Download PDF
Int J Sports Med 2019; 40(03): 191-199
DOI: 10.1055/a-0756-9659
Orthopedics & Biomechanics
© Georg Thieme Verlag KG Stuttgart · New York

A Reliable Video-based ACL Injury Screening Tool for Female Team Sport Athletes

Gillian Weir
1   Biomechanics Laboratory, The University Massachusetts, Amherst, United States
,
Jacqueline Alderson
2   School of Human Sciences, The University of Western Australia, Perth, Australia
3   Auckland University of Technology, Sports Performance Research Institute New Zealand (SPRINZ), Auckland, New Zealand
,
Natalie Smailes
2   School of Human Sciences, The University of Western Australia, Perth, Australia
,
Bruce Elliott
2   School of Human Sciences, The University of Western Australia, Perth, Australia
,
Cyril Donnelly
2   School of Human Sciences, The University of Western Australia, Perth, Australia
› Author Affiliations
Further Information

Publication History



accepted 01 October 2018

Publication Date:
10 January 2019 (online)

Also available at
    Permissions and Reprints

Abstract

This study aimed to develop a 2-dimensional (2D) video screening tool capable of predicting an athlete’s peak 3-dimensional (3D) knee moments during unplanned sidestepping. 2D video-based kinematic measures were simultaneously captured with 3D peak knee moments for 30 female field hockey players (15 junior, 15 senior). Intra- and intertester repeatability of 2D kinematic measures was performed. Then, linear regression models were used to model 3D knee moments from 2D kinematic variables utilizing 80% of the sample (n=24). Regression equations were then validated on the remaining 20% of the sample (n=6). Angular 2D measures had good-excellent intra- (ICC=0.936–0.998) and intertester (ICC=0.662–0.949) reliability. Displacement measures had poor-excellent intra- (ICC=0.377–0.539) and inter-tester (ICC=0.219–0.869) reliability. Significant independent predictors of peak knee moments were dynamic knee valgus, knee flexion angle at foot strike, trunk flexion range of motion (ROM), trunk lateral flexion, hip abduction and knee flexion ROM (P<0.05). Regression equations generated from these models effectively predicted peak knee extension, valgus and internal rotation moments (i. e., were not different from measured values P>0.05, ES<0.4) in the 20% subsample. 2D video-based measurements of an athlete's full body kinematics during unplanned sidestepping provide a reliable, specific, sensitive and cost-effective means for screening female team sport athletes.

Key words

injury prevention - hockey - valgus knee moments - training - anterior cruciate ligament
 

  • References

  • 1 Agel J, Arendt EA, Bershadsky B. Anterior cruciate ligament injury in national collegiate athletic association basketball and soccer. Am J Sports Med 2005; 33: 524-531
    CrossrefPubMedGoogle Scholar
  • 2 Arendt EA, Agel J, Dick R. Anterior cruciate ligament injury patterns among collegiate men and women. J Athl Train 1999; 34: 86-92
    PubMedGoogle Scholar
  • 3 Bahr R. Why screening tests to predict injury do not work—and probably never will…: A critical review. Br J Sports Med 2016; 50: 776-780
    CrossrefPubMedGoogle Scholar
  • 4 Besier TF, Lloyd DG, Ackland TR, Cochrane JL. Anticipatory effects on knee joint loading during running and cutting maneuvers. Med Sci Sports Exerc 2001; 33: 1176-1181
    PubMedGoogle Scholar
  • 5 Besier TF, Lloyd DG, Cochrane JL, Ackland TR. External loading of the knee joint during running and cutting maneuvers. Med Sci Sports Exerc 2001; 33: 1168-1175
    PubMedGoogle Scholar
  • 6 Besier TF, Sturnieks DL, Alderson JA, Lloyd DG. Repeatability of gait data using a functional hip joint centre and a mean helical knee axis. J Biomech 2003; 36: 1159-1168
    CrossrefPubMedGoogle Scholar
  • 7 Chappell JD, Limpisvasti O. Effect of a neuromuscular training program on the kinetics and kinematics of jumping tasks. Am J Sports Med 2008; 36: 1081-1086
    CrossrefPubMedGoogle Scholar
  • 8 Cochrane JL, Lloyd DG, Besier TF, Elliott BC, Doyle TL, Ackland TR. Training affects knee kinematics and kinetics in cutting maneuvers in sport. Med Sci Sports Exerc 2010; 42: 1535-1544
    CrossrefPubMedGoogle Scholar
  • 9 Cohen J. Statistical Power Analyses for the Social Sciences. Hillsdale NJ: Lawrence Erlbaum Assoc; 1988
    Google Scholar
  • 10 Dempsey AR, Lloyd DG, Elliott BC, Steele JR, Munro BJ, Russo KA. The effect of technique change on knee loads during sidestep cutting. Med Sci Sports Exerc 2007; 39: 1765-1773
    CrossrefPubMedGoogle Scholar
  • 11 Donnelly CJ, Elliott BC, Ackland TR, Doyle TLA, Beiser TF, Finch CF, Cochrane JL, Dempsey AR, Lloyd DG. An anterior cruciate ligament injury prevention framework: Incorporating the recent evidence. Res Sports Med 2012; 20: 239-262
    CrossrefPubMedGoogle Scholar
  • 12 Donnelly CJ, Elliott BC, Doyle TL, Finch CF, Dempsey AR, Lloyd DG. Changes in knee joint biomechanics following balance and technique training and a season of Australian football. Br J Sports Med 2012; 46: 917-922
    CrossrefPubMedGoogle Scholar
  • 13 Donnelly CJ, Lloyd DG, Elliott BC, Reinbolt JA. Optimizing whole-body kinematics to minimize valgus knee loading during sidestepping: Implications for ACL injury risk. J Biomech 2012; 45: 1491-1497
    CrossrefPubMedGoogle Scholar
  • 14 Ford KR, Myer GD, Hewett TE. Valgus knee motion during landing in high school female and male basketball players. Med Sci Sports Exerc 2003; 35: 1745-1750
    CrossrefPubMedGoogle Scholar
  • 15 Gianotti SM, Marshall SW, Hume PA, Bunt L. Incidence of anterior cruciate ligament injury and other knee ligament injuries: A national population-based study. J Sci Med Sport 2009; 12: 622-627
    CrossrefPubMedGoogle Scholar
  • 16 Hallgren KA. Computing inter-rater reliability for observational data: An overview and tutorial. Tutor Quant Methods Psychol 2012; 8: 23-34
    PubMedGoogle Scholar
  • 17 Harriss DJ, MacSween A, Atkinson G. Standards for ethics in sport and exercise science research: 2018 update. Int J Sports Med 2017; 38: 1126-1131
    Article in Thieme ConnectPubMedGoogle Scholar
  • 18 Hashemi J, Breighner R, Chandrashekar N, Hardy DM, Chaudhari AM, Shultz SJ, Slauterbeck JR, Beynnon BD. Hip extension, knee flexion paradox: A new mechanism for non-contact ACL injury. J Biomech 2011; 44: 577-585
    CrossrefPubMedGoogle Scholar
  • 19 Hashemi J, Breighner R, Jang T-H, Chandrashekar N, Ekwaro-Osire S, Slauterbeck JR. Increasing pre-activation of the quadriceps muscle protects the anterior cruciate ligament during the landing phase of a jump: An in vitro simulation. Knee 2010; 17: 235-241
    CrossrefPubMedGoogle Scholar
  • 20 Havens KL, Sigward SM. Cutting mechanics: Relation to performance and anterior cruciate ligament injury risk. Med Sci Sports Exerc 2015; 47: 818-824
    CrossrefPubMedGoogle Scholar
  • 21 Havens KL, Sigward SM. Whole body mechanics differ among running and cutting maneuvers in skilled athletes. Gait Posture 2015; 42: 240-245
    CrossrefPubMedGoogle Scholar
  • 22 Hewett TE, Myer GD, Ford KR, Heidt RS, Colosimo AJ, McLean SG, Van den Bogert AJ, Paterno MV, Succop P. Biomechanical measures of neuromuscular control and valgus loading of the knee predict anterior cruciate ligament injury risk in female athletes. Am J Sports Med 2005; 33: 492-501
    CrossrefPubMedGoogle Scholar
  • 23 Jones PA, Herrington LC, Graham-Smith P. Technique determinants of knee joint loads during cutting in female soccer players. Hum Mov Sci 2015; 42: 203-211
    CrossrefPubMedGoogle Scholar
  • 24 Koga H, Nakamae A, Shima Y, Iwasa J, Myklebust G, Engebretsen L, Bahr R, Krosshaug T. Mechanisms for noncontact anterior cruciate ligament injuries: Knee joint kinematics in 10 injury situations from female team handball and basketball. Am J Sports Med 2010; 38: 2218-2225
    CrossrefPubMedGoogle Scholar
  • 25 Kristianslund E, Krosshaug T, Van den Bogert AJ. Effect of low-pass filtering on joint moments from inverse dynamics: Implications for injury prevention. J Biomech 2012; 45: 666-671
    CrossrefPubMedGoogle Scholar
  • 26 Krosshaug T, Slauterbeck JR, Engebretsen L, Bahr R. Biomechanical analysis of anterior cruciate ligament injury mechanisms: Three-dimensional motion reconstruction from video sequences. Scand J Med Sci Sports 2007; 17: 508-519
    PubMedGoogle Scholar
  • 27 Lim B-O, Lee YS, Kim JG, An KO, Yoo J, Kwon YH. Effects of sports injury prevention training on the biomechanical risk factors of anterior cruciate ligament injury in high school female basketball players. Am J Sports Med 2009; 37: 1728-1734
    CrossrefPubMedGoogle Scholar
  • 28 McLean SG, Huang X, Van Den Bogert AJ. Association between lower extremity posture at contact and peak knee valgus moment during sidestepping: Implications for ACL injury. Clin Biomech 2005; 20: 863-870
    CrossrefPubMedGoogle Scholar
  • 29 McLean SG, Walker K, Ford KR, Myer GD, Hewett TE, van den Bogert AJ. Evaluation of a two dimensional analysis method as a screening and evaluation tool for anterior cruciate ligament injury. Br J Sports Med 2005; 39: 355-362
    CrossrefPubMedGoogle Scholar
  • 30 Myer GD, Ford KR, Brent JL, Hewett TE. Differential neuromuscular training effects on ACL injury risk factors in “high-risk” versus “low-risk” athletes. BMC Musculoskelet Disord 2007; 8: 39
    CrossrefPubMedGoogle Scholar
  • 31 Myer GD, Ford KR, Hewett TE. Tuck jump assessment for reducing anterior cruciate ligament injury risk. Athl Ther Today 2008; 13: 39-44
    PubMedGoogle Scholar
  • 32 Myer GD, Ford KR, Khoury J, Succop P, Timothy EH.. Biomechanics laboratory-based prediction algorithm to identify female athletes with high knee loads that increase risk of ACL injury. Br J Sports Med 2010; 45: 245-252
    PubMedGoogle Scholar
  • 33 Noyes FR, Barber-Westin SD, Fleckenstein C, Walsh C, West J. The drop-jump screening test: Difference in lower limb control by gender and effect of neuromuscular training in female athletes. Am J Sports Med 2005; 33: 197-207
    CrossrefPubMedGoogle Scholar
  • 34 Padua DA, Marshall SW, Boling MC, Thigpen CA, Garrett Jr WE, Beutler AI. The Landing Error Scoring System (LESS) is a valid and reliable clinical assessment tool of jump-landing biomechanics: the JUMP-ACL study. Am J Sports Med 2009; 37: 1996-2002
    CrossrefPubMedGoogle Scholar
  • 35 Robinson MA, Donnely CJ, Vanrenterghem J, Pataky TC. Sagittal plane kinematics predict non-sagittal joint moments in unplanned sidestepping. In: The 25th Congress of the International Society of Biomechanics, Glasgow, UK. 12th–16th July, 2015
    PubMed
  • 36 Sigward S, Powers CM. The influence of experience on knee mechanics during side-step cutting in females. Clin Biomech 2006; 21: 740-747
    CrossrefPubMedGoogle Scholar
  • 37 Vanrenterghem J, Venables E, Pataky T, Robinson MA. The effect of running speed on knee mechanical loading in females during side cutting. J Biomech 2012; 45: 2444-2449
    CrossrefPubMedGoogle Scholar
  • 38 Winter DA. Biomechanics and Motor Control of Human Movement. 4th ed Hoboken, NJ: John Wiley & Sons; 2009
    Google Scholar
  • 39 Wu G, Siegler S, Allard P, Kirtley C, Leardini A, Rosenbaum D, Whittle M, D’Lima D, Cristofolini L, Witte H. ISB recommendation on definitions of joint coordinate system of various joints for the reporting of human joint motion—part I: Ankle, hip, and spine. J Biomech 2002; 35: 543-548
    CrossrefPubMedGoogle Scholar
  • 40 Zazulak BT, Hewett TE, Reeves NP, Goldberg B, Cholewicki J. Deficits in neuromuscular control of the trunk predict knee injury risk. Am J Sports Med 2007; 35: 1123-1130
    CrossrefPubMedGoogle Scholar