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Table of Contents
ORIGINAL ARTICLE
Year : 2019  |  Volume : 9  |  Issue : 1  |  Page : 6-14

An analysis of musculoskeletal variables, comparative to team norms, leading to an anterior cruciate ligament rupture in a female soccer player


1 University of Pittsburgh, Neuromuscular Research Laboratory, Pittsburgh, PA, USA
2 Michael W. Krzyzewski Human Performance Laboratory, Duke University, Durham, NC, USA
3 Department of Physical Therapy, Augusta University, Augusta, GA, USA
4 Department of Athletics, University of Pittsburgh, Petersen Events Center, Pittsburgh, PA, USA

Date of Submission01-Aug-2019
Date of Decision15-Aug-2019
Date of Acceptance30-Aug-2019
Date of Web Publication28-Feb-2020

Correspondence Address:
Dr. Caleb D Johnson
Harvard Medical School, Spaulding National Running Center, 1575 Cambridge St., Cambridge, MA 02138
USA
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/DORJ.DORJ_2_19

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  Abstract 


Aim: The identification of sport- and gender-specific, prospective, and modifiable risk factors contributing to noncontact anterior cruciate ligament (ACL) injury is limited. This lack of information leaves clinicians at a loss in practicing evidence-based injury prevention. The purpose of this study is to describe the methods by which a female soccer player suffering from a noncontact ACL injury was compared to the rest of her team to identify modifiable strength and flexibility deficits possibly contributing to the injury.
Materials and Methods: Twenty-two individuals were recruited from a Division I, female soccer team (age = 19.3 ± 1.2 years). All testing was completed 2 months before competitive play. Strength was assessed for ankle inversion/eversion and dorsiflexion (AIS/AES, ADS), knee flexion/extension (KFS/KES), hip abduction/adduction (HABS/HADS), and hip internal/external rotation (HIS/HES). Agonist/antagonist ratios were also calculated. Flexibility was assessed for active ankle dorsiflexion (DF), weight-bearing ankle DF mobility, hamstring flexibility with passive hip flexion (PHF), and active knee extension. The ACL case's strength and flexibility variables were compared to team averages for the dominant leg (affected side) using one-sample t-tests and Wilcoxon signed-rank tests.
Results: The ACL case's injury was the result of a planting and cutting motion. The ACL case displayed significantly lower ADS (−7.84% of body weight), AIS (−7.41%), AES (−6.58%), KFS (−5.39%), HABS (−3.14%), HES (−2.84%), and a significantly lower HABS-to-HADS ratio (−0.12) compared to team averages. The ACL case also displayed significantly lower PHF (−16.89°) and higher DF (+1.85°).
Conclusions: Several plausible strength and flexibility deficits were identified that could have played a role in the ACL case's injury.
Clinical Significance: The methods and instrumentation used to identify deficits in the ACL case were inexpensive and clinic-friendly.

Keywords: Anterior cruciate ligament, football, handheld dynamometer, injury


How to cite this article:
Johnson CD, Faherty MS, Varnell MS, Lovalekar M, Williams VJ, Csonka J, Salesi K, Sell TC. An analysis of musculoskeletal variables, comparative to team norms, leading to an anterior cruciate ligament rupture in a female soccer player. Duke Orthop J 2019;9:6-14

How to cite this URL:
Johnson CD, Faherty MS, Varnell MS, Lovalekar M, Williams VJ, Csonka J, Salesi K, Sell TC. An analysis of musculoskeletal variables, comparative to team norms, leading to an anterior cruciate ligament rupture in a female soccer player. Duke Orthop J [serial online] 2019 [cited 2020 May 29];9:6-14. Available from: http://www.dukeorthojournal.com/text.asp?2019/9/1/6/279429




  Introduction Top


The identification of mechanisms and predictors of injury specific to an athletic population is a vital, preceding step to the development of injury prevention programs.[1],[2] The volume of injury prevention research focused on noncontact ACL injury in females has grown exponentially in the past two decades due to the elevated prevalence of ACL injury in females. This elevated prevalence is a result of an estimated 4–6 times greater incidence rate when compared to male athletes and 5–10 times increase in high school and collegiate sport participation by females over the past 30 years.[3] Second, a noncontact mechanism of injury accounts for the vast majority (70%–72%) of all ACL injuries, which points to the possibility that modifiable intrinsic factors may predict the risk of injury.[4],[5] Finally, ACL injuries carry a multifactorial burden for affected athletes, including (1) costly/invasive surgery, (2) costly/lengthy rehabilitation, (3) losses in performance even after rehabilitation, (4) high risk for reinjury, (5) severe psychosocial effects and deficits on academic performance, and (6) high risk for the development of osteoarthritis.[3],[6],[7],[8],[9],[10]

In preventing and/or rehabilitating any injury, programs targeting prospectively identified, injury-specific, and modifiable risk factors are paramount. Limited hip rotation, synthetic playing surfaces in American football, and different aspects of the knee joint's bony structures have been retrospectively identified.[11],[12],[13],[14] Further, lower-extremity strength and flexibility have also been proposed as contributing factors for ACL injuries.[3],[15],[16],[17] However, the only modifiable variable that has been shown to prospectively predict first-time, noncontact ACL injury in athletes is excessive knee valgus angle during a landing task.[18] Researchers have also hypothesized that these risk factors most likely differ by population differences (age, sport, and team). One example of this is the presence of body mass index (BMI) as a prospective risk factor for noncontact ACL injury in female military cadets, but absent in the female athletic population.[19] The number of collegiate schools sponsoring female soccer teams has grown over 300% since 1988, and internal derangement of the knee is the second most common injury for this population.[20] Despite the apparent need, no studies have prospectively identified risk factors for noncontact ACL injury in this population.

The difficulty in identifying predisposing risk factors for any musculoskeletal injury (but especially for one with a low relative incidence) lies in the need for large sample sizes, long-term follow-ups, and an overall high cost by nature. An alternative to this, and one that offers the advantage of also being specific to sport, age and team status, are studies that utilize samples of a single athletic team.[21] Numerous case studies related to injury prevention or rehabilitation have been published utilizing small or single-case sample sizes.[21] In the absence of studies with large samples, these case studies are a viable option for clinicians and can be designed to utilize objective measures to track their respective athletes or team. A review of previous injury prevention, physiotherapy case studies by Sousa et al.[21] revealed that the most common topic was ACL injury in soccer players. However, the majority of the case studies were retrospective in nature, using same-subject or historical controls, and qualitative analyses with poorly defined methods.[21] Case studies utilizing a prospective design and quantitative data would provide stronger and more actionable information for clinicians treating ACL injuries.

The purpose of the data collection described in this study was to establish a team- and sport-specific database of modifiable risk factors leading to lower-extremity injury for a collegiate women's soccer team. We chose to focus on strength and flexibility, based on their supported role in ACL injury and the relative ease with which these variables can be collected in the clinic. The purpose of this study is to (a) describe the methods by which clinician-friendly, reliable measures were collected for players, in the field and with minimal equipment; (b) describe the process by which players were tracked throughout the season for injury; and (c) describe the process by which a player suffering a noncontact ACL rupture during the season was compared to team averages for modifiable, team-specific variables that may have predisposed them to injury. We hypothesized that the ACL case would display significant strength and flexibility deficits compared to the rest of her uninjured teammates. If these hypotheses hold true, these data will show the significance of screening for potential musculoskeletal risk factors that can be modified to improve an athlete's injury risk profile.


  Materials and Methods Top


Participants

Individuals (aged 18–35 years) were recruited from a Division I, female soccer team. All individuals were screened for inclusion/exclusion based on the following criteria: (1) currently active on team roster, (2) currently cleared by medical personnel for full participation in practice/competition, and (3) no lower extremity injury in the 4 weeks before the respective testing session. Twenty-two individuals met the criteria for inclusion and were available for preseason testing (age [years] =19.3 ± 1.2, height [cm] =168.06 ± 6.74, weight [kg] =61.93 ± 6.63, and BMI [kg/m2] =21.99 ± 1.64). All study procedures were approved by the University Institutional Review Board, and informed consent was obtained from each individual before the collection of any data.

Instrumentation

Anthropometrics

A wall-mounted stadiometer (Seca, Hanover, MD) and an electronic scale (Life Measurement Instruments, Concord, CA) were used to measure height and body weight, respectively.

Handheld dynamometer

A handheld dynamometer (HHD) (Lafayette Instrument Co., Lafayette, IN) was used to assess isometric muscle force. According to the manufacturer's data, the device was calibrated to a sensitivity of 0.1% and a range of 0–500 N. Therefore, peak force was measured for all strength variables to the nearest 0.1 N. HHD has been shown to be valid in measuring isometric strength for all lower-extremity muscle groups assessed when compared to isokinetic dynamometry.[22]

Goniometer/inclinometer

A universal goniometer (Aircast, Summit, NJ) and a handheld inclinometer (Saunders Digital Inclinometer, Chaska, MN) were used to assess flexibility. All measures were taken to the nearest 1°. Handheld inclinometers and goniometers have shown good construct validity in a prior research.[23]

Procedures

Individuals were first informed of all study procedures, and informed consent was obtained, followed by injury history questionnaires, height and weight measurement, flexibility assessments, and strength assessments. All testing was completed on the same day, at the team's athletic training facility, and occurring 2-months or less before the start of the collegiate soccer season.

Injury assessment/tracking

Injury history was obtained via self-report before testing and all reported injuries were verified by a certified athletic trainer (ATC). Injuries were tracked throughout each competitive season by review of medical records maintained by the team's athletic training staff. An ATC and/or certified physical therapist reviewed all medical records for any musculoskeletal injury sustained during the competitive season. All injuries were classified by type, location, stage (acute/overuse), and time-lost.

Flexibility

Flexibility testing included active ankle dorsiflexion (DF), weight-bearing ankle dorsiflexion mobility (wDM), and hamstring flexibility measured with passive hip flexion (PHF) and active knee extension (AKE). All testing procedures followed previously established protocols and have shown good-to-excellent interrater reliability in previous studies (Intraclass correlation coefficients = 0.76–0.99).[24],[25],[26],[27],[28],[29],[30],[31],[32] Three measurements were taken for each test and averaged for data analysis.

Active ankle DF was assessed in a prone position, with straight knees and feet hanging off the end of a treatment table. With the researcher stabilizing the subtalar joint, the case was asked to dorsiflex their foot as far as possible. A goniometer was used to measure the angle formed by the lateral midline of the leg, on a line from the head of the fibula to the tip of the lateral malleolus, and the lateral midline of the foot, in line with the border of the calcaneus.

wDM was assessed using the weight-bearing lunge test. In bare feet, cases started facing a wall in a lunge position with their bodyweight supported by outstretched arms on the wall and an extended back leg. The case attempts to keep their front foot flat, while simultaneously flexing their ankle and knee forward to touch their knee to the wall. The case was then asked to gradually move the front foot further from the wall until they could no longer touch their front knee to the wall when keeping their foot flat. DF mobility was measured as the distance (cm) from the wall to the tip of the first toe.

Active hamstring flexibility was assessed with an AKE test. Cases began in a supine position on a treatment table, with one leg straight and the leg being tested flexed at 90°. The thigh of the flexed leg was stabilized by a researcher to prevent hip motion, and the case was asked to straighten (extend) his/her leg a much as possible. A digital inclinometer was aligned with the lateral midline of the fibula between the lateral epicondyle of the femur and the lateral malleolus to measure the degree of knee extension deficit from a vertical plum line.

Passive hamstring flexibility was assessed with a straight leg raise test. Cases laid in a supine position on a treatment table with both legs extended fully. Cases were instructed to relax their leg while the researcher passively raised their leg to its end range of motion, making sure to avoid posterior pelvic tilt, changes in lumbar curve, and the opposite leg raising off the table. A digital inclinometer was aligned with the lateral midline of the femur between the greater trochanter and the lateral epicondyle of the femur to measure the degree of PHF.

Strength

Isometric muscle strength was assessed for ankle dorsiflexion (ADS), ankle inversion/eversion (AIS/AES), knee flexion/extension (KFS/KES), hip abduction/adduction (HADS/HABS), and hip internal/external rotation (HIS/HES). Procedures for all strength assessments were done with a HHD and followed previously established protocols, with good-to-excellent inter/intrarater reliability (ICCs = 0.73–0.98).[24],[25],[33],[34],[35],[36],[37] Further, all assessments of strength have shown good-to-excellent interrater reliability in previous pilot testing at our laboratory (ICCs = 0.60–0.99).

For all measurements, a practice trial at 50% effort was given and then three trials at 100% effort were collected for each movement and averaged for data analysis. Practice trials were allowed for a warm-up before maximal exertion as well as familiarity for both the case and researcher. Rest between trials was achieved by alternating limbs and movement (i.e., alternating between inversion on the left leg and eversion on the right leg). Before all trials, the limb being tested was passively moved into a neutral position for the given movement by the researcher. During trials, cases were asked to push against a nonmoving force provided by the researcher (“make tests”). The goal of the researchers administering the test was to match their applied resistance with the HHD to the force being exerted by the case. In this effort, cases were asked to incrementally “ramp” into each movement, gradually building to a maximal contraction. A second researcher was utilized to stabilize the case during assessment, in an effort to prevent utilization of secondary movers. Positioning of cases, placement site for HHD, stabilization, and testing reliability (intraclass correlation coefficients and minimum detectable change) are summarized in [Table 1].
Table 1: Summary of handheld dynamometer procedures

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Data reduction

Strength measures were normalized to body weight (kg of force/kg of body weight) and used to calculate strength ratios between opposing muscles groups for dominant and nondominant legs, including knee flexion/extension (FE-R), hip abduction/adduction (AB/AD-R), and hip external/internal rotation (ER/IR-R).

Statistical analysis

Statistical analysis was carried out with IBM SPSS Statistics version 21 (IBM Corp., Armonk, NY, USA). All strength and flexibility variables for the dominant limbs of the uninjured players were assessed for normality. For normally distributed variables, one-sample t-tests were used to assess differences between the ACL case's strength and flexibility in her dominant limb (injured limb) and the means for those variables in the uninjured cases' dominant limbs. For nonnormally distributed variables, Wilcoxon signed-rank tests were used. Statistical significance was set a priori at < 0.05.


  Results Top


The ACL case suffered an ACL rupture to her dominant leg in the second half of a game. The mechanism of injury was noncontact in nature and involved a planting and cutting motion. The injured knee was first examined and diagnosed by an athletic trainer and team physician and then confirmed by magnetic resonance imaging. The injury was a first-time, noncontact ACL rupture and resulted in 3 months removal from activity. After the injury was confirmed and relayed to the study's researchers, the case's injury history was checked, revealing a prior knee sprain to the injured knee. This sprain occurred 20 weeks before the ACL rupture and resulted in a minimal loss of playing time. The type of sprain is unknown, as the injury was never formally assessed. The ACL case was not experiencing any symptoms related to the prior injury at baseline testing. The remaining players were used as the uninjured, “control” group. However, all but one of the players had at least one previous lower extremity injury, as is typical in competitive athletes.

Descriptive data for the uninjured teammates and ACL case, as well as P values from the resulting statistical tests, are reported in [Table 2]. All test statistics and P values reported are for one sample t-tests excluding the HL-HE variable (Wilcoxon signed-rank test). The ACL case demonstrated significantly higher DF (10.50° vs. 8.65°) and significantly lower PHF (60.00° vs. 76.89°). In relation to strength, the ACL case demonstrated significantly lower ADS (20.17% vs. 28.01%), AIS (16.77% v.s 24.18%), AES (17.30% vs. 23.88%), KFS (25.70% vs. 32.09%), HABS (14.27% vs. 17.41%), and HES (11.13% vs. 13.97%). Finally, the ACL case demonstrated a significantly lower Hip AB/AD-R (0.89 vs. 1.01).
Table 2: Results of one sample t tests comparing the anterior cruciate ligament case to team means

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  Discussion Top


The main purpose of this case study was to provide a description of the methods used to prospectively assess and monitor an athletic team for potential, modifiable risk factors for musculoskeletal injuries specific to their team, sport, and gender. We had hypothesized that the ACL case would display significant strength and flexibility deficits, possibly predisposing her to the ruptured ACL that she suffered. ACL injuries carry a significant burden for both the affected athletes and the clinicians treating them; however little is understood about the modifiable risk factors for these injuries specific to sport and gender.[3],[6],[7],[8],[9],[38],[39],[40],[41] The significance of this study lies in providing clinicians with some form of objective measurement with which to assess and track their respective teams/athletes, when data regarding risk factors for certain injuries are lacking. Although the statistical power of these findings may hold limitations, their clinical significance would seem to be very powerful, in that all the methods described are clinician-friendly and requiring little and relatively inexpensive equipment. Further, the results of this study show the significance of screening for potential musculoskeletal risk factors that can be modified to improve an athlete's injury risk profile, in this case, ACL rupture.

Mean values for isometric strength obtained in this study are similar to those reported in the previous literature, excluding HADS, HABS, and knee FE-R.[42],[43] Our mean values for HADS (17.76%) and HABS (17.41%) were significantly lower than those previously reported by Stoll et al.[42] (29.5% and 31.2%, respectively). Further, our mean knee FE-R (0.77) was slightly higher than that reported by the same authors (0.577).[42] The differences in HADS and HABS could be attributed to two methodological differences between the studies: (a) Stoll et al. utilized a nonelastic band and a pull-gauge where the current study utilized handheld dynamometry and (b) our procedures placed an emphasis on stabilizing accessory movement and this emphasis may not have been as great in the previous study. However, with the limited description of the author's procedures, these possibilities are hard to confirm. The significantly higher knee FE-R could possibly be explained by the different populations utilized in each study, collegiate soccer players compared to “healthy adults.” It is likely that collegiate soccer players focus more on training their knee flexors compared to the extensors than a normal “healthy adult,” given the performance demands of their sport.

Mean values for flexibility obtained for this study are similar to those reported in previous literature, excluding AKE and wDM.[24],[26],[44],[45],[46],[47] Mean values for wDM (8.37 cm) are similar to those reported by O'Shea and Grafton[44] (9.3 cm), but lower than those reported by Bennell et al.[26] (13.8 cm) and Hoch et al.[45] (11.9 cm). These mixed associations could possibly be attributed to the mixed-gender samples utilized by all three previous studies, where the current study only included females. Further, none of the previous three studies utilized samples only including athletes. Mean values for AKE (16.35°) are significantly lower than those reported by Hamid et al.[46] (22.8°) and Schulze et al.[47] (27.1°). While these two previous studies did report mean values for only females, the differences in AKE could, again, be attributed to a different sample, healthy adults compared to collegiate athletes. This theory becomes more likely based on the results of the study by Schulze et al.,[47] revealing that the covariate “Years of Participation in Physical Activity” had a significant, negative impact on AKE.

The ACL case demonstrated significantly lower ankle strength values compared to her teammates, including ADS, AIS, and AES. Previous research linking ankle strength to first-time ACL injury is lacking. A risk factor for noncontact ACL injury that has been proposed in previous research, and that may provide an indirect link to ankle strength, is excessive foot pronation.[3],[48],[49] The assertion could be made that greater ankle strength helps limit excessive foot pronation during soccer play. However, the link between foot pronation and noncontact ACL injury has shown conflicting results when assessed retrospectively and negative results when assessed prospectively.[3],[48],[50] Individuals with chronic/functional ankle instability show altered knee kinematics and kinetics during functional landing tasks, indicative of higher ACL injury risk.[51],[52],[53],[54] This provides another possible, indirect link to the case's ACL injury, with ankle strength deficits being a primary causative factor in chronic/functional ankle instability.[55],[56],[57]

The ACL case also demonstrated significantly lower KFS, HABS, HES, and AB/AD-R. While all these differences (2.84%–6.39%) are also lower than the MDCs (5.1%–7.6%) calculated for each respective assessment, a body of research supports them as possible risk factors for noncontact ACL injury in female athletes. The hamstrings have been noted as an important muscle group for ACL stability, providing a counterbalance to the forward pull of the quadriceps and intrinsic/extrinsic anterior shear forces during dynamic exercise.[3] While much of the research has focused on the level and timing of activation of the hamstrings, a study by Myer et al. showed that female soccer and basketball players who suffered ACL injuries demonstrated significantly lower hamstring strength compared to matched, male controls, but similar quadriceps strength.[15]

With regard to HABS and HES, a study by Hewett et al.[18] found that peak knee abduction moment and knee valgus angles during landing significantly predicted noncontact ACL injury in a large cohort of female athletes. The hip abductors and external rotators are important muscles in controlling the position of the knee during dynamic movement, specifically in preventing the valgus, internally rotated position predisposing female athletes to ACL injury.[3] Although it has not been shown that HABS and HES significantly alter these landing variables independently, it has been shown that training of the hip musculature that increases isometric hip strength can result in concurrent improvements in these landing variables.[48],[58] This dichotomy makes it likely that neuromuscular recruitment and timely activation are significant mediators in how the hip musculature affects peak knee abduction moments and knee valgus angles during landing.[59],[60] Nonetheless, it would seem reasonable to assert that adequate HABS and HES would play a role as well.

The ACL case presented with significantly higher DF (1.85°) and significantly lower PHF (−16.89°). There is very limited research to support either of these variables having a role in the ACL case's injury, especially in the case of higher DF which has only been proposed as a potentially protective factor against noncontact ACL injury.[16],[17] In regard to lower PHF, it has been shown that limited knee and hip flexion at the initial contact of a landing activity predicts altered knee kinematics and kinetics.[61] The hamstring group spans both the knee and hip joints and limited flexibility of the muscle group could, theoretically, limit the amount of knee and hip flexion during dynamic maneuvers such as cutting and landing. However, there is no research to the author's knowledge that supports this claim and therefore definitive conclusions are impossible in relation to the current injury.

Finally, an examination of the ACL case's injury history revealed a previous injury to the affected knee. The case was diagnosed with an acute knee sprain, 20 months before her ACL rupture. The previous injury occurred during game play, as a result of direct contact with another player. It did not require surgery and only caused a minimal loss of playing time.


  Conclusions Top


The ACL case presented with significantly lower ankle, hamstring, and hip strength values, as well as several differences in flexibility, compared to the rest of her team mates. While each of these factors hold varying levels of evidence as potential causes for a noncontact ACL injury, it would seem prudent to discuss them as a whole. A deficit in ankle strength presents the likelihood of instability in the joint most distal to the knee. A deficit in hip abduction and external rotation strength presents the likelihood of a lack of control over knee position during dynamic movement and instability in the joint most-proximal to the knee. Finally, a deficit in hamstring strength presents the likelihood of a lack of posterior pull to stabilize the femur during activities causing higher anterior shear forces and limited hamstring flexibility may alter knee and hip flexion causing further dysfunction at the knee. The combination of these factors with the case's previous injury, while obviously having no empirical evidence to support it, presents the most likely basis for the ACL case's injury. Indeed, the overwhelming lack of empirical evidence to support most musculoskeletal characteristics as independent risk factors for noncontact ACL injury in female athletes makes it likely that a multitude of factors act together to predispose each athlete to this type of injury, as well as others.

Some limitations are present in the current study. First, we wish to acknowledge the obvious limitation of examining one row of data. The statistical analyses of the ACL case's variables compared to the team averages is in no way meant to establish these variables as risk factors for ACL injury or even as definitive causative factors in the ACL case's injury. Larger sample, prospective studies are needed to confirm risk factors for any injury. The purpose of our statistical analysis, and subsequent evaluation of the findings, was merely to provide an example on how clinicians can track and assess their athletes for potentially risky strength and flexibility deficits, using some type of objective criteria. Therefore, while we cannot say that the deficits observed in our case definitely resulted in an ACL rupture, a clinician would almost certainly recommend improving those deficits in an attempt to improve the athlete's overall injury risk profile.

Second, we acknowledge the low effect sizes of the statistical differences observed between the ACL case and team averages. All strength deficits were below the minimum detectable changes for each respective assessment, and the difference in DF was <2°. However, as was stated previously, we propose that it is the combination of the ACL case's strength and flexibility deficits that is the most likely culprit for her injury. Therefore, while these deficits may seem clinically irrelevant independent of each other, they are much more relevant as a whole.

Clinical significance

This study contains the methods by which collegiate athletes were tracked for modifiable musculoskeletal characteristics that had the potential to predict injury. Further, it provides the statistical methodology by which an athlete who suffered a noncontact ACL injury was assessed for potential causes specific to her injury. Finally, all the data collection described was done with inexpensive, clinician-friendly instrumentation. As stated previously, not all variables collected were supported by research on their role in ACL injuries for female soccer players; however, they all hold some association with lower-extremity injury risk. Therefore, the intention was not to investigate risk factors for all noncontact ACL injuries, but to provide these methodologies as a model for athletic trainers and physical therapists who wish to assess and track their athletes for potential and modifiable musculoskeletal deficits, that may inform and focus their injury prevention efforts.

Acknowledgments

We would like to acknowledge the following individuals for their contributions to the current study: Paul Whitehead, Nicholas Heebner, Matthew Darnell and Heather Bansbach.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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