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Disability risk in pediatric motor vehicle crash occupants

Doud, Andrea N. MD; Schoell, Samantha L. MS; Weaver, Ashley A. PhD; Talton, Jennifer W. MS; Barnard, Ryan T. MS; Petty, John K. MD; Stitzel, Joel D. PhD

Journal of Trauma and Acute Care Surgery: May 2017 - Volume 82 - Issue 5 - p 933–938
doi: 10.1097/TA.0000000000001418
Original Articles

BACKGROUND Mortality rates among children in motor vehicle crashes (MVCs) are typically low; however, nonfatal injuries can vary in severity by imposing differing levels of short- and long-term disability. To better discriminate the severity of nonfatal MVC injuries, a pediatric-specific disability risk (DR) metric was created.

METHODS The National Automotive Sampling System 2000 to 2011 was used to define the top 95% most common Abbreviated Injury Scale (AIS) 2+ injuries among pediatric MVC occupants. Functional Independence Measure scores were abstracted from the National Trauma Data Bank 2002 to 2006. Multiple imputation was used to account for missing data. The DR and coinjury-adjusted DR (DRMAIS) of the most common AIS 2+ MVC-induced injuries were calculated for 7-year-old to 18-year-old children by determining the proportion of those disabled after an injury to those sustaining the injury. DR and DRMAIS values ranged from 0 to 1, representing 0% to 100% DR.

RESULTS The mean DR and DRMAIS of all injuries were 0.290 and 0.191, respectively. DR and DRMAIS were greatest for injuries to the head (DR, 0.340; DRMAIS, 0.279), thorax (DR, 0.320; DRMAIS, 0.233), and spine (DR, 0.315; DRMAIS, 0.200). The mean DR and DRMAIS increased with increasing AIS severity but there was significant variation and overlapping values across AIS severity levels. Comparison of DRMAIS to coinjury-adjusted mortality risk (MRMAIS) revealed that among 118 injuries with MRMAIS of 0.000, DRMAIS ranged from 0.000 to 0.429.

CONCLUSION Incorporation of DR metrics into injury severity metrics may improve the ability to distinguish between the severity of different nonfatal injuries. This is especially crucial in the pediatric population where permanent disability can result in a high number of years lost due to disability. The accuracy of such severity metrics is crucial to the success of pediatric triage algorithms such as Advanced Automatic Crash Notification algorithms.

LEVEL OF EVIDENCE Epidemiologic/prognostic study, level III.

Supplemental digital content is available in the text.

From the Department of General Surgery (A.N.D., J.K.P.), Wake Forest School of Medicine; Childress Institute for Pediatric Trauma (A.N.D.); Department of Biomedical Engineering (S.L.S., A.A.W., J.D.S.), and the Division of Public Health Sciences (J.W.T., R.T.B.), Wake Forest School of Medicine, Winston-Salem, North Carolina.

Submitted: January 11, 2017, Revised: February 7, 2017, Accepted: February 15, 2017, Published online: March 8, 2017.

Supplemental digital content is available for this article. Direct URL citations appear in the printed text, and links to the digital files are provided in the HTML text of this article on the journal’s Web site (

Address for reprints: Ashley A. Weaver, PhD, Department of Biomedical Engineering, Wake Forest University School of Medicine, Medical Center Blvd, Winston-Salem, NC 27157; email:

© 2017 Lippincott Williams & Wilkins, Inc.