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Doud A.N.,Childress Institute for Pediatric Trauma | Lawrence K.,Weill Cornell | Zeller K.A.,Childress Institute for Pediatric Trauma
Journal of Pediatric Surgery | Year: 2015

Background Parental, familial, and demographic risk factors for nonaccidental trauma (NAT) have been well-studied, but neonatal factors, such as comorbidities and prematurity have not. We assess the correlation of these factors with NAT. Methods A total of 234 cases of NAT and 287 cases of accidental trauma (AT) among children < 1 year were identified in a trauma registry. Known risk factors for NAT, gestational age, and neonatal comorbidities were abstracted from medical records. Chi-square analysis and logistic regression evaluated the association of prematurity and comorbidities with NAT compared to AT with and without controlling for confounders. Results Children treated for NAT were younger than those treated for AT and were more likely to have younger parents with substance abuse issues. Prematurity, major comorbidities, and minor comorbidities were more common in those treated after NAT than after AT (24.8% vs 12.7%, p = 0.0004; 25.6% vs 7.2%, p < 0.0001, and 42.6% vs 29.3%, p = 0.0014, respectively). After model adjustments for other risk factors, major comorbidity remained a significant risk factor for NAT compared to AT, with an adjusted odds ratio of 4.37 (p < 0.0001). Conclusions Among other risk factors, neonatal factors predict a child's risk for abuse. We have an opportunity for targeted preventive interventions among this at-risk population. © 2015 Elsevier Inc. All rights reserved.


Davenport E.M.,Advanced Neuroscience Imaging Research ANSIR Laboratory | Davenport E.M.,Virginia Polytechnic Institute and State University | Whitlow C.T.,Advanced Neuroscience Imaging Research ANSIR Laboratory | Whitlow C.T.,Medical Center Boulevard | And 11 more authors.
Journal of Neurotrauma | Year: 2014

The aim of this study was to determine whether the cumulative effects of head impacts from a season of high school football produce magnetic resonance imaging (MRI) measureable changes in the brain in the absence of clinically diagnosed concussion. Players from a local high school football team were instrumented with the Head Impact Telemetry System (HITS™) during all practices and games. All players received pre- and postseason MRI, including diffusion tensor imaging (DTI). Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT) was also conducted. Total impacts and risk-weighted cumulative exposure (RWE), including linear (RWELinear), rotational (RWERotational), and combined components (RWECP), were computed from the sensor data. Fractional, linear, planar, and spherical anisotropies (FA, CL, CP, and CS, respectively), as well as mean diffusivity (MD), were used to determine total number of abnormal white matter voxels defined as 2 standard deviations above or below the group mean. Delta (post-preseason) ImPACT scores for each individual were computed and compared to the DTI measures using Spearman's rank correlation coefficient. None of the players analyzed experienced clinical concussion (N=24). Regression analysis revealed a statistically significant linear relationship between RWECPand FA. Secondary analyses demonstrated additional statistically significant linear associations between RWE (RWECPand RWELinear) and all DTI measures. There was also a strong correlation between DTI measures and change in Verbal Memory subscore of the ImPACT. We demonstrate that a single season of football can produce brain MRI changes in the absence of clinical concussion. Similar brain MRI changes have been previously associated with mild traumatic brain injury. © Mary Ann Liebert, Inc.


Doud A.N.,Childress Institute for Pediatric Trauma | Petty J.,Childress Institute for Pediatric Trauma | Stitzel J.D.,Childress Institute for Pediatric Trauma
Traffic Injury Prevention | Year: 2016

ABSTRACT: Objective: Appropriate treatment at designated trauma centers (TCs) improves outcomes among injured children after motor vehicle crashes (MVCs). Advanced Automatic Crash Notification (AACN) has shown promise in improving triage to appropriate TCs. Pediatric-specific AACN algorithms have not yet been created. To create such an algorithm, it will be necessary to include some metric of development (age, height, or weight) as a covariate in the injury risk algorithm. This study sought to determine which marker of development should serve as a covariate in such an algorithm and to quantify injury risk at different levels of this metric. Methods: A retrospective review of occupants age < 19 years within the MVC data set NASS-CDS 2000–2011 was performed. R2 values of logistic regression models using age, height, or weight to predict 18 key injury types were compared to determine which metric should be used as a covariate in a pediatric AACN algorithm. Clinical judgment, literature review, and chi-square analysis were used to create groupings of the chosen metric that would discriminate injury patterns. Adjusted odds of particular injury types at the different levels of this metric were calculated from logistic regression while controlling for gender, vehicle velocity change (delta V), belted status (optimal, suboptimal, or unrestrained), and crash mode (rollover, rear, frontal, near-side, or far-side). Results: NASS-CDS analysis produced 11,541 occupants age < 19 years with nonmissing data. Age, height, and weight were correlated with one another and with injury patterns. Age demonstrated the best predictive power in injury patterns and was categorized into bins of 0–4 years, 5–9 years, 10–14 years, and 15–18 years. Age was a significant predictor of all 18 injury types evaluated even when controlling for all other confounders and when controlling for age- and gender-specific body mass index (BMI) classifications. Adjusted odds of key injury types with respect to these age categorizations revealed that younger children were at increased odds of sustaining Abbreviated Injury Scale (AIS) 2+ and 3+ head injuries and AIS 3+ spinal injuries, whereas older children were at increased odds of sustaining thoracic fractures, AIS 3+ abdominal injuries, and AIS 2+ upper and lower extremity injuries. Conclusions: The injury patterns observed across developmental metrics in this study mirror those previously described among children with blunt trauma. This study identifies age as the metric best suited for use in a pediatric AACN algorithm and utilizes 12 years of data to provide quantifiable risks of particular injuries at different levels of this metric. This risk quantification will have important predictive purposes in a pediatric-specific AACN algorithm. © 2016 Taylor & Francis Group, LLC.


Doud A.N.,Childress Institute for Pediatric Trauma | Petty J.K.,Childress Institute for Pediatric Trauma
Traffic Injury Prevention | Year: 2015

Objective: Survival risk ratios (SRRs) and their probabilistic counterpart, mortality risk ratios (MRRs), have been shown to be at odds with Abbreviated Injury Scale (AIS) severity scores for particular injuries in adults. SRRs have been validated for pediatrics but have not been studied within the context of pediatric age stratifications. We hypothesized that children with similar motor vehicle crash (MVC) injuries may have different mortality risks (MR) based upon developmental stage and that these MRs may not correlate with AIS severity. Methods: The NASS-CDS 2000–2011 was used to define the top 95% most common AIS 2+ injuries among MVC occupants in 4 age groups: 0–4, 5–9, 10–14, and 15–18 years. Next, the National Trauma Databank 2002–2011 was used to calculate the MR (proportion of those dying with an injury to those sustaining the injury) and the co-injury-adjusted MR (MRMAIS) for each injury within 6 age groups: 0–4, 5–9, 10–14, 15–18, 0–18, and 19+ years. MR differences were evaluated between age groups aggregately, between age groups based upon anatomic injury patterns and between age groups on an individual injury level using nonparametric Wilcoxon tests and chi-square or Fisher's exact tests as appropriate. Correlation between AIS and MR within each age group was also evaluated. Results: MR and MRMAIS distributions of the most common AIS 2+ injuries were right skewed. Aggregate MR of these most common injuries varied between the age groups, with 5- to 9-year-old and 10- to 14-year-old children having the lowest MRs and 0- to 4-year-old and 15- to 18-year-old children and adults having the highest MRs (all P <.05). Head and thoracic injuries imparted the greatest mortality risk in all age groups with median MRMAIS ranging from 0 to 6% and 0 to 4.5%, respectively. Injuries to particular body regions also varied with respect to MR based upon age. For example, thoracic injuries in adults had significantly higher MRMAIS than such injuries among 5- to 9-year-olds and 10- to 14-year-olds (P =.04; P <.01). Furthermore, though AIS was positively correlated with MR within each age group, less correlation was seen for children than for adults. Large MR variations were seen within each AIS grade, with some lower AIS severity injuries demonstrating greater MRs than higher AIS severity injuries. As an example, MRMAIS in 0- to 18-year-olds was 0.4% for an AIS 3 radius fracture versus 1.4% for an AIS 2 vault fracture. Conclusions: Trauma severity metrics are important for outcome prediction models and can be used in pediatric triage algorithms and other injury research. Trauma severity may vary for similar injuries based upon developmental stage, and this difference should be reflected in severity metrics. The MR-based data-driven determination of injury severity in pediatric occupants of different age cohorts provides a supplement or an alternative to AIS severity classification for pediatric occupants in MVCs. © 2015, Copyright © Taylor & Francis Group, LLC.


Cobb B.R.,Wake forest University | Urban J.E.,Wake forest University | Urban J.E.,Medical Center Blvd | Davenport E.M.,Wake forest University | And 8 more authors.
Annals of Biomedical Engineering | Year: 2013

Head impact exposure in youth football has not been well-documented, despite children under the age of 14 accounting for 70% of all football players in the United States. The objective of this study was to quantify the head impact exposure of youth football players, age 9-12, for all practices and games over the course of single season. A total of 50 players (age = 11.0 ± 1.1 years) on three teams were equipped with helmet mounted accelerometer arrays, which monitored each impact players sustained during practices and games. During the season, 11,978 impacts were recorded for this age group. Players averaged 240 ± 147 impacts for the season with linear and rotational 95th percentile magnitudes of 43 ± 7 g and 2034 ± 361 rad/s2. Overall, practice and game sessions involved similar impact frequencies and magnitudes. One of the three teams however, had substantially fewer impacts per practice and lower 95th percentile magnitudes in practices due to a concerted effort to limit contact in practices. The same team also participated in fewer practices, further reducing the number of impacts each player experienced in practice. Head impact exposures in games showed no statistical difference. While the acceleration magnitudes among 9-12 year old players tended to be lower than those reported for older players, some recorded high magnitude impacts were similar to those seen at the high school and college level. Head impact exposure in youth football may be appreciably reduced by limiting contact in practices. Further research is required to assess whether such a reduction in head impact exposure will result in a reduction in concussion incidence. © 2013 The Author(s).


PubMed | Childress Institute for Pediatric Trauma
Type: Evaluation Studies | Journal: Traffic injury prevention | Year: 2016

Appropriate treatment at designated trauma centers (TCs) improves outcomes among injured children after motor vehicle crashes (MVCs). Advanced Automatic Crash Notification (AACN) has shown promise in improving triage to appropriate TCs. Pediatric-specific AACN algorithms have not yet been created. To create such an algorithm, it will be necessary to include some metric of development (age, height, or weight) as a covariate in the injury risk algorithm. This study sought to determine which marker of development should serve as a covariate in such an algorithm and to quantify injury risk at different levels of this metric.A retrospective review of occupants age < 19 years within the MVC data set NASS-CDS 2000-2011 was performed. R(2) values of logistic regression models using age, height, or weight to predict 18 key injury types were compared to determine which metric should be used as a covariate in a pediatric AACN algorithm. Clinical judgment, literature review, and chi-square analysis were used to create groupings of the chosen metric that would discriminate injury patterns. Adjusted odds of particular injury types at the different levels of this metric were calculated from logistic regression while controlling for gender, vehicle velocity change (delta V), belted status (optimal, suboptimal, or unrestrained), and crash mode (rollover, rear, frontal, near-side, or far-side).NASS-CDS analysis produced 11,541 occupants age < 19 years with nonmissing data. Age, height, and weight were correlated with one another and with injury patterns. Age demonstrated the best predictive power in injury patterns and was categorized into bins of 0-4 years, 5-9 years, 10-14 years, and 15-18 years. Age was a significant predictor of all 18 injury types evaluated even when controlling for all other confounders and when controlling for age- and gender-specific body mass index (BMI) classifications. Adjusted odds of key injury types with respect to these age categorizations revealed that younger children were at increased odds of sustaining Abbreviated Injury Scale (AIS) 2+ and 3+ head injuries and AIS 3+ spinal injuries, whereas older children were at increased odds of sustaining thoracic fractures, AIS 3+ abdominal injuries, and AIS 2+ upper and lower extremity injuries.The injury patterns observed across developmental metrics in this study mirror those previously described among children with blunt trauma. This study identifies age as the metric best suited for use in a pediatric AACN algorithm and utilizes 12 years of data to provide quantifiable risks of particular injuries at different levels of this metric. This risk quantification will have important predictive purposes in a pediatric-specific AACN algorithm.


PubMed | Childress Institute for Pediatric Trauma and Weill Cornell
Type: Journal Article | Journal: Journal of pediatric surgery | Year: 2015

Parental, familial, and demographic risk factors for nonaccidental trauma (NAT) have been well-studied, but neonatal factors, such as comorbidities and prematurity have not. We assess the correlation of these factors with NAT.A total of 234 cases of NAT and 287 cases of accidental trauma (AT) among children <1 year were identified in a trauma registry. Known risk factors for NAT, gestational age, and neonatal comorbidities were abstracted from medical records. Chi-square analysis and logistic regression evaluated the association of prematurity and comorbidities with NAT compared to AT with and without controlling for confounders.Children treated for NAT were younger than those treated for AT and were more likely to have younger parents with substance abuse issues. Prematurity, major comorbidities, and minor comorbidities were more common in those treated after NAT than after AT (24.8% vs 12.7%, p=0.0004; 25.6% vs 7.2%, p<0.0001, and 42.6% vs 29.3%, p=0.0014, respectively). After model adjustments for other risk factors, major comorbidity remained a significant risk factor for NAT compared to AT, with an adjusted odds ratio of 4.37 (p<0.0001).Among other risk factors, neonatal factors predict a childs risk for abuse. We have an opportunity for targeted preventive interventions among this at-risk population.


Urban J.E.,Wake forest University | Urban J.E.,Medical Center Blvd | Davenport E.M.,Wake forest University | Davenport E.M.,Medical Center Blvd | And 10 more authors.
Annals of Biomedical Engineering | Year: 2013

Sports-related concussion is the most common athletic head injury with football having the highest rate among high school athletes. Traditionally, research on the biomechanics of football-related head impact has been focused at the collegiate level. Less research has been performed at the high school level, despite the incidence of concussion among high school football players. The objective of this study is to twofold: to quantify the head impact exposure in high school football, and to develop a cumulative impact analysis method. Head impact exposure was measured by instrumenting the helmets of 40 high school football players with helmet mounted accelerometer arrays to measure linear and rotational acceleration. A total of 16,502 head impacts were collected over the course of the season. Biomechanical data were analyzed by team and by player. The median impact for each player ranged from 15.2 to 27.0 g with an average value of 21.7 (±2.4) g. The 95th percentile impact for each player ranged from 38.8 to 72.9 g with an average value of 56.4 (±10.5) g. Next, an impact exposure metric utilizing concussion injury risk curves was created to quantify cumulative exposure for each participating player over the course of the season. Impacts were weighted according to the associated risk due to linear acceleration and rotational acceleration alone, as well as the combined probability (CP) of injury associated with both. These risks were summed over the course of a season to generate risk weighted cumulative exposure. The impact frequency was found to be greater during games compared to practices with an average number of impacts per session of 15.5 and 9.4, respectively. However, the median cumulative risk weighted exposure based on combined probability was found to be greater for practices vs. games. These data will provide a metric that may be used to better understand the cumulative effects of repetitive head impacts, injury mechanisms, and head impact exposure of athletes in football. © 2013 Biomedical Engineering Society.


News Article | December 15, 2016
Site: www.prweb.com

The Childress Institute for Pediatric Trauma was featured on “In America” hosted by James Earl Jones on PBS affiliates throughout the U.S. The video segment highlighted two pediatric trauma survivors and their families, as well as the need for an improved system of pediatric trauma care. Weezie Broughton was hit by a car while crossing the street when she was 11 years old. Meredith Cross fell off a horse when she was 15 years old. Both girls sustained traumatic brain injuries, multiple surgeries and extensive hospital stays. Their families are now advocates for improving pediatric trauma care for all children in the U.S. "Kids are injured by car wrecks, falls, playing sports, drowning, fires, poisoning and many other ways," said the Childress Institute’s Executive Director Bob Gfeller. "The holidays can mean increased travel and many opportunities for kids to get hurt. Families may be far from their usual hospital and emergency care team. It’s critical for EMS and hospitals to have the right tools when a child is injured, no matter where they are, because the first 60 minutes can make a difference in survival and recovery." The Childress Institute is raising awareness about the need for improved pediatric trauma care during the Golden Hour, or first 60 minutes after a serious injury. The Institute profiled 24 pediatric trauma stories in November to highlight that one child dies every hour, every day from pediatric trauma. If you or someone you know has a child that has been seriously injured, please share your story and tag #OurGoldenHour. Traumatic injury is the No. 1 killer of children in the U.S., claiming the lives of more than 10,000 children each year. In addition, almost 300,000 children are hospitalized and over 8 million children are treated in the emergency department for serious injuries each year, many of whom struggle with long-term recoveries and disabilities. The Childress Institute funds research, education and advocacy to save injured kids. Watch the “In America” video at https://www.youtube.com/ChildressInstitute. For more information on the Childress Institute, please visit https://saveinjuredkids.org, or on social media at https://www.facebook.com/SaveInjuredKids/, Twitter @injuredkids or Instagram @saveinjuredkids. About the Childress Institute for Pediatric Trauma Life threatening injury is the No. 1 killer of kids in America. Nearly 10,000 children lose their lives every year from serious injuries, and many more are treated in the emergency room. It can happen anywhere, at any time, to any child. The Childress Institute for Pediatric Trauma discovers and shares the best ways to prevent and treat severe injuries in children. The Institute funds research, education and advocacy to help improve the care and treatment injured kids receive across the U.S. The Childress Institute was founded at Wake Forest Baptist Medical Center in 2008 through a generous gift from Richard and Judy Childress. Visit http://www.SaveInjuredKids.org to learn more.


Loftis K.L.,Wake forest University | Pranikoff T.,Wake forest University | Pranikoff T.,Childress Institute for Pediatric Trauma | Anthony E.Y.,Wake forest University | And 4 more authors.
48th Annual Rocky Mountain Bioengineering Symposium and 48th International ISA Biomedical Sciences Instrumentation Symposium 2011 | Year: 2011

Pediatric occupants are vulnerable in motor vehicle crashes (MVCs), and alternative restraints have been developed for their protection. T his study sought to characterize injuries in MVCs for pediatric occupants and to identify scenarios that m ay benefit from enhanced vehicle safety. Using the NASS-CDS database (2000-2008), pediatri c occupants (< 19 yr old) were characterized by their age and injuries to look at national averag es in MVCs. There were over 14 million pediatric injuries and non-injured occupants in weighted NASS-CDS (out of over 70 million total). Of these pediatric cases, 60% sustained injuries, which was comparable to the percentage of all occupants injured (65%). Six percent of NASS-CDS pediatric occupants had AIS 2+ injuries, which is the injury inclusion criteria for CIREN pediatric cases. CIREN was used to investigate pediatric occupants and injuries resulting from incorrect positioning and restrain ts according to NHTSA sugge stions. Results indicated that m any injured pediatric occupants were not properly restrained, with over 100 in the fr ont row of the vehicle under 13 years of age. There were also over 200 CIREN pediatric occupants under 4′ 9″ that were not seated in a child safety seat (CSS). The most frequently injured body region was the face, followed by the head and lower extremity. Eighty-six percent of head injuries and 82% of spinal injuries were AIS 2+. This study supports prior findings that demonstrate a need for enhanced public awareness for proper CSS use to reduce pediatric injuries in the future.

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