation to this subclass was independently associated with mortality (odds ratio = 2.7; CI95 = 1.2-6.0; P = 0.016), and adjunctive corticosteroids prescribed at physician discretion were independently associated with mortality in this subclass (odds ratio = 4.1; CI95 = 1.4-12.0; P = 0.011). CONCLUSIONS We developed and tested a gene expression-based classification method for pediatric septic shock that meets the time constraints of the critical care environment, and can potentially inform therapeutic decisions.

The pediatric sepsis biomarker risk model

IntroductionThe intrinsic heterogeneity of clinical septic shock is a major challenge. For clinical trials, individual patient management, and quality improvement efforts, it is unclear which patients are least likely to survive and thus benefit from alternative treatment approaches. A robust risk stratification tool would greatly aid decision-making. The objective of our study was to derive and test a multi-biomarker-based risk model to predict outcome in pediatric septic shock.MethodsTwelve candidate serum protein stratification biomarkers were identified from previous genome-wide expression profiling. To derive the risk stratification tool, biomarkers were measured in serum samples from 220 unselected children with septic shock, obtained during the first 24 hours of admission to the intensive care unit. Classification and Regression Tree (CART) analysis was used to generate a decision tree to predict 28-day all-cause mortality based on both biomarkers and clinical variables. The derived tree was subsequently tested in an independent cohort of 135 children with septic shock.ResultsThe derived decision tree included five biomarkers. In the derivation cohort, sensitivity for mortality was 91% (95% CI 70 - 98), specificity was 86% (80 - 90), positive predictive value was 43% (29 - 58), and negative predictive value was 99% (95 - 100). When applied to the test cohort, sensitivity was 89% (64 - 98) and specificity was 64% (55 - 73). In an updated model including all 355 subjects in the combined derivation and test cohorts, sensitivity for mortality was 93% (79 - 98), specificity was 74% (69 - 79), positive predictive value was 32% (24 - 41), and negative predictive value was 99% (96 - 100). False positive subjects in the updated model had greater illness severity compared to the true negative subjects, as measured by persistence of organ failure, length of stay, and intensive care unit free days.ConclusionsThe pediatric sepsis biomarker risk model (PERSEVERE; PEdiatRic SEpsis biomarkEr Risk modEl) reliably identifies children at risk of death and greater illness severity from pediatric septic shock. PERSEVERE has the potential to substantially enhance clinical decision making, to adjust for risk in clinical trials, and to serve as a septic shock-specific quality metric.

The influence of developmental age on the early transcriptomic response of children with septic shock.

Septic shock is a frequent and costly problem among patients in the pediatric intensive care unit (PICU) and is associated with high mortality and devastating survivor morbidity. Genome-wide expression patterns can provide molecular granularity of the host response and offer insight into why large variations in outcomes exist. We derived whole-blood genome-wide expression patterns within 24 h of PICU admission from children with septic shock. We compared the transcriptome between septic shock developmental-age groups defined as neonates (≤28 d, n = 17), infants (1 month to 1 year, n = 62), toddlers (2–5 years, n = 54) and school-age (≥6 years, n = 47) and age-matched controls. Direct intergroup comparisons demonstrated profound changes in neonates, relative to older children. Neonates with septic shock demonstrated reduced expression of genes representing key pathways of innate and adaptive immunity. In contrast to the largely upregulated transcriptome in all other groups, neonates exhibited a predominantly downregulated transcriptome when compared with controls. Neonates and school-age subjects had the most uniquely regulated genes relative to controls. Age-specific studies of the host response are necessary to identify developmentally relevant translational opportunities that may lead to improved sepsis outcomes.

Validation of a gene expression-based subclassification strategy for pediatric septic shock

Objective:Septic shock heterogeneity has important implications for clinical trial implementation and patient management. We previously addressed this heterogeneity by identifying three putative subclasses of children with septic shock based exclusively on a 100-gene expression signature. Here we attempted to prospectively validate the existence of these gene expression-based subclasses in a validation cohort. Design:Prospective observational study involving microarray-based bioinformatics. Setting:Multiple pediatric intensive care units in the United States. Patients:Separate derivation (n = 98) and validation (n = 82) cohorts of children with septic shock. Interventions:None other than standard care. Measurements and Main Results:Gene expression mosaics of the 100 class-defining genes were generated for 82 individual patients in the validation cohort. Using computer-based image analysis, patients were classified into one of three subclasses (“A,” “B,” or “C”) based on color and pattern similarity relative to reference mosaics generated from the original derivation cohort. After subclassification, the clinical database was mined for phenotyping. Subclass A patients had higher illness severity relative to subclasses B and C as measured by maximal organ failure, fewer intensive care unit-free days, and a higher Pediatric Risk of Mortality score. Patients in subclass A were characterized by repression of genes corresponding to adaptive immunity and glucocorticoid receptor signaling. Separate subclass assignments were conducted by 21 individual clinicians using visual inspection. The consensus classification of the clinicians had modest agreement with the computer algorithm. Conclusions:We have validated the existence of subclasses of children with septic shock based on a biologically relevant, 100-gene expression signature. The subclasses have relevant clinical differences.

Interleukin-27 is a novel candidate diagnostic biomarker for bacterial infection in critically ill children

IntroductionDifferentiating between sterile inflammation and bacterial infection in critically ill patients with fever and other signs of the systemic inflammatory response syndrome (SIRS) remains a clinical challenge. The objective of our study was to mine an existing genome-wide expression database for the discovery of candidate diagnostic biomarkers to predict the presence of bacterial infection in critically ill children.MethodsGenome-wide expression data were compared between patients with SIRS having negative bacterial cultures (n = 21) and patients with sepsis having positive bacterial cultures (n = 60). Differentially expressed genes were subjected to a leave-one-out cross-validation (LOOCV) procedure to predict SIRS or sepsis classes. Serum concentrations of interleukin-27 (IL-27) and procalcitonin (PCT) were compared between 101 patients with SIRS and 130 patients with sepsis. All data represent the first 24 hours of meeting criteria for either SIRS or sepsis.ResultsTwo hundred twenty one gene probes were differentially regulated between patients with SIRS and patients with sepsis. The LOOCV procedure correctly predicted 86% of the SIRS and sepsis classes, and Epstein-Barr virus-induced gene 3 (EBI3) had the highest predictive strength. Computer-assisted image analyses of gene-expression mosaics were able to predict infection with a specificity of 90% and a positive predictive value of 94%. Because EBI3 is a subunit of the heterodimeric cytokine, IL-27, we tested the ability of serum IL-27 protein concentrations to predict infection. At a cut-point value of ≥5 ng/ml, serum IL-27 protein concentrations predicted infection with a specificity and a positive predictive value of >90%, and the overall performance of IL-27 was generally better than that of PCT. A decision tree combining IL-27 and PCT improved overall predictive capacity compared with that of either biomarker alone.ConclusionsGenome-wide expression analysis has provided the foundation for the identification of IL-27 as a novel candidate diagnostic biomarker for predicting bacterial infection in critically ill children. Additional studies will be required to test further the diagnostic performance of IL-27.The microarray data reported in this article have been deposited in the Gene Expression Omnibus under accession number GSE4607.

Decreasing Handoff-Related Care Failures in Children’s Hospitals

BACKGROUND AND OBJECTIVE: Patient handoffs in health care require transfer of information, responsibility, and authority between providers. Suboptimal patient handoffs pose a serious safety risk. Studies demonstrating the impact of improved patient handoffs on care failures are lacking. The primary objective of this study was to evaluate the effect of a multihospital collaborative designed to decrease handoff-related care failures. METHODS: Twenty-three children’s hospitals participated in a quality improvement collaborative aimed at reducing handoff-related care failures. The improvement was guided by evidence-based recommendations regarding handoff intent and content, standardized handoff tools/methods, and clear transition of responsibility. Hospitals tailored handoff elements to locally important handoff types. Handoff-related care failures were compared between baseline and 3 intervention periods. Secondary outcomes measured compliance to specific change package elements and balancing measure of staff satisfaction. RESULTS: Twenty-three children’s hospitals evaluated 7864 handoffs over the 12-month study period. Handoff-related care failures decreased from baseline (25.8%) to the final intervention period (7.9%) (P < .05). Significant improvement was observed in every handoff type studied. Compliance to change package elements improved (achieving a common understanding about the patient from 86% to 96% [P < .05]; clear transition of responsibility from 92% to 96% [P < .05]; and minimized interruptions and distractions from 84% to 90% [P < .05]) as did overall satisfaction with the handoff (from 55% to 70% [P < .05]). CONCLUSIONS: Implementation of a standardized evidence-based handoff process across 23 children’s hospitals resulted in a significant decrease in handoff-related care failures, observed over all handoff types. Compliance to critical components of the handoff process improved, as did provider satisfaction.

Testing the Prognostic Accuracy of the Updated Pediatric Sepsis Biomarker Risk Model

Background We previously derived and validated a risk model to estimate mortality probability in children with septic shock (PERSEVERE; PEdiatRic SEpsis biomarkEr Risk modEl). PERSEVERE uses five biomarkers and age to estimate mortality probability. After the initial derivation and validation of PERSEVERE, we combined the derivation and validation cohorts (n = 355) and updated PERSEVERE. An important step in the development of updated risk models is to test their accuracy using an independent test cohort. Objective To test the prognostic accuracy of the updated version PERSEVERE in an independent test cohort. Methods Study subjects were recruited from multiple pediatric intensive care units in the United States. Biomarkers were measured in 182 pediatric subjects with septic shock using serum samples obtained during the first 24 hours of presentation. The accuracy of PERSEVERE 28-day mortality risk estimate was tested using diagnostic test statistics, and the net reclassification improvement (NRI) was used to test whether PERSEVERE adds information to a physiology-based scoring system. Results Mortality in the test cohort was 13.2%. Using a risk cut-off of 2.5%, the sensitivity of PERSEVERE for mortality was 83% (95% CI 62–95), specificity was 75% (68–82), positive predictive value was 34% (22–47), and negative predictive value was 97% (91–99). The area under the receiver operating characteristic curve was 0.81 (0.70–0.92). The false positive subjects had a greater degree of organ failure burden and longer intensive care unit length of stay, compared to the true negative subjects. When adding PERSEVERE to a physiology-based scoring system, the net reclassification improvement was 0.91 (0.47–1.35; p<0.001). Conclusions The updated version of PERSEVERE estimates mortality probability reliably in a heterogeneous test cohort of children with septic shock and provides information over and above a physiology-based scoring system.

Corticosteroids are associated with repression of adaptive immunity gene programs in pediatric septic shock.

RATIONALE Corticosteroids are prescribed commonly for patients with septic shock, but their use remains controversial and concerns remain regarding side effects. OBJECTIVES To determine the effect of adjunctive corticosteroids on the genomic response of pediatric septic shock. METHODS We retrospectively analyzed an existing transcriptomic database of pediatric septic shock. Subjects receiving any formulation of systemic corticosteroids at the time of blood draw for microarray analysis were classified in the septic shock corticosteroid group. We compared normal control subjects (n = 52), a septic shock no corticosteroid group (n = 110), and a septic shock corticosteroid group (n = 70) using analysis of variance. Genes differentially regulated between the no corticosteroid group and the corticosteroid group were analyzed using Ingenuity Pathway Analysis. MEASUREMENTS AND MAIN RESULTS The two study groups did not differ with respect to illness severity, organ failure burden, mortality, or mortality risk. There were 319 gene probes differentially regulated between the no corticosteroid group and the corticosteroid group. These genes corresponded predominately to adaptive immunity-related signaling pathways, and were down-regulated relative to control subjects. Notably, the degree of down-regulation was significantly greater in the corticosteroid group, compared with the no corticosteroid group. A similar pattern was observed for genes corresponding to the glucocorticoid receptor signaling pathway. CONCLUSIONS Administration of corticosteroids in pediatric septic shock is associated with additional repression of genes corresponding to adaptive immunity. These data should be taken into account when considering the benefit to risk ratio of adjunctive corticosteroids for septic shock.

Post-ICU admission fluid balance and pediatric septic shock outcomes: A risk-stratified analysis

Objective:Observed associations between fluid balance and septic shock outcomes are likely confounded by initial mortality risk. We conducted a risk-stratified analysis of the association between post-ICU admission fluid balance and pediatric septic shock outcomes. Design:Retrospective analysis of an ongoing multicenter pediatric septic shock clinical and biological database. Setting:Seventeen PICUs in the United States. Patients:Three hundred and seventeen children with septic shock. Interventions:None. Measurements and Main Results:We stratified subjects into three mortality risk categories (low, intermediate, and high) using a validated biomarker-based stratification tool. Within each category, we assessed three fluid balance variables: total fluid intake/kg/d during the first 24 hours, percent positive fluid balance during the first 24 hours, and cumulative percent positive fluid balance up to 7 days. We used logistic regression to estimate the effect of fluid balance on the odds of 28-day mortality, and on complicated course, which we defined as either death within 28 days or persistence of two or more organ failures at 7 days. There were 40 deaths, and 91 subjects had a complicated course. Increased cumulative percent positive fluid balance was associated with mortality in the low-risk cohort (n = 204; odds ratio, 1.035; 95% CI, 1.004–1.066) but not in the intermediate- and high-risk cohorts. No other associations with mortality were observed. Fluid intake, percent positive fluid balance in the first 24 hours, and cumulative percent positive fluid balance were all associated with increased odds of a complicated course in the low-risk cohort but not in the intermediate- and high-risk cohorts. Conclusions:When stratified for mortality risk, increased fluid intake and positive fluid balance after ICU admission are associated with worse outcomes in pediatric septic shock patients with a low initial mortality risk but not in patients at moderate or high mortality risk.