Citation

Pappas E, Shiyko MP, Ford KR, Myer GD, Hewett TE. Med. Sci. Sports Exerc. 2015; 48(1): 107-113.

Affiliation

1Discipline of Physiotherapy, Faculty of Health Sciences, University of Sydney, Lidcombe, NSW, Australia; 2Orthopaedic Sports Medicine Center of Ioannina, Department of Orthopaedic Surgery, School of Medicine, Ioannina, Greece; 3Department of Counseling Psychology, Bouve School of Health Sciences, Boston, MA; 4Department of Physical Therapy, School of Health Sciences, High Point University, High Point, NC; 5Department of Pediatrics, College of Medicine, University of Cincinnati, Cincinnati, OH; 6Division of Sports Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH; 7OSU Sports Medicine, The Sports Health & Performance Institute, Departments of Physiology & Cell Biology, Orthopaedic Surgery, Family Medicine and Biomedical Engineering, The Ohio State University, Columbus, OH; 8The Micheli Center for Sports Injury Prevention, Waltham, MA.

Copyright

(Copyright © 2015, Lippincott Williams and Wilkins)

DOI

10.1249/MSS.0000000000000750

PMID

26258858

Abstract

PURPOSE: To quantify the prevalence of biomechanical deficit patterns associated with ACL injury risk and their inter-connections in a large cohort of female athletes during an unanticipated cutting task.

METHODS: High school female athletes (N=721) performed an unanticipated cutting task in the biomechanics laboratory. Trunk and lower extremity 3D kinetics and kinematics were measured and entered into a latent profile analysis model.

RESULTS: Approximately 40% of female athletes demonstrated no biomechanical deficits and were categorized into the low risk group. The second most prevalent profile (24%) demonstrated a combination of high quadriceps and leg dominance deficits and was labeled as quadriceps-leg. The third most prevalent profile (22%) demonstrated a combination of trunk and leg dominance deficits and to lesser extent ligament dominance deficits, and was labeled as trunk-leg-ligament. Finally, the fourth profile (14%) demonstrated very high ligament dominance deficits only and it was labeled as ligament dominance profile.

CONCLUSIONS: This is the first study to identify the most common biomechanical profiles associated with ACL injury during a cutting task in a large cohort of female athletes. Approximately 60% of female athletes belong to one of the high-risk profiles. With the exception of the ligament dominance profile, the current analysis indicates that risk profiles consist of a combination of biomechanical deficits. The findings provide important insight into the prevalence of biomechanical deficits and future directions for the development of injury prevention programs. The findings can be used to guide the development of quick and easy tests that accurately categorize athletes into one of the profiles and subsequently prescribe tailored injury prevention programs that will be more effective and efficient than the current generic ones.

Language: en