Injury Prediction / Prevention

Functional Movement Screen Injury Prediction

Lisman P, O’Connor FG, Deuster PA, Knapik JJ. Functional movement screen and aerobic fitness predict injuries in military training. Med Sci Sports Exerc. 2013 Apr;45(4):636-43.

“Combining slow RT and low FMS scores (≤14) increased the predictive value across all injury classifications: candidates scoring poorly on both tests were 4.2 times more likely to experience an injury.”

Take Home: Injury risk is multifactorial. Using aerobic fitness combined with fundamental movement competency as measured by the Functional Movement Screen proved to be a powerful predictor of injury in Marine Corps officer candidates. Demonstrates the need for using multiple tests and categorizing the subjects into risk levels  (Lehr et al 2013).

Various Occupations.

Butler RJ, Contreras M, Burton LC, Plisky PJ, Goode A, Kiesel K. Modifiable risk factors predict injuries in firefighters during training academies. Work. 2013

ROC curve analysis established that a FMS cut score of ≤14 was able to discriminate between those at a greater risk for injury. In addition, the deep squat and push up component of the FMS were statistically significant predictors of injury status along with the sit and reach test.”

Take Home: In a different population than previously studied (firefighters rather than athlete or military) the Functional Movement Screen was found predictive of injury. This may demonstrate that fundamental movement patterns are important regardless of activity type.

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O’Connor FG, Deuster PA, Davis J, Pappas CG, Knapik JJ. Functional movement screening: predicting injuries in officer candidates. Med Sci Sports Exerc. 2011 Dec;43(12):2224-30.

“Both Long Cycle and Short Cycle cohorts demonstrated higher injury risk among candidates who had scores ≤14 compared with those with scores >14 (LC: risk ratio (RR) = 1.65, 95% confidence interval = 1.05-2.59, P = 0.03; SC: RR = 1.91, 95% confidence interval = 1.21-3.01, P < 0.01). Overall, 79.8% of persons with scores ≤14 were in the group with fitness scores <280 (/300), whereas only 6.6% of candidates in the group with fitness scores ≥280 had scores ≤14.”

Take Home: Functional Movement Screen score is associated with injury risk in Marine officer candidates regardless of the length of the basic training session.

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Kiesel K, Plisky PJ, Voight ML. Can Serious Injury in Professional Football be Predicted by a Preseason Functional Movement Screen? N Am J Sports Phys Ther. 2007 Aug;2(3):147-58.

“The results of this study suggest fundamental movement (as measured by the FMS™) is an identifiable risk factor for injury in professional football players. The findings of this study suggest professional football players with dysfunctional fundamental movement patterns as measured by the FMS(™) are more likely to suffer an injury than those scoring higher on the FMS™.”

Take Home: Performance on a basic test of fundamental movement patterns is helpful in predicting injuries in professional football players.

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Chorba RS, Chorba DJ, Bouillon LE, Overmyer CA, Landis  JA. Use of functional movement screening tool to determine injury risk in female collegiate athletes. N Am J Sports  Phys Ther. 2010;5:47-54.

“A score of 14 or less on the FMS™ tool resulted in a 4-fold increase in risk of lower extremity injury in female collegiate athletes participating in fall and winter sports. The screening tool was able to predict injury in female athletes without a history of major musculoskeletal injury such as ACLR.”

Take Home: It is interesting to note that athletes with history ACL reconstruction were included in the study. This may indicate that the Functional Movement Screen may be able to pick up some of the motor control changes that occur after injury that place athletes at increased risk.

Group Injury Prevention Programs

Myklebust G, Skjølberg A, Bahr R. ACL injury incidence in female handball 10 years after the Norwegian ACL prevention study: important lessons learned. Br J Sports Med. 2013 May;47(8):476-9

After implementing ACL prevention programs in handball teams for over 10 years, the authors sought to answer the question of what made the injury prevention programs successful. They came to 3 main conclusions for successful programs:

  1. “must have coach as a “partner” in the process.”
  2. The prevention program was efficient
  3. The message “we delivered to coaches in seminars, through pamphlets, interviews and on our website, was no longer ‘may reduce injury risk’, but ‘will reduce injury risk by at least 50%’. This ‘specific’ information meets one of the Heath Brothers’ criteria for ‘sticky’ messages—messages that have influence.”

Finally, the authors concluded:

“Risk factor studies are necessary to identify the individual’s needs for special training and optimise the selection of preventive exercises. In the meantime, we suggest that team sports include prevention exercises in their warm-up, tailor the exercise  programme to the specific sport and focus on coach education as a key factor”

 

Injury Prediction Using Injury Risk Algorithm & Risk Categories

Lehr ME, Plisky PJ, Kiesel KB, Butler RJ, Fink M, Underwood FB. Field Expedient Screening and Injury Risk Algorithm Categories as Predictors of Non-Contact Lower Extremity Injury. Scan J Med Sci Sport. 2013

“Athletes identified as High Risk (n = 63) were at a greater risk of noncontact LE injury (27/63) during the season [RR: 3.4 95% confidence interval 2.0 to 6.0]. These results suggest that an injury prediction algorithm composed of performance on efficient, low-cost, field-ready tests can help identify individuals at elevated risk of noncontact LE injury.”

TAKE HOME: By utilizing efficient, easy to administer (history, Functional Movement Screen, Y Balance Test) athletes at greatest risk of injury can be identifited and injury prevention resources can be allocated to those at greatest risk of injury.

Strength and Flexibility Asymmetries as Risk Factors for Injury

  • Athletes experienced more lower extremity injuries if they had knee flexor and hip extensor strength asymmetries (Knapick 1991Nadler 2001)
  • Eccentric hamstring strength asymmetries were at greater risk of sustaining a hamstring muscle strain. (Fousekis 2011)
  • Hamstring/quad ratio asymmetry (Soderman 2001)
  • Ankle strength asymmetry (Baumhauer 1995)
  • Asymmetrical landing patterns predict second ACL tear in previously reconstructed athletes (Paterno 2010)

Why are there Age, Gender, Sport/Activity specific norms and risk cut points for the Y Balance Test?

I spend a lot of time discussing that the Functional Movement Screen (FMS) and Selective Functional Movement Assessment (SFMA) are not intended to be sport specific or even “Functional” measures. The FMS and SFMA are used to determine if a person has the underlying movement competency to serve as the foundation for his or her activity.
So why are there age, gender, and sport/activity specific norms and risk cut points for the Y Balance Test? Isn’t that a contradiction?

When it comes to higher level testing (such as dynamic balance), there can be an activity specific balance adaptation that occurs. To see how this plays out as different norms and injury risk cut points, check out this short video

Y Balance Test Injury Prediction

Plisky PJ, Rauh MJ, Kaminski TW, Underwood, FB. Star Excursion Balance Test predicts lower extremity injury in high school basketball players. J Orthop Sports Phys Ther. 2006;36(12):911-9

  • “players with an anterior right/left reach distance difference greater than 4 cm were 2.5 times more likely to sustain a lower extremity injury (P<.05). Girls with a composite reach distance less than 94.0% of their limb length were 6.5 times more likely to have a lower extremity injury (P<.05).”
  • TAKE HOME MESSAGE: This was the first study demonstrating the Star Excursion Balance Test’s predictive ability. If you athletes have an asymmetry or low composite score, they may be at great risk of injury. Thus, one should consider using the SEBT for return to sport testing and in the pre-participation physical.

Star Excursion & Y Balance Test Lower Quarter Systematic Review

Gribble PA, Hertel J, Plisky PJ. Using the Star Excursion Balance Test to Assess Dynamic Postural Control Deficits and Outcomes in Lower Extremity Injury – A Literature and Systematic Review. J Athl Train. 2012;47(3):339-57.

  • “The Star Excursion Balance Test is a reliable measure and a valid dynamic test to predict risk of lower extremity injury, to identify dynamic balance deficits in patients with lower extremity conditions, and to be responsive to training programs in healthy participants and those with lower extremity conditions.”
  • TAKE HOME MESSAGE: The Star Excursion & Y Balance Test should be used for return to sport testing, pre-participation physicals, and annual musculoskeletal exams.
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Phil Plisky

I want to change peoples lives through dialogue about injury prevention research and return to activity testing.

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