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

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

Introduction: Differentiating 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. Methods: Genome-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. Results: Two 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. Conclusions: Genome-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

Corticosteroids and pediatric septic shock outcomes: a risk stratified analysis.

The potential benefits of corticosteroids for septic shock may depend on initial mortality risk.We determined associations between corticosteroids and outcomes in children with septic shock who were stratified by initial mortality risk.We conducted a retrospective analysis of an ongoing, multi-center pediatric septic shock clinical and biological database. Using a validated biomarker-based stratification tool (PERSEVERE), 496 subjects were stratified into three initial mortality risk strata (low, intermediate, and high). Subjects receiving corticosteroids during the initial 7 days of admission (n = 252) were compared to subjects who did not receive corticosteroids (n = 244). Logistic regression was used to model the effects of corticosteroids on 28-day mortality and complicated course, defined as death within 28 days or persistence of two or more organ failures at 7 days.Subjects who received corticosteroids had greater organ failure burden, higher illness severity, higher mortality, and a greater requirement for vasoactive medications, compared to subjects who did not receive corticosteroids. PERSEVERE-based mortality risk did not differ between the two groups. For the entire cohort, corticosteroids were associated with increased risk of mortality (OR 2.3, 95% CI 1.3-4.0, p = 0.004) and a complicated course (OR 1.7, 95% CI 1.1-2.5, p = 0.012). Within each PERSEVERE-based stratum, corticosteroid administration was not associated with improved outcomes. Similarly, corticosteroid administration was not associated with improved outcomes among patients with no comorbidities, nor in groups of patients stratified by PRISM.Risk stratified analysis failed to demonstrate any benefit from corticosteroids in this pediatric septic shock cohort

The pediatric sepsis biomarker risk model

Introduction: The 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. Methods: Twelve 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. Results: The 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. Conclusions: The 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

Association between corticosteroids and mortality.

<p>Association between corticosteroids and mortality.</p

Association between corticosteroids and complicated course (CC) based on PRISM tertiles.

<p>Association between corticosteroids and complicated course (CC) based on PRISM tertiles.</p

Clinical and demographic data for the study subjects.

<p>Clinical and demographic data for the study subjects.</p

Clinical and demographic data for the study subjects without comorbidities.

<p>Clinical and demographic data for the study subjects without comorbidities.</p