Three-Dimensional Motion Analysis Validation of a Clinic-Based Nomogram Designed to Identify High ACL Injury Risk in Female Athletes
ABSTRACT 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.
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ABSTRACT: Available methods for screening anterior cruciate ligament (ACL) injury risk are effective but limited in application as they generally rely on expensive and time-consuming biomechanical movement analysis. A potentially efficient alternative to biomechanical screening is skilled movement analysis via visual inspection (ie, having experts estimate injury risk factors based on observations of athletes' movements). To develop a brief, valid psychometric assessment of ACL injury risk factor estimation skill: the ACL Injury Risk Estimation Quiz (ACL-IQ). Cohort study (diagnosis); Level of evidence, 3. A total of 660 individuals participated in various stages of the study, including athletes, physicians, physical therapists, athletic trainers, exercise science researchers/students, and members of the general public in the United States. The ACL-IQ was fully computerized and made available online (www.ACL-IQ.org). Item sampling/reduction, reliability analysis, cross-validation, and convergent/discriminant validity analyses were conducted to refine the efficiency and validity of the assessment. Psychometric optimization techniques identified a short (mean time, 2 min 24 s), robust, 5-item assessment with high reliability (test-retest: r = 0.90) and high test sensitivity (average difference of exercise science professionals vs general population: Cohen d = 2). Exercise science professionals and individuals from the general population scored 74% and 53% correct, respectively. Convergent and discriminant validity was demonstrated. Scores on the ACL-IQ were best predicted by ACL knowledge and specific judgment strategies (ie, cue use) and were largely unrelated to domain-general spatial/decision-making ability, personality, or other demographic variables. Overall, 23% of the total sample (40% of exercise science professionals; 6% of general population) performed better than or equal to the ACL nomogram. This study presents the results of a systematic approach to assess individual differences in ACL injury risk factor estimation skill; the assessment approach is efficient (ie, it can be completed in <3 min) and psychometrically robust. The results provide evidence that some individuals have the ability to visually estimate ACL injury risk factors more accurately than other instrument-based ACL risk estimation methods (ie, ACL nomogram). The ACL-IQ provides the foundation for assessing the efficacy of observational ACL injury risk factor assessment (ie, does simple skilled visual inspection reduce ACL injuries?). The ACL-IQ can also be used to increase our understanding of the perceptual-cognitive mechanisms underlying injury risk assessment expertise, which can be leveraged to accelerate learning and improve performance. © 2015 The Author(s).The American Journal of Sports Medicine 04/2015; DOI:10.1177/0363546515580791 · 4.70 Impact Factor
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ABSTRACT: Since previous numbers-needed-to-treat (NNT) and relative risk reduction (RRR) report, a few studies were published to evaluate prophylactic effectiveness of neuromuscular training for anterior cruciate ligament (ACL) injury in female athletes. The purpose of the current analyses was to determine the effectiveness of neuromuscular training interventions in reducing both non-contact and overall ACL injury risk in female athletes through RRR and NNT. The keywords 'knee', 'anterior cruciate ligament', 'ACL', 'prospective', 'neuromuscular', 'training', 'female' and 'prevention' were searched to find studies published from 1995 to 2011 in PubMed and EBSCO (CINAHL, Health source, MEDLINE and SPORT Discus). Inclusion criteria required that relevant studies: recruited physically active young girls as subjects, documented the number of ACL injuries, employed a neuromuscular training intervention, and used a prospective controlled study design. The numbers of non-contact and overall ACL injuries, subjects and observation time period were used to calculate RRR and NNT for each study. A total of 12 studies met the inclusion criteria. There was a 73.4% (95% CI 62.5% to 81.1%) and 43.8% (95% CI 28.9% to 55.5%) of RRR for non-contact and overall ACL injuries. From the NNT analysis, it was determined that, respectively, 108 (95% CI 86 to 150) and 120 (95% CI 74 to 316) individuals would need to be trained to prevent one non-contact or one overall ACL injury over the course of one competitive season. Although the RRR analysis indicated prophylactic benefits of neuromuscular training, the relatively large NNT indicated that many athletes are needed to prevent one ACL injury. A future direction to reduce NNT and improve the efficiency of ACL injury-prevention strategies is to develop a screening system for identifying at-risk athletes.British journal of sports medicine 06/2012; 46(14):979-88. DOI:10.1136/bjsports-2011-090895 · 4.17 Impact Factor
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ABSTRACT: Multi-center collaborations provide a powerful alternative to overcome the inherent limitations to single-center investigations. Specifically, multi-center projects can support large-scale prospective, longitudinal studies that investigate relatively uncommon outcomes, such as anterior cruciate ligament injury. This project was conceived to assess within- and between-center reliability of an affordable, clinical nomogram utilizing two-dimensional video methods to screen for risk of knee injury. The authors hypothesized that the two-dimensional screening methods would provide good-to-excellent reliability within and between institutions for assessment of frontal and sagittal plane biomechanics.