Neal J. Thomas

Predicting hospital-associated mortality for medicare patients: a method for patients with stroke, pneumonia, acute myocardial infarction, and congestive heart failure

We created a microcomputer-based system that uses characteristics of the patient at admission to predict death within 30 days of hospital admission for Medicare patients with stroke, pneumonia, myocardial infarction, and congestive heart failure. These conditions account for 13% of discharges and 31% of 30-day mortality for Medicare patients over 64 years of age. The system was calibrated on a stratified, random sample of 5888 discharges (about 1470 for each condition) from seven states, with stratification by hospital type to make the sample nationally representative. The predictors must be specially abstracted from the medical record. The cross-validated R2 for predictions is 0.14 to 0.25, which is better than the values for other systems for which we have data. Risk-adjusted predicted group mortality rates may be useful in interpreting information on unadjusted mortality rates, and patient-specific predictions may be useful in identifying unexpected deaths for clinical review.

Therapeutic Hypothermia after Out-of-Hospital Cardiac Arrest in Children

BACKGROUND Therapeutic hypothermia is recommended for comatose adults after witnessed out-of-hospital cardiac arrest, but data about this intervention in children are limited. METHODS We conducted this trial of two targeted temperature interventions at 38 childrens hospitals involving children who remained unconscious after out-of-hospital cardiac arrest. Within 6 hours after the return of circulation, comatose patients who were older than 2 days and younger than 18 years of age were randomly assigned to therapeutic hypothermia (target temperature, 33.0°C) or therapeutic normothermia (target temperature, 36.8°C). The primary efficacy outcome, survival at 12 months after cardiac arrest with a Vineland Adaptive Behavior Scales, second edition (VABS-II), score of 70 or higher (on a scale from 20 to 160, with higher scores indicating better function), was evaluated among patients with a VABS-II score of at least 70 before cardiac arrest. RESULTS A total of 295 patients underwent randomization. Among the 260 patients with data that could be evaluated and who had a VABS-II score of at least 70 before cardiac arrest, there was no significant difference in the primary outcome between the hypothermia group and the normothermia group (20% vs. 12%; relative likelihood, 1.54; 95% confidence interval [CI], 0.86 to 2.76; P=0.14). Among all the patients with data that could be evaluated, the change in the VABS-II score from baseline to 12 months was not significantly different (P=0.13) and 1-year survival was similar (38% in the hypothermia group vs. 29% in the normothermia group; relative likelihood, 1.29; 95% CI, 0.93 to 1.79; P=0.13). The groups had similar incidences of infection and serious arrhythmias, as well as similar use of blood products and 28-day mortality. CONCLUSIONS In comatose children who survived out-of-hospital cardiac arrest, therapeutic hypothermia, as compared with therapeutic normothermia, did not confer a significant benefit in survival with a good functional outcome at 1 year. (Funded by the National Heart, Lung, and Blood Institute and others; THAPCA-OH ClinicalTrials.gov number, NCT00878644.).

Anemia, Blood Loss, and Blood Transfusions in North American Children in the Intensive Care Unit

RATIONALE Minimizing exposure of children to blood products is desirable. OBJECTIVES We aimed to understand anemia development, blood loss, and red blood cell (RBC) transfusions in the pediatric intensive care unit (PICU). METHODS Prospective, multicenter, 6-month observational study in 30 PICUs. Data were collected on consecutive children (<18 yr old) in the PICU for 48 hours or more. MEASUREMENTS AND MAIN RESULTS Anemia development, blood loss, and RBC transfusions were measured. A total of 977 children were enrolled. Most (74%) children were anemic in the PICU (33% on admission, 41% developed anemia). Blood draws accounted for 73% of daily blood loss; median loss was 5.0 ml/day. Forty-nine percent of children received transfusions; 74% of first transfusions were on Days 1-2. After adjusting for age and illness severity, compared with nontransfused children, children who underwent transfusion had significantly longer days of mechanical ventilation (2.1 d, P < 0.001) and PICU stay (1.8 d, P = 0.03), and had increased mortality (odds ratio [OR], 11.6; 95% confidence interval [CI], 1.43-90.9; P = 0.02), nosocomial infections (OR, 1.9; 95% CI, 1.2-3.0; P = 0.004), and cardiorespiratory dysfunction (OR, 2.1; 95% CI, 1.5-3.0; P < 0.001). High blood loss per kilogram body weight from blood draws (OR, 1.11; 95% CI, 1.03-1.2; P = 0.01) was associated with RBC transfusion more than 48 hours after admission. The most common indication for transfusion was low hemoglobin (42%). Pretransfusion hemoglobin values varied greatly (mean, 9.7 +/- 2.7 g/dl). CONCLUSIONS Critically ill children are at significant risk for developing anemia and receiving blood transfusions. Transfusion in the PICU was associated with worse outcomes. It is imperative to minimize blood loss from blood draws and to set clear transfusion thresholds.

Pediatric Acute Respiratory Distress Syndrome: Consensus Recommendations From the Pediatric Acute Lung Injury Consensus Conference

OBJECTIVE To describe the final recommendations of the Pediatric Acute Lung Injury Consensus Conference. DESIGN Consensus conference of experts in pediatric acute lung injury. SETTING Not applicable. SUBJECTS PICU patients with evidence of acute lung injury or acute respiratory distress syndrome. INTERVENTIONS None. METHODS A panel of 27 experts met over the course of 2 years to develop a taxonomy to define pediatric acute respiratory distress syndrome and to make recommendations regarding treatment and research priorities. When published, data were lacking a modified Delphi approach emphasizing strong professional agreement was used. MEASUREMENTS AND MAIN RESULTS A panel of 27 experts met over the course of 2 years to develop a taxonomy to define pediatric acute respiratory distress syndrome and to make recommendations regarding treatment and research priorities. When published data were lacking a modified Delphi approach emphasizing strong professional agreement was used. The Pediatric Acute Lung Injury Consensus Conference experts developed and voted on a total of 151 recommendations addressing the following topics related to pediatric acute respiratory distress syndrome: 1) Definition, prevalence, and epidemiology; 2) Pathophysiology, comorbidities, and severity; 3) Ventilatory support; 4) Pulmonary-specific ancillary treatment; 5) Nonpulmonary treatment; 6) Monitoring; 7) Noninvasive support and ventilation; 8) Extracorporeal support; and 9) Morbidity and long-term outcomes. There were 132 recommendations with strong agreement and 19 recommendations with weak agreement. Once restated, the final iteration of the recommendations had none with equipoise or disagreement. CONCLUSIONS The Consensus Conference developed pediatric-specific definitions for acute respiratory distress syndrome and recommendations regarding treatment and future research priorities. These are intended to promote optimization and consistency of care for children with pediatric acute respiratory distress syndrome and identify areas of uncertainty requiring further investigation.

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.

Delayed antimicrobial therapy increases mortality and organ dysfunction duration in pediatric sepsis.

Objectives: Delayed antimicrobials are associated with poor outcomes in adult sepsis, but data relating antimicrobial timing to mortality and organ dysfunction in pediatric sepsis are limited. We sought to determine the impact of antimicrobial timing on mortality and organ dysfunction in pediatric patients with severe sepsis or septic shock. Design: Retrospective observational study. Setting: PICU at an academic medical center. Patients: One hundred thirty patients treated for severe sepsis or septic shock. Interventions: None. Measurements and Main Results: We determined if hourly delays from sepsis recognition to initial and first appropriate antimicrobial administration were associated with PICU mortality (primary outcome); ventilator-free, vasoactive-free, and organ failure–free days; and length of stay. Median time from sepsis recognition to initial antimicrobial administration was 140 minutes (interquartile range, 74–277 min) and to first appropriate antimicrobial was 177 minutes (90–550 min). An escalating risk of mortality was observed with each hour delay from sepsis recognition to antimicrobial administration, although this did not achieve significance until 3 hours. For patients with more than 3-hour delay to initial and first appropriate antimicrobials, the odds ratio for PICU mortality was 3.92 (95% CI, 1.27–12.06) and 3.59 (95% CI, 1.09–11.76), respectively. These associations persisted after adjustment for individual confounders and a propensity score analysis. After controlling for severity of illness, the odds ratio for PICU mortality increased to 4.84 (95% CI, 1.45–16.2) and 4.92 (95% CI, 1.30–18.58) for more than 3-hour delay to initial and first appropriate antimicrobials, respectively. Initial antimicrobial administration more than 3 hours was also associated with fewer organ failure–free days (16 [interquartile range, 1–23] vs 20 [interquartile range, 6–26]; p = 0.04). Conclusions: Delayed antimicrobial therapy was an independent risk factor for mortality and prolonged organ dysfunction in pediatric sepsis.

Defining acute lung disease in children with the oxygenation saturation index.

Objective: To evalute whether a formula could be derived using oxygen saturation (Spo2) to replace Pao2 that would allow identification of children with acute lung injury and acute respiratory distress syndrome. Definitions of acute lung injury and acute respiratory distress syndrome require arterial blood gases to determine the Pao2/Fio2 ratio of 300 (acute lung injury) and 200 (acute respiratory distress syndrome). Design: Post hoc data analysis of measurements abstracted from two prospective databases of randomized controlled trials. Setting: Academic pediatric intensive care units. Patients: A total of 255 children enrolled in two large prospective trials of therapeutic intervention for acute lung disease: calfactant and prone positioning. Interventions: Data were abstracted including Pao2, Paco2, pH, Fio2, and mean airway pressure. Repeated-measures analyses, using linear mixed-effects models, were used to build separate prediction equations for the Spo2/Fio2 ratio, oxygenation index [(Fio2 × Mean Airway Pressure)/Pao2], and oxygen saturation index [(Fio2 × Mean Airway Pressure)/Spo2 ]. A generalization of R2 was used to measure goodness-of-fit. Generalized estimating equations with a logit link were used to calculate the sensitivity and specificity for the cutoffs of Pao2/Fio2 ratio of 200 and 300 and equivalent values of Spo2/Fio2 ratio, oxygenation index, and oxygen saturation index. Measurements and Main Results: An Spo2/Fio2 ratio of 253 and 212 would equal criteria for acute lung injury and acute respiratory distress syndrome, respectively. An oxygenation index of 5.3 would equal acute lung injury criteria, and an oxygenation index of 8.1 would qualify for acute respiratory distress syndrome. An oxygen saturation index, which includes the mean airway pressure and the noninvasive measure of oxygenation, of 6.5 would be equivalent to the acute lung injury criteria, and an oxygen saturation index of 7.8 would equal acute respiratory distress syndrome criteria. Conclusions: Noninvasive methods of assessing oxygenation may be utilized with reasonable sensitivity and specificity to define acute lung injury and acute respiratory distress syndrome, and, with prospective validation, have the potential to increase the number of children enrolled into clinical trials.

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.

Comparison of SpO2 to PaO2 based markers of lung disease severity for children with acute lung injury.

Objective:Given pulse oximetry is increasingly substituting for arterial blood gas monitoring, noninvasive surrogate markers for lung disease severity are needed to stratify pediatric risk. We sought to validate prospectively the comparability of SpO2/Fio2 to PaO2/Fio2 and oxygen saturation index to oxygenation index in children. We also sought to derive a noninvasive lung injury score. Design:Prospective, multicentered observational study in six pediatric intensive care units. Patients:One hundred thirty-seven mechanically ventilated children with SpO2 80% to 97% and an indwelling arterial catheter. Interventions:Simultaneous blood gas, pulse oximetry, and ventilator settings were collected. Derivation and validation data sets were generated, and linear mixed modeling was used to derive predictive equations. Model performance and fit were evaluated using the validation data set. Measurements and Main Results:One thousand one hundred ninety blood gas, SpO2, and ventilator settings from 137 patients were included. Oxygen saturation index had a strong linear association with oxygenation index in both derivation and validation data sets, given by the equation oxygen saturation index = 2.76 1 0.547*oxygenation index (derivation). 1/SpO2/Fio2 had a strong linear association with 1/PaO2/Fio2 in both derivation and validation data sets given by the equation 1/SpO2/Fio2 = 0.00232 1 0.443/PaO2/Fio2 (derivation). SpO2/Fio2 criteria for acute respiratory distress syndrome and acute lung injury were 221 (95% confidence interval 215–226) and 264 (95% confidence interval 259–269). Multivariate models demonstrated that oxygenation index, serum pH, and Paco2 were associated with oxygen saturation index (p < .05); and 1/PaO2/Fio2, mean airway pressure, serum pH, and Paco2 were associated with 1/SpO2/Fio2 (p < .05). There was strong concordance between the derived noninvasive lung injury score and the original pediatric modification of lung injury score with a mean difference of 20.0361 &agr;0.264 sd. Conclusions:Lung injury severity markers, which use SpO2, are adequate surrogate markers for those that use PaO2 in children with respiratory failure for SpO2 between 80% and 97%. They should be used in clinical practice to characterize risk, to increase enrollment in clinical trials, and to determine disease prevalence. (Crit Care Med 2012; 40:–1316)