Prediction of Lower Extremity Injuries from Vertical Jump Kinetic Data in Collegiate Athletes

Abstract

PURPOSE: The vertical jump provides critical kinetic information regarding athletic performance, and can be quantified by the force-time (F-T curve) with defined phases of movement. Alterations in the efficiency of mechanisms used for force production could potentially lead to abnormal force dissipation and resultant injury. The purpose of this study was to identify which force plate variables from a vertical jump task could identify collegiate athletes who sustained a lower extremity injury. METHODS: Vertical jump testing using a force plate with dedicated software (SpartaTrac system) was performed by all healthy varsity collegiate athletes at several intervals throughout the athletic year over 3 academic years. The testing procedure consisted of each subject performing a series of 6 consecutive vertical jumps. Injuries were documented by the team athletic trainers and verified with the health care organization’s electronic medical documentation system. Injuries were defined as occurring no more than 60 days after a jump and defined as lower extremity by OSICS 10 code. 234 lower extremity injuries were identified. Subjects were matched by age, sex and sport. Vertical jump variables used were load, explode and drive, operationally defined as the average eccentric rate of force development, average concentric force, and concentric impulse, respectively. Logistic regression was used to determine if the battery of variables could predict whether or not an athlete would sustain a lower extremity injury. Additionally, athletes who sustained an ACL injury were identified, matched, and analyzed correspondingly. RESULTS: Load, explode, and drive, when entered into the regression equation, showed the ability to predict lower extremity injury, χ2= 14.6, df=4, P < 0.01; with explode independently showing significant prediction at P = 0.02. Load, explode, and drive also showed the ability to predict ACL injury, χ2= 13.92, df = 3, P < 0.01, with load and explode independently showing significant prediction at P < 0.05. CONCLUSION: The force plate variables collected from vertical jumps were able to identify athletes who sustained a lower extremity injury. Additionally, these variables were able to identify athletes who sustained an ACL injury.