Craig R. Warden

Epidemiology and Outcomes From Out-of-Hospital Cardiac Arrest in Children The Resuscitation Outcomes Consortium Epistry–Cardiac Arrest

Background— Population-based data for pediatric cardiac arrest are scant and largely from urban areas. The Resuscitation Outcomes Consortium (ROC) Epistry–Cardiac Arrest is a population-based emergency medical services registry of out-of-hospital nontraumatic cardiac arrest (OHCA). This study examined age-stratified incidence and outcomes of pediatric OHCA. We hypothesized that survival to hospital discharge is less frequent from pediatric OHCA than adult OHCA. Methods and Results— This prospective population-based cohort study in 11 US and Canadian ROC sites included persons <20 years of age who received cardiopulmonary resuscitation or defibrillation by emergency medical service providers and/or received bystander automatic external defibrillator shock or who were pulseless but received no resuscitation by emergency medical services between December 2005 and March 2007. Patients were stratified a priori into 3 age groups: <1 year (infants; n=277), 1 to 11 years (children; n=154), and 12 to 19 years (adolescents; n=193). The incidence of pediatric OHCA was 8.04 per 100 000 person-years (72.71 in infants, 3.73 in children, and 6.37 in adolescents) versus 126.52 per 100 000 person-years for adults. Survival for all pediatric OHCA was 6.4% (3.3% for infants, 9.1% for children, and 8.9% for adolescents) versus 4.5% for adults (P=0.03). Unadjusted odds ratio for pediatric survival to discharge compared with adults was 0.71 (95% confidence interval, 0.37 to 1.39) for infants, 2.11 (95% confidence interval, 1.21 to 3.66) for children, and 2.04 (95% confidence interval, 1.24 to 3.38) for adolescents. Conclusions— This study demonstrates that the incidence of OHCA in infants approaches that observed in adults but is lower among children and adolescents. Survival to discharge was more common among children and adolescents than infants or adults.

Guidelines for the acute medical management of severe traumatic brain injury in infants, children, and adolescents--second edition.

Author Affiliations Patrick M. Kochanek, MD, FCCM, Professor and Vice Chair, Department of Critical Care Medicine, University of Pittsburgh School of Medicine Nancy Carney, PhD, Associate Professor, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University P. David Adelson, MD, FACS, FAAP, Director, Barrow Neurological Institute at Phoenix Children’s Hospital, Chief, Pediatric Neurosurgery/ Children’s Neurosciences Stephen Ashwal, MD, Distinguished Professor of Pediatrics and Neurology, Chief of the Division of Child Neurology, Department of Pediatrics, Loma Linda University School of Medicine Michael J. Bell, MD, Associate Professor of Critical Care Medicine, University of Pittsburgh School of Medicine Susan Bratton, MD, MPH, FAAP, Professor of Pediatric Critical Care Medicine, University of Utah School of Medicine Susan Carson, MPH, Senior Research Associate, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University Randall M. Chesnut, MD, FCCM, FACS, Professor of Neurological Surgery, Orthopedics and Sports Medicine, University of Washington School of Medicine Jamshid Ghajar, MD, PhD, FACS, Clinical Professor of Neurological Surgery, Weill Cornell Medical College, President of the Brain Trauma Foundation Brahm Goldstein, MD, FAAP, FCCM, Senior Medical Director, Clinical Research, Ikaria, Inc., Professor of Pediatrics, University of Medicine and Dentistry of New Jersey, Robert Wood Johnson Medical School Gerald A. Grant, MD, Associate Professor of Surgery and Pediatrics, Duke University School of Medicine Niranjan Kissoon, MD, FAAP, FCCM, Professor of Paediatrics and Emergency Medicine, British Columbia’s Children’s Hospital, University of British Columbia Kimberly Peterson, BSc, Research Associate, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University Nathan R. Selden, MD, PhD, FACS, FAAP, Campagna Professor and Vice Chair of Neurological Surgery, Oregon Health & Science University Robert C. Tasker, MBBS, MD, FRCP, Chair and Director, Neurocritical Care, Children’s Hospital Boston, Professor of Neurology and Anesthesia, Harvard Medical School Karen A. Tong, MD, Associate Professor of Radiology, Loma Linda University Monica S. Vavilala, MD, Professor of Anesthesiology and Pediatrics, University of Washington School of Medicine Mark S. Wainwright, MD, PhD, Director, Pediatric Neurocritical Care, Associate Professor of Pediatrics, Northwestern University Feinberg School of Medicine Craig R. Warden, MD, MPH, MS, Professor of Emergency Medicine and Pediatrics, Chief, Pediatric Emergency Services, Oregon Health & Science University/Doernbecher Children’s Hospital

Impact of prehospital mode of transport after severe injury: a multicenter evaluation from the Resuscitation Outcomes Consortium.

BACKGROUND: There is ongoing controversy about the relative effectiveness of air medical versus ground transportation for severely injured patients. In some systems, air medical crews may provide a higher level of care but may require longer transport times. We sought to evaluate the impact of mode of transport on outcome based on analysis of data from two randomized trials of prehospital hypertonic resuscitation. METHODS: Injured patients were enrolled based on prehospital evidence of hypovolemic shock (systolic blood pressure ⩽70 mm Hg or systolic blood pressure = 71–90 mm Hg with heart rate ≥108 bpm) or severe traumatic brain injury (TBI; Glasgow Coma Scale score ⩽8). Patient demographics, injury severity, and physiology were compared based on mode of transport. Multivariate logistic regression was used to determine the impact of mode of transport on 24-hour and 28-day survival for all patients and 6-month extended Glasgow Outcome Scale for patients with TBI, adjusting for differences in injury severity. RESULTS: Included were 2,049 patients, of which 703 (34%) were transported by air. Patients transported by air were more severely injured (mean Injury Severity Score, 30.3 vs. 22.8; p < 0.001), more likely to be in the TBI cohort (70% vs. 55.4%; p < 0.001), and more likely blunt mechanism (94.0% vs. 78.1%; p < 0.001). Patients transported by air had higher rates of prehospital intubation (81% vs. 36%; p < 0.001), received more intravenous fluids (mean 1.3 L vs. 0.8 L; p < 0.001), and had longer prehospital times (mean 76.1 minutes vs. 43.5 minutes; p < 0.001). Adjusted analysis revealed no significant impact of mode of transport on survival or 6-month neurologic outcome (air transport—28-day survival: odds ratio, 1.11; 95% confidence interval, 0.82–1.51; 6-month extended Glasgow Outcome Scale score ⩽4: odds ratio, 0.94; 95% confidence interval, 0.68–1.31). CONCLUSION: There was no difference in the adjusted clinical outcome according to mode of transport. However, air medical transported more severely injured patients with more advanced life support procedures and longer prehospital time. LEVEL OF EVIDENCE: III.

Using Geographic Information Systems to Evaluate Cardiac Arrest Survival

Objective. To evaluate cardiac arrest survival using geographical information systems (GIS) methodology. Methods. Patient data were obtained from a fire district Utstein-style adult cardiac arrest registry that also included address data. All incident locations were geocoded andfire station first-due areas were mapped by using the new computer-aided dispatch geographic data. Retrospective assignment of first-due versus second-due fire response unit was done by using a GIS “point-in-polygon” algorithm Survival to hospital admission was the primary outcome measure for incidents responded to by first-due versus second-due apparatus controlling for other potential predictors of survival using logistic regression. Cluster analysis was also performed to evaluate potential areas of high or low rates of survival. Results. There were 461 eligible patients with an average age of 67 ± 17 years, 63% were male, 53% had a witnessed arrest, bystander cardiopulmonary resuscitation was performed in 38%, bystander automatic external defibrillator (AED) Page: 1 was used in 0.01%, ventricular fibrillation or ventricular tachycardia were the presenting rhythms in 44%, the average response time was 5.5 ± 2.1 minutes, andsurvival to hospital admission was 17%. There was no significant difference in response time between survivors (4.97 minutes) andnon-survivors (5.52 minutes), (difference 0.55 minutes, 95%CI −0.08 to 1.18 min). The number of cardiac arrest calls varied from 1 to 49 for each station andthe rate of second-due response varied from 0 to 19%. There was a nonsignificant association of survival to hospital admission for the first-due area cohort: odds ratio 0.70, 95% CI 0.38–1.29. Conclusion GIS is a new methodology for analyzing EMS incident data. It adds a spatial component of analysis to traditional statistical techniques. No spatial difference was found on patient survival in this analysis. Key words: cardiac arrest; emergency medical services; geographical information systems.

Midazolam and diazepam for pediatric seizures in the prehospital setting.

Objective. The objective of this study was to compare the efficacy andadverse events associated with the use of diazepam andmidazolam for the treatment of pediatric seizures in the prehospital setting. Methods. This was a retrospective cohort study of all patients younger than 18 years treated for a seizure with a benzodiazepine by emergency medical services in Multnomah County, Oregon, from 1998 to 2001. The emergency medical services system consists of a single private advanced life support transporting ambulance service with fire department first responders that are all advanced life support capable. The benzodiazepine used changed from diazepam to midazolam at the midpoint of this period. The primary outcomes were termination of the seizure by arrival to the emergency department (ED), recurrence of seizure while in the ED, or the requirement for active airway interventions including intubation. The two cohorts were also compared for demographics, past history of seizures, long-term use of seizure medications, response times, route of administration, use of second doses of benzodiazepines, andfinal disposition. Results. Forty-five patients were treated with diazepam, and48 were treated with midazolam. The two cohorts were comparable except the diazepam cohort had a significantly increased proportion of patients with previous afebrile seizures (53% vs. 25%; p = 0.005). The midazolam cohort had an increased use of nonintravenous route for initial dosing (65% vs. 42%; p = 0.02). The two cohorts were equivalent in rates of termination of seizures before to ED arrival, recurrence of seizures in the ED, requiring airway support or a second dose of benzodiazepine, andadmission to the hospital. Conclusions. Diazepam andmidazolam appear to be equivalent in treating seizures andcausing adverse events. Paramedics appear to be administering midazolam intramuscularly more often than they use diazepam rectally.

Identifying High-risk Geographic Areas for Cardiac Arrest Using Three Methods for Cluster Analysis

OBJECTIVES   The objective was to identify high-risk census tracts, defined as those areas that have both a high incidence of out-of-hospital cardiac arrest (OHCA) and a low prevalence of bystander cardiopulmonary resuscitation (CPR), by using three spatial statistical methods. METHODS   This was a secondary analysis of two prospectively collected registries in the city of Columbus, Ohio. Consecutive adult (≥18 years) OHCA patients, restricted to those of cardiac etiology and treated by emergency medical services (EMS) from April 1, 2004, to April 30, 2009, were studied. Three different spatial analysis methods (Global Empirical Bayes, Local Morans I, and SaTScans spatial scan statistic) were used to identify high-risk census tracts. RESULTS   A total of 4,553 arrests in 200 census tracts occurred during the study period, with 1,632 arrests included in the final sample after exclusions for no resuscitation attempt, noncardiac etiology, etc. The overall incidence for OHCA was 0.70 per 1,000 people for the 6-year study period (SD = ±0.52). Bystander CPR occurred in 20.2% (n = 329), with 10.0% (n = 167) surviving to hospital discharge. Five high-risk census tracts were identified by all three analytic methods. CONCLUSIONS   The five high-risk census tracts identified may be possible sites for high-yield targeted community-based interventions to improve CPR training and cardiovascular disease education efforts and ultimately improve survival from OHCA.

Design and implementation of the Resuscitation Outcomes Consortium Pragmatic Airway Resuscitation Trial (PART)

Airway management is an important component of resuscitation from out-of-hospital cardiac arrest (OHCA). The optimal approach to advanced airway management is unknown. The Pragmatic Airway Resuscitation Trial (PART) will compare the effectiveness of endotracheal intubation (ETI) and Laryngeal Tube (LT) insertion upon 72-h survival in adult OHCA. Encompassing United States Emergency Medical Services agencies affiliated with the Resuscitation Outcomes Consortium (ROC), PART will use a cluster-crossover randomized design. Participating subjects will include adult, non-traumatic OHCA requiring bag-valve-mask ventilation. Trial interventions will include (1) initial airway management with ETI and (2) initial airway management with LT. The primary and secondary trial outcomes are 72-h survival and return of spontaneous circulation. Additional clinical outcomes will include airway management process and adverse events. The trial will enroll a total of 3000 subjects. Results of PART may guide the selection of advanced airway management strategies in OHCA.

Trauma in the Neighborhood: A Geospatial Analysis and Assessment of Social Determinants of Major Injury in North America

OBJECTIVES We sought to identify and characterize areas with high rates of major trauma events in 9 diverse cities and counties in the United States and Canada. METHODS We analyzed a prospective, population-based cohort of injured individuals evaluated by 163 emergency medical service agencies transporting patients to 177 hospitals across the study sites between December 2005 and April 2007. Locations of injuries were geocoded, aggregated by census tract, assessed for geospatial clustering, and matched to sociodemographic measures. Negative binomial models were used to evaluate population measures. RESULTS Emergency personnel evaluated 8786 major trauma patients, and data on 7326 of these patients were available for analysis. We identified 529 (13.7%) census tracts with a higher than expected incidence of major trauma events. In multivariable models, trauma events were associated with higher unemployment rates, larger percentages of non-White residents, smaller percentages of foreign-born residents, lower educational levels, smaller household sizes, younger age, and lower income levels. CONCLUSIONS Major trauma events tend to cluster in census tracts with distinct population characteristics, suggesting that social and contextual factors may play a role in the occurrence of significant injury events.

Predicting Ambulance Time of Arrival to the Emergency Department Using Global Positioning System and Google Maps

Abstract Objective. To derive and validate a model that accurately predicts ambulance arrival time that could be implemented as a Google Maps web application. Methods. This was a retrospective study of all scene transports in Multnomah County, Oregon, from January 1 through December 31, 2008. Scene and destination hospital addresses were converted to coordinates. ArcGIS Network Analyst was used to estimate transport times based on street network speed limits. We then created a linear regression model to improve the accuracy of these street network estimates using weather, patient characteristics, use of lights and sirens, daylight, and rush-hour intervals. The model was derived from a 50% sample and validated on the remainder. Significance of the covariates was determined by p < 0.05 for a t-test of the model coefficients. Accuracy was quantified by the proportion of estimates that were within 5 minutes of the actual transport times recorded by computer-aided dispatch. We then built a Google Maps-based web application to demonstrate application in real-world EMS operations. Results. There were 48,308 included transports. Street network estimates of transport time were accurate within 5 minutes of actual transport time less than 16% of the time. Actual transport times were longer during daylight and rush-hour intervals and shorter with use of lights and sirens. Age under 18 years, gender, wet weather, and trauma system entry were not significant predictors of transport time. Our model predicted arrival time within 5 minutes 73% of the time. For lights and sirens transports, accuracy was within 5 minutes 77% of the time. Accuracy was identical in the validation dataset. Lights and sirens saved an average of 3.1 minutes for transports under 8.8 minutes, and 5.3 minutes for longer transports. Conclusions. An estimate of transport time based only on a street network significantly underestimated transport times. A simple model incorporating few variables can predict ambulance time of arrival to the emergency department with good accuracy. This model could be linked to global positioning system data and an automated Google Maps web application to optimize emergency department resource use. Use of lights and sirens had a significant effect on transport times. Key words: emergency medical services; prehospital emergency care.

Unchanged pediatric out-of-hospital cardiac arrest incidence and survival rates with regional variation in North America

AIM Outcomes for pediatric out-of-hospital cardiac arrest (OHCA) are poor. Our objective was to determine temporal trends in incidence and mortality for pediatric OHCA. METHODS Adjusted incidence and hospital mortality rates of pediatric non-traumatic OHCA patients from 2007-2012 were analyzed using the 9 region Resuscitation Outcomes Consortium-Epidemiological Registry (ROC-Epistry) database. Children were divided into 4 age groups: perinatal (<3 days), infants (3days-1year), children (1-11 years), and adolescents (12-19 years). ROC regions were analyzed post-hoc. RESULTS We studied 1738 children with OHCA. The age- and sex-adjusted incidence rate of OHCA was 8.3 per 100,000 person-years (75.3 for infants vs. 3.7 for children and 6.3 for adolescents, per 100,000 person-years, p<0.001). Incidence rates differed by year (p<0.001) without overall linear trend. Annual survival rates ranged from 6.7-10.2%. Survival was highest in the perinatal (25%) and adolescent (17.3%) groups. Stratified by age group, survival rates over time were unchanged (all p>0.05) but there was a non-significant linear trend (1.3% increase) in infants. In the multivariable logistic regression analysis, infants, unwitnessed event, initial rhythm of asystole, and region were associated with worse survival, all p<0.001. Survival by region ranged from 2.6-14.7%. Regions with the highest survival had more cases of EMS-witnessed OHCA, bystander CPR, and increased EMS-defibrillation (all p<0.05). CONCLUSIONS Overall incidence and survival of children with OHCA in ROC regions did not significantly change over a recent 5year period. Regional variation represents an opportunity for further study to improve outcomes.