Pamela M Vacek1, James R Slauterbeck2, Timothy W Tourville3, Daniel R Sturnick2, Leigh-Ann Holterman1, Helen C Smith2, Sandra J Shultz4, Robert J Johnson2, Kelly J Tourville3, Bruce D Beynnon5. 1. Department of Medical Biostatistics, University of Vermont, Burlington, Vermont, USA. 2. McClure Musculoskeletal Research Center, Department of Orthopaedics and Rehabilitation, University of Vermont, Burlington, Vermont, USA. 3. Department of Rehabilitation and Movement Science, University of Vermont, Burlington, Vermont, USA. 4. Department of Kinesiology, University of North Carolina at Greensboro, Greensboro, North Carolina, USA. 5. McClure Musculoskeletal Research Center, Department of Orthopaedics and Rehabilitation, University of Vermont, Burlington, Vermont, USA bruce.beynnon@uvm.edu.
Abstract
BACKGROUND: Multivariate analysis that identifies the combination of risk factors associated with anterior cruciate ligament (ACL) trauma is important because it provides insight into whether a variable has a direct causal effect on risk or an indirect effect that is mediated by other variables. It can also reveal risk factors that might not be evident in univariate analyses; if a variable's effect is moderated by other variables, its association with risk may be apparent only after adjustment for the other variables. Most important, multivariate analyses can identify combinations of risk factors that are more predictive of risk than individual risk factors. HYPOTHESIS: A diverse combination of risk factors predispose athletes to first-time noncontact ACL injury, and these relationships are different for male and female athletes. STUDY DESIGN: Case-control study; Level of evidence, 3. METHODS: Athletes competing in organized sports at the high school and college levels participated in this study. Data from injured subjects (109 suffering an ACL injury) and matched controls (227 subjects) from the same athletic team were analyzed with multivariate conditional logistic regression to examine the effects of combinations of variables (demographic characteristics, joint laxity, lower extremity alignment, strength, and personality traits) on the risk of suffering their first ACL injury and to construct risk models. RESULTS: For male athletes, increases in anterior-posterior displacement of the tibia relative to the femur (knee laxity), posterior knee stiffness, navicular drop, and a decrease in standing quadriceps angle were jointly predictive of suffering an ACL injury. For female athletes the combined effects of having a parent who had suffered an ACL injury and increases in anterior-posterior knee laxity and body mass index were predictive of ACL injury. CONCLUSION: Multivariate models provided more information about ACL injury risk than individual risk factors. Both male and female risk models included increased anterior-posterior knee laxity as a predictor of ACL injury but were otherwise dissimilar.
BACKGROUND: Multivariate analysis that identifies the combination of risk factors associated with anterior cruciate ligament (ACL) trauma is important because it provides insight into whether a variable has a direct causal effect on risk or an indirect effect that is mediated by other variables. It can also reveal risk factors that might not be evident in univariate analyses; if a variable's effect is moderated by other variables, its association with risk may be apparent only after adjustment for the other variables. Most important, multivariate analyses can identify combinations of risk factors that are more predictive of risk than individual risk factors. HYPOTHESIS: A diverse combination of risk factors predispose athletes to first-time noncontact ACL injury, and these relationships are different for male and female athletes. STUDY DESIGN: Case-control study; Level of evidence, 3. METHODS: Athletes competing in organized sports at the high school and college levels participated in this study. Data from injured subjects (109 suffering an ACL injury) and matched controls (227 subjects) from the same athletic team were analyzed with multivariate conditional logistic regression to examine the effects of combinations of variables (demographic characteristics, joint laxity, lower extremity alignment, strength, and personality traits) on the risk of suffering their first ACL injury and to construct risk models. RESULTS: For male athletes, increases in anterior-posterior displacement of the tibia relative to the femur (knee laxity), posterior knee stiffness, navicular drop, and a decrease in standing quadriceps angle were jointly predictive of suffering an ACL injury. For female athletes the combined effects of having a parent who had suffered an ACL injury and increases in anterior-posterior knee laxity and body mass index were predictive of ACL injury. CONCLUSION: Multivariate models provided more information about ACL injury risk than individual risk factors. Both male and female risk models included increased anterior-posterior knee laxity as a predictor of ACL injury but were otherwise dissimilar.
Authors: Sandra J Shultz; Randy J Schmitz; Kenneth L Cameron; Kevin R Ford; Dustin R Grooms; Lindsey K Lepley; Gregory D Myer; Brian Pietrosimone Journal: J Athl Train Date: 2019-08-28 Impact factor: 2.860
Authors: Bruce D Beynnon; Niccolo Fiorentino; Mack Gardner-Morse; Timothy W Tourville; James R Slauterbeck; Daniel R Sturnick; Erin C Argentieri; Carl W Imhauser Journal: J Orthop Res Date: 2019-11-19 Impact factor: 3.494
Authors: James G Levins; Daniel R Sturnick; Erin C Argentieri; Mack Gardner-Morse; Pamela M Vacek; Michael J Desarno; Timothy W Tourville; James R Slauterbeck; Bruce D Beynnon Journal: Am J Sports Med Date: 2016-08-11 Impact factor: 6.202
Authors: Thomas R Pfeiffer; Ajay C Kanakamedala; Elmar Herbst; Kanto Nagai; Conor Murphy; Jeremy M Burnham; Adam Popchak; Richard E Debski; Volker Musahl Journal: Knee Surg Sports Traumatol Arthrosc Date: 2017-08-19 Impact factor: 4.342