On the ability of experimental impact measures to predict tooth injuries in an ex vivo swine model

Background/Aim Impact to the orofacial region, in particular teeth, is a frequent incident leading to injury in many sports and can result in health and economic costs for the injured individual. The majority of previous work has applied synthetic models such as plaster or stone, to form analogs of...

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Veröffentlicht in:Dental traumatology 2021-06, Vol.37 (3), p.464-473
Hauptverfasser: Houg, Kathryn P., Adanty, Kevin, MacGillivray, Samantha R., McAllister, Lowell, Levin, Liran, Alexiou, Maria, Graf, Daniel, Romanyk, Dan L., Dennison, Christopher R.
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Sprache:eng
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Zusammenfassung:Background/Aim Impact to the orofacial region, in particular teeth, is a frequent incident leading to injury in many sports and can result in health and economic costs for the injured individual. The majority of previous work has applied synthetic models such as plaster or stone, to form analogs of relevant structures to study the potential for impact‐induced injury. Biomechanical studies that have applied tissue models (animal or human) for the purpose of determining the biomechanical measures associated with dental injury are rare. The aim of this study was to apply a simple ex vivo model based on swine dentition to ascertain which of a select list of measurable quantities associated with impact mechanics could predict luxation and fracture of teeth due to impact. Methods Mandibular central incisors of ex vivo swine dentitions were impacted using a linear drop tower with heights ranging from 1.20 m to 2.42 m. Seven mechanical predictors were assessed at impact and were then subjected to binary logistic regression techniques to determine which was the best predictor of luxations or fractures of the teeth. Results Of the seven mechanical predictors, (1) the velocity of the impacting body (R2 = 0.477), (2) a proxy measure for the change in kinetic energy of the impacting body (R2 = 0.586), and (3) the approximate energy absorbed by the tissue (R2 = 0.722) were found to be statistically significantly different (p 
ISSN:1600-4469
1600-9657
DOI:10.1111/edt.12645