TY - JOUR
T1 - Three-dimensional motion analysis validation of a clinic-based nomogram designed to identify high ACL injury risk in female athletes
AU - Myer, Gregory D.
AU - Ford, Kevin R.
AU - Khoury, Jane
AU - Hewett, Timothy E.
N1 - Funding Information:
The authors would like to acknowledge funding support from National Institutes of Health/NIAMS Grants R01-AR049735, R01-AR05563, and R01-AR056259. The authors would like to thank Boone County School District, KY, particularly School Superintendent Randy Poe, for participation in this study. The authors would also like to thank Mike Blevins, Ed Massey, and the athletes and coaches of Boone County public school district for their participation in this study. The authors would like to acknowledge the Sports Medicine Biodynamics Team, who worked together to make large data collection sessions. Finally, the authors would like to acknowledge Sam Wordeman for his assistance with the use of R-project software and Dr. Mitch Rauh for his helpful advice throughout this investigation. Results of the present study do not constitute endorsement by American College of Sports Medicine.
PY - 2011/2
Y1 - 2011/2
N2 - Aims: Prospective measures of high knee abduction moment (KAM) during landing identify female athletes at increased risk for anterior cruciate ligament (ACL) injury. Laboratory-driven measurements predict high KAM with 90% accuracy. This study aimed to validate the clinic-based variables against 3-dimensional motion analysis measurements. Methods: Twenty female basketball, soccer, and volleyball players (age, 15.9 ± 1.3 years; height, 163.6 ± 9.9 cm; body mass, 57.0 ± 12.1 kg) were tested using 3-dimensional motion analysis and clinic-based techniques simultaneously. Multiple logistic regression models have been developed to predict high KAM (a surrogate for ACL injury risk) using both measurement techniques. Clinic-based measurements were validated against 3-dimensional motion analysis measures, which were recorded simultaneously, using within- and between-method reliability as well as sensitivity and specificity comparisons. Results: The within-variable analysis showed excellent inter-rater reliability for all variables using both 3-dimensional motion analysis and clinic-based methods, with intraclass correlation coefficients (ICCs) that ranged from moderate to high (0.60-0.97). In addition, moderate-to-high agreement was observed between 3-dimensional motion analysis and clinic-based measures, with ICCs ranging from 0.66 to 0.99. Bland-Altman plots confirmed that each variable provided no systematic shift between 3-dimensional motion analysis and clinic-based methods, and there was no association between difference and average. A developed regression equation also supported model validity with > 75% prediction accuracy of high KAM using both the 3-dimensional motion analysis and clinic-based techniques. Conclusion: The current validation provides the critical next step to merge the gap between laboratory identification of injury risk factors and clinical practice. Implementation of the developed prediction tool to identify female athletes with high KAM may facilitate the entry of female athletes with high ACL injury risk into appropriate injury-prevention programs.
AB - Aims: Prospective measures of high knee abduction moment (KAM) during landing identify female athletes at increased risk for anterior cruciate ligament (ACL) injury. Laboratory-driven measurements predict high KAM with 90% accuracy. This study aimed to validate the clinic-based variables against 3-dimensional motion analysis measurements. Methods: Twenty female basketball, soccer, and volleyball players (age, 15.9 ± 1.3 years; height, 163.6 ± 9.9 cm; body mass, 57.0 ± 12.1 kg) were tested using 3-dimensional motion analysis and clinic-based techniques simultaneously. Multiple logistic regression models have been developed to predict high KAM (a surrogate for ACL injury risk) using both measurement techniques. Clinic-based measurements were validated against 3-dimensional motion analysis measures, which were recorded simultaneously, using within- and between-method reliability as well as sensitivity and specificity comparisons. Results: The within-variable analysis showed excellent inter-rater reliability for all variables using both 3-dimensional motion analysis and clinic-based methods, with intraclass correlation coefficients (ICCs) that ranged from moderate to high (0.60-0.97). In addition, moderate-to-high agreement was observed between 3-dimensional motion analysis and clinic-based measures, with ICCs ranging from 0.66 to 0.99. Bland-Altman plots confirmed that each variable provided no systematic shift between 3-dimensional motion analysis and clinic-based methods, and there was no association between difference and average. A developed regression equation also supported model validity with > 75% prediction accuracy of high KAM using both the 3-dimensional motion analysis and clinic-based techniques. Conclusion: The current validation provides the critical next step to merge the gap between laboratory identification of injury risk factors and clinical practice. Implementation of the developed prediction tool to identify female athletes with high KAM may facilitate the entry of female athletes with high ACL injury risk into appropriate injury-prevention programs.
KW - Anterior cruciate ligament injury
KW - Drop-vertical jump landing
KW - High-risk biomechanics
KW - Injury prevention
KW - Knee
KW - Young athletes
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U2 - 10.3810/psm.2011.02.1858
DO - 10.3810/psm.2011.02.1858
M3 - Article
C2 - 21378483
AN - SCOPUS:79952240847
SN - 0091-3847
VL - 39
SP - 19
EP - 28
JO - Physician and Sportsmedicine
JF - Physician and Sportsmedicine
IS - 1
ER -