ACL Clinical Prediction Tools and Prevention Programs for Females

Statistically speaking, females are at greater risk for rupturing their ACL than men playing the same sports. Why is this?

Anatomic Differences

• Pelvis width, Q-Angle,  size of the ACL, and size of the intercondylar notch (where the ACL crosses the knee joint)

Hormonal Differences

• The ACL has hormone receptors for estrogen and progesterone, and it has been thought that hormone concentration could play a role in ACL injuries. Studies have shown some differences in rates of ACL injury during different phases of the menstrual cycle. However, there has been some conflicting data, and the effect of hormone concentration on ACL injury risk has yet to be defined.

Biomechanic Differences

• Women have been found to have differences in biomechanic movements of the knee seen when pivoting, jumping, and landing — activities that often lead to an ACL injury.

The theories above are just that – theories. Unfortunately no one knows exactly what causes the increased risk of ACL tears in females. More investigation is constantly taking place to better answer this question. The below trial took place in the Cincinnati Children’s Hospital Medical Center, and investigated a tool to help identify female athletes at risk for ACL injury.

BACKGROUND: Prospective measures of high knee abduction moment (KAM) during landing identify female athletes at high risk for anterior cruciate ligament injury. Laboratory-based measurements demonstrate 90% accuracy in prediction of high KAM. Clinic-based prediction algorithms that employ correlates derived from laboratory-based measurements also demonstrate high accuracy for prediction of high KAM mechanics during landing.

HYPOTHESES: Clinic-based measures derived from highly predictive laboratory-based models are valid for the accurate prediction of high KAM status, and simultaneous measurements using laboratory-based and clinic-based techniques highly correlate. Study Design Cohort study (diagnosis); Level of evidence, 2.

METHODS: One hundred female athletes (basketball, soccer, volleyball players) were tested using laboratory-based measures to confirm the validity of identified laboratory-based correlate variables to clinic-based measures included in a prediction algorithm to determine high KAM status. To analyze selected clinic-based surrogate predictors, another cohort of 20 female athletes was simultaneously tested with both clinic-based and laboratory-based measures.

RESULTS: The prediction model (odds ratio: 95% confidence interval), derived from laboratory-based surrogates including (1) knee valgus motion (1.59: 1.17-2.16 cm), (2) knee flexion range of motion (0.94: 0.89 degrees -1.00 degrees ), (3) body mass (0.98: 0.94-1.03 kg), (4) tibia length (1.55: 1.20-2.07 cm), and (5) quadriceps-to-hamstrings ratio (1.70: 0.48%-6.0%), predicted high KAM status with 84% sensitivity and 67% specificity (P < .001). Clinic-based techniques that used a calibrated physician’s scale, a standard measuring tape, standard camcorder, ImageJ software, and an isokinetic dynamometer showed high correlation (knee valgus motion, r = .87; knee flexion range of motion, r = .95; and tibia length, r = .98) to simultaneous laboratory-based measurements. Body mass and quadriceps-to-hamstrings ratio were included in both methodologies and therefore had r values of 1.0.

CONCLUSION: Clinically obtainable measures of increased knee valgus, knee flexion range of motion, body mass, tibia length, and quadriceps-to-hamstrings ratio predict high KAM status in female athletes with high sensitivity and specificity. Female athletes who demonstrate high KAM landing mechanics are at increased risk for anterior cruciate ligament injury and are more likely to benefit from neuromuscular training targeted to this risk factor. Use of the developed clinic-based assessment tool may facilitate high-risk athletes’ entry into appropriate interventions that will have greater potential to reduce their injury risk.

This study is of great importance with regard to predicting at risk females who participate in jumping sports. The question is, so what do we do about it now?

There has been some evidence to suggest that ACL Prevention Programs, such as this one can be beneficial in preventing injury in at-risk females.

Renstrom et al (2008) in the BMJ provided a current concepts statement regarding such programs. The authors noted:

“These programmes attempt to alter dynamic loading of the tibiofemoral joint through neuromuscular and proprioceptive training. They emphasise proper landing and cutting techniques. This includes landing softly on the forefoot and rolling back to the rearfoot, engaging knee and hip flexion and, where possible, landing on two feet. Players are trained to avoid excessive dynamic valgus of the knee and to focus on the “knee over toe position” when cutting.”

At risk players can also be identified using the drop vertical jump test by Noyes et al (2005).

Does your practice perform such prevention programs?

References

Myer GD, Ford KR, Khoury J, Succop P, Hewett TE. Development and Validation of a Clinic-Based Prediction Tool to Identify Female Athletes at High Risk for Anterior Cruciate Ligament Injury. Am J Sports Med. Jul 1 2010.

Renstrom P, Ljungqvist A, Arendt E, et al. Non-contact ACL injuries in female athletes: an International Olympic Committee current concepts Statement. Br J Sports Med. 2008;42 (6):394-412.

Noyes F, Barber-Westin F, Fleckenstein C, et al.  The Drop-Jump Screening Test

Difference in Lower Limb Control By Gender and Effect of Neuromuscular Training in Female Athletes. The American Journal of Sports Medicine. 2005; 33(2): 197-207.

Griffin Y,Agel J, Albohm M, et al. Noncontact Anterior Cruciate Ligament Injuries: Risk Factors and Prevention Strategies. J Am Acad Orthop Surg. 2000; 8(3): 141-150.