Nick Anas

Pulmonary hypertension in infants with bronchopulmonary dysplasia

Seventeen children with oxygen-dependent bronchopulmonary dysplasia, right ventricular hypertrophy, and Doppler echocardiographic evidence of pulmonary hypertension were studied by cardiac catheterization. Fifteen of these patients had pulmonary hypertension when placed in room air; six of these 15 patients were shown to have large systemic-to-pulmonary collateral vessels. The hemodynamic responses to oxygen and hydralazine were evaluated. Five patients developed normal pulmonary artery pressure while receiving supplemental oxygen and were not studied further. Of the remaining ten patients, the six patients with large, hemodynamically significant collateral vessels all had deleterious reactions to hydralazine. Two of the four patients without collateral pulmonary circulation responded to hydralazine with further reductions in mean pulmonary artery pressure. Five of the ten patients who had persistent pulmonary hypertension while receiving oxygen have died. Cardiac catheterization and angiography may provide important diagnostic, therapeutic, and prognostic information in patients with pulmonary hypertension complicating bronchopulmonary dysplasia.

High-frequency oscillatory ventilation in pediatric respiratory failure: A multicenter experience

ObjectiveThe use of high-frequency oscillatory ventilation (HFOV) has increased dramatically in the management of respiratory failure in pediatric patients. We surveyed ten pediatric centers that frequently use high-frequency oscillation to describe current clinical practice and to examine factors related to improved outcomes. DesignRetrospective, observational questionnaire study. SettingTen tertiary care pediatric intensive care units. PatientsTwo hundred ninety patients managed with HFOV between January 1997 and June 1998. InterventionsNone. Measurements and Main ResultsPatients were classified according to presence or absence of preexisting lung disease, symptomatic respiratory syncytial virus infection, or presence of cyanotic heart disease or residual right-to-left intracardiac shunt. In addition, patients for whom HFOV acutely failed were analyzed separately. Those patients with preexisting lung disease were significantly smaller, had a significantly higher incidence of pulmonary infection as the triggering etiology, and had a significantly greater duration of conventional ventilation before institution of HFOV compared with patients without preexisting lung disease. Stepwise logistic regression was used to predict mortality and the occurrence of chronic lung disease in survivors. In patients without preexisting lung disease, the model predicted a 70% probability of death when the oxygenation index (OI) after 24 hrs was 28 in the immunocompromised patients and 64 in the patients without immunocompromise. In the immunocompromised patients, the model predicted a 90% probability of death when the OI after 24 hrs was 58. In survivors without preexisting lung disease, the model predicted a 70% probability of developing chronic lung disease when the OI at 24 hrs was 31 in the patients with sepsis syndrome and 50 in the patients without sepsis syndrome. In the patients with sepsis syndrome, the model predicted a 90% probability of developing chronic lung disease when the OI at 24 hrs was 45. ConclusionsGiven the number of centers involved and the size of the database, we feel that our results broadly reflect current practice in the use of HFOV in pediatric patients. These results may help in deciding which patients are most likely to benefit from aggressive intervention by using extracorporeal techniques and may help identify high-risk populations appropriate for prospective study of innovative modes of supporting gas exchange (e.g., partial liquid breathing or intratracheal pulmonary ventilation).

Genomic expression profiling across the pediatric systemic inflammatory response syndrome, sepsis, and septic shock spectrum

Objectives:To advance our biological understanding of pediatric septic shock, we measured the genome-level expression profiles of critically ill children representing the systemic inflammatory response syndrome (SIRS), sepsis, and septic shock spectrum. Design:Prospective observational study involving microarray-based bioinformatics. Setting:Multiple pediatric intensive care units in the United States. Patients:Children ≤10 years of age: 18 normal controls, 22 meeting criteria for SIRS, 32 meeting criteria for sepsis, and 67 meeting criteria for septic shock on day 1. The available day 3 samples included 20 patients still meeting sepsis criteria, 39 patients still meeting septic shock criteria, and 24 patients meeting the exclusive day 3 category, SIRS resolved. Interventions:None other than standard care. Measurements and Main Results:Longitudinal analyses were focused on gene expression relative to control samples and patients having paired day 1 and day 3 samples. The longitudinal analysis focused on up-regulated genes revealed common patterns of up-regulated gene expression, primarily corresponding to inflammation and innate immunity, across all patient groups on day 1. These patterns of up-regulated gene expression persisted on day 3 in patients with septic shock, but not to the same degree in the other patient classes. The longitudinal analysis focused on down-regulated genes demonstrated gene repression corresponding to adaptive immunity-specific signaling pathways and was most prominent in patients with septic shock on days 1 and 3. Gene network analyses based on direct comparisons across the SIRS, sepsis, and septic shock spectrum, and all available patients in the database, demonstrated unique repression of gene networks in patients with septic shock corresponding to major histocompatibility complex antigen presentation. Finally, analyses focused on repression of genes corresponding to zinc-related biology demonstrated that this pattern of gene repression is unique to patients with septic shock. Conclusions:Although some common patterns of gene expression exist across the pediatric SIRS, sepsis, and septic shock spectrum, septic shock is particularly characterized by repression of genes corresponding to adaptive immunity and zinc-related biology.

Identification of pediatric septic shock subclasses based on genome-wide expression profiling

BackgroundSeptic shock is a heterogeneous syndrome within which probably exist several biological subclasses. Discovery and identification of septic shock subclasses could provide the foundation for the design of more specifically targeted therapies. Herein we tested the hypothesis that pediatric septic shock subclasses can be discovered through genome-wide expression profiling.MethodsGenome-wide expression profiling was conducted using whole blood-derived RNA from 98 children with septic shock, followed by a series of bioinformatic approaches targeted at subclass discovery and characterization.ResultsThree putative subclasses (subclasses A, B, and C) were initially identified based on an empiric, discovery-oriented expression filter and unsupervised hierarchical clustering. Statistical comparison of the three putative subclasses (analysis of variance, Bonferonni correction, P < 0.05) identified 6,934 differentially regulated genes. K-means clustering of these 6,934 genes generated 10 coordinately regulated gene clusters corresponding to multiple signaling and metabolic pathways, all of which were differentially regulated across the three subclasses. Leave one out cross-validation procedures indentified 100 genes having the strongest predictive values for subclass identification. Forty-four of these 100 genes corresponded to signaling pathways relevant to the adaptive immune system and glucocorticoid receptor signaling, the majority of which were repressed in subclass A patients. Subclass A patients were also characterized by repression of genes corresponding to zinc-related biology. Phenotypic analyses revealed that subclass A patients were younger, had a higher illness severity, and a higher mortality rate than patients in subclasses B and C.ConclusionGenome-wide expression profiling can identify pediatric septic shock subclasses having clinically relevant phenotypes.

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.

Dobutamine pharmacokinetics and pharmacodynamics in pediatric intensive care patients.

ObjectiveTo evaluate the pharmacokinetics and pharmacodynamics of dobutamine in critically ill children. DesignA prospective study of pediatric patients receiving continuous infusions of dobutamine in a stepwise format from 2.5 to 10.0 μg/kg/min. SettingA pediatric critical care unit. PatientsTwelve children ranging in age from 1 month to 17 yrs with primary medical conditions. MeasurementsPlasma dobutamine concentrations and hemodynamic responses were measured at each infusion rate at steady state. Dose response data were analyzed to determine the threshold or minimum plasma dobutamine concentration necessary for discernible hemodynamic effects. Main ResultsDobutamine plasma clearance rates ranged from 40 to 130 mL/kg/min. Each patient presented a linear increase in the plasma dobutamine concentration at each infusion rate (r2=.97, p < .001). Plasma clearance rate vs. actual dobutamine concentration did not vary. Cardiac output, BP, and heart rate increased 30%, 17%, and 7%, respectively, at maximal dose. The dobutamine concentration thresholds for changes in cardiac output, BP, and heart rate were 13 ±PT 6, 23 ±PT 14, and 65 ±PT 30 ng/mL, respectively. ConclusionsThere was no effect of plasma dobutamine concentration or infusion rate on plasma clearance rate. For this group of patients, over the range of the intravenous doses studied, dobutamine pharmacokinetics followed a first-order kinetic model. Threshold values for dobutamine usually show increases in cardiac output before changes in heart rate. These data demonstrate that dobutamine is an effective inotropic agent in critically ill pediatric patients and has minimal chronotropic action. (Crit Care Med 1992; 20:601–608)

Validating the genomic signature of pediatric septic shock

We previously generated genome-wide expression data (microarray) from children with septic shock having the potential to lead the field into novel areas of investigation. Herein we seek to validate our data through a bioinformatic approach centered on a validation patient cohort. Forty-two children with a clinical diagnosis of septic shock and 15 normal controls served as the training data set, while 30 separate children with septic shock and 14 separate normal controls served as the test data set. Class prediction modeling using the training data set and the previously reported genome-wide expression signature of pediatric septic shock correctly identified 95-100% of controls and septic shock patients in the test data set, depending on the class prediction algorithm and the gene selection method. Subjecting the test data set to an identical filtering strategy as that used for the training data set, demonstrated 75% concordance between the two gene lists. Subjecting the test data set to a purely statistical filtering strategy, with highly stringent correction for multiple comparisons, demonstrated <50% concordance with the previous gene filtering strategy. However, functional analysis of this statistics-based gene list demonstrated similar functional annotations and signaling pathways as that seen in the training data set. In particular, we validated that pediatric septic shock is characterized by large-scale repression of genes related to zinc homeostasis and lymphocyte function. These data demonstrate that the previously reported genome-wide expression signature of pediatric septic shock is applicable to a validation cohort of patients.

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.