Pediatric spinal injury in the US: epidemiology and disparities

Abstract

<jats:sec> <jats:title>OBJECT</jats:title> <jats:p>In the US, race and economic status have pervasive associations with mechanisms of injury, severity of injury, management, and outcomes of trauma. The goal of the current study was to examine these relationships on a large scale in the setting of pediatric spinal injury.</jats:p></jats:sec> <jats:sec> <jats:title>METHODS</jats:title> <jats:p>Admissions for spinal fracture without or with spinal cord injury (SCI), spinal dislocation, and SCI without radiographic abnormality were identified in the Kids’ Inpatient Database (KID) and the National Trauma Data Bank (NTDB) registry for 2009. Patients ranged in age from birth up to 21 years. Data from the KID were used to estimate nationwide annual incidences. Data from the NTDB were used to describe patterns of injury in relation to age, race, and payor, with corroboration from the KID. Multiple logistic regression was used to model rates of mortality and spinal fusion.</jats:p></jats:sec> <jats:sec> <jats:title>RESULTS</jats:title> <jats:p>In 2009, the estimated incidence of hospital admission for spinal injury in the US was 170 per 1 million in the population under 21 years of age. The incidence of SCI was 24 per 1 million. Incidences varied regionally. Adolescents predominated. Patterns of injury varied by age, race, and payor. Black patients were more severely injured than patients of other races as measured by Injury Severity Scale scores. Among black patients with spinal injury in the NTDB, 23.9% suffered firearm injuries; only 1% of white patients suffered firearm injuries. The overall mortality rate in the NTDB was 3.9%. In a multivariate analysis that included a large panel of clinical and nonclinical factors, black race retained significance as a predictor of mortality (p = 0.006; adjusted OR 1.571 [1.141–2.163]). Rates of spinal fusion were associated with race and payor in the NTDB data and with payor in the KID: patients with better insurance underwent spinal fusion at higher rates.</jats:p></jats:sec> <jats:sec> <jats:title>CONCLUSIONS</jats:title> <jats:p>The epidemiology of pediatric spinal injury in the US cannot be understood apart from considerations of race and economic status.</jats:p></jats:sec>

Epidemiology of spinal cord injury without radiographic abnormality in children: A nationwide perspective

“…It should be noted that the relative rate of SCIWORA versus other types of spinal injuries was not evaluated in the present analysis as information on this subject is available in the literature. Piatt recently evaluated a similar patient sample and found SCIWORA to represent nearly 20 % of injuries in children aged less than 3 years, 9.4 % of injuries in children aged 3–12 years, and only 5 % of injuries in patients aged 13–20 years [ 9 ].…”

Pregnancy Outcomes in Women with Spinal Cord Injuries: A Population‐Based Study

“…Many of these studies were conducted in earlier time periods and may not reflect current treatment advances or population characteristics. Most relied on self‐reported outcomes, making nonresponse bias a concern, given that some nonwhite and disadvantaged groups are both more likely to sustain traumatic injuries and to have more severe injuries, to have congenital defects such as SB, and are historically less likely to participate in research studies . Many earlier studies were not population‐based, with results not representative of the larger community of women with these conditions.…”

Big Data Research in Pediatric Neurosurgery: Content, Statistical Output, and Bibliometric Analysis

“…However, 8 of these measures lacked CIs, and 75 lacked p values, yielding 381 (82%) with complete statistical data. A Bonferroni p value correction for statistical significance was performed in 4 studies [22-25]. …”

“…Big data can provide information on the associations of hospital type, provider caseload, and geography with outcomes, as has been nicely done for pediatric brain tumors, shunt surgery, and cerebrovascular pathology [37, 38, 45]. Also relevant would be their use in studies of epidemiologic, socioeconomic, or demographic questions, as they pertain to changes over time (trend analysis), for which there are a number of excellent examples [22, 23, 46-50]. …”