title: Identification of trauma patients at risk of thoracic aortic tear by mechanism of injury.
abstract: OBJECTIVE
  We sought to identify potential measurable on-scene information that would assist clinicians in the identification of patients at risk for thoracic aortic tear (AT) after vehicular trauma.
  
  
  METHODS
  Data were prospectively collected at the scene of 295 motor vehicle crashes from 1995 to 1999. There were 34 cases (12%) with AT. Scene data consisted of vehicle maximal crush, maximal intrusion into the occupant compartment, change in velocity (Delta V) and principal direction of force. Thoracic aortic injuries were confirmed radiographically or at autopsy. Crash factors were analyzed for correlation with AT by logistic regression.
  
  
  RESULTS
  Delta V > or = 20 mph and near-side impact were the factors having the strongest correlation with thoracic aortic injury. Delta V > or = 20 mph (n = 32 with AT) had an odds ratio = 6.4, (p < 0.01). Near impact (n = 20 with AT) had an odds ratio = 2.3, (p < 0.05) and intrusion > or = 15 inches had an odds ratio = 3.2, p < 0.05. The sensitivity, specificity, and accuracy of the presence of near impact, Delta V > or = 20 mph, or both, were 100%, 34%, and 64%. The positive and negative predictive values were 16% and 100%, respectively. There was no relationship of AT to use of seat belts or airbags.
  
  
  CONCLUSIONS
  Thoracic aortic injury after vehicular collision can be reliably excluded if near-impact, Delta V > or = 20 mph, or intrusion > or = 15 inches are not present. Mechanism of injury in the form of crash scene information may aid clinicians in identifying individuals at risk for thoracic aortic tear after vehicular trauma.
authors.affiliation: William Lehman Injury Research Center, Ryder Trauma Center, Miami, Florida, USA.
authors.forename: T G
authors.initials: TG
authors.lastname: Horton
authors.forename: S M
authors.initials: SM
authors.lastname: Cohn
authors.forename: M P
authors.initials: MP
authors.lastname: Heid
authors.forename: J S
authors.initials: JS
authors.lastname: Augenstein
authors.forename: J C
authors.initials: JC
authors.lastname: Bowen
authors.forename: M G
authors.initials: MG
authors.lastname: McKenney
authors.forename: R C
authors.initials: RC
authors.lastname: Duncan
mesh_terms: D000063:Accidents, Traffic / Q000706:statistics & numerical data; D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D003625:Data Collection; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D011446:Prospective Studies; D011859:Radiography; D012307:Risk Factors; D013895:Thoracic Arteries / Q000000981:diagnostic imaging / Q000293:injuries*; D014947:Wounds and Injuries / Q000209:etiology*