What is the Subsequent Rate of Surgery and Predictors After Previous ACL Reconstruction?

In the July issue of the American Journal of Sports Medicine, there was a great research study published called The Rate of Subsequent Surgery and Predictors After Anterior Cruciate Ligament Reconstruction.  In this particular study, the authors were looking at the rate of all subsequent knee surgeries following a primary ACL reconstruction (ACLR) at 2 and 6 years post initial surgery.  In studies of this nature, they do a retrospective analysis of data provided by a MOON (Multicenter Orthopedic Outcome Network) group.  In simplistic terms, this is a group of orthopedic centers that are reporting their data for these types of studies in order to provide a N value (number of subjects) that allows for conclusions to be made based on statistically significant data. 

Previous MOON group studies have provided some great data related to ACL injuries.  Recently published results of a multi-site study indicated that 20% of females who have an ACLR will have a second one within 3 years.  In a 12 year follow up study published in 2012, investigators found that 79% of those who had an ACLR had osteoarthritis on the involved side.  So this study looking to see what is the rate and predictors of all subsequent surgeries at short term and midterm follow-up.  Using this information, can we identify those more at risk for subsequent injury? 

In the US alone, there are well over 200,000 ACLR annually.  The cost associated with this initial injury is astronomical, over $5B.  That being said, 5.8% will re-rupture their ipsilateral ACL and 11.8% will rupture their contralateral ACL within 5 years of the initial injury.  Predictors and causative factors for this re-rupture are not known.  Yet, the rupture of the ACL is not the only knee injury that these patients are more susceptible to.  Knowing what other injuries occur, the rates of these injuries along with predictors for these may provide us with the knowledge to prevent life altering pathology and aid in reducing those who suffer OA later down the line.

In this study, 980 patients were prospectively enrolled in a MOON cohort from Jan. 2002 to Dec. 2003.  The 2 and 6 year follow-up information for all subsequent procedures was obtained, operative reports reviewed and procedures categorized.  What was found was that 185 underwent subsequent surgery on the ipsilateral leg (18.9%) and 100 on the contralateral knee (10.2%) at the 6 year follow-up.  On the ipsilateral limb, 13.3% had cartilage procedures, 7.7% ACL revision and 5.4% arthrofibrosis.  For the contralateral limb there was a 6.4% rate of primary ACL ruptures. 

Based on this, authors concluded that ipsilateral vs. contralateral ACL tears occurred at similar rates (7.7% and 6.4% respectively) at 6 year follow-up following a primary ACLR.  They also concluded that 18.9% of patients underwent subsequent surgeries on the ipsilateral knee 6 years after a primary ACLR.  The only 2 risk factors that were identified in this study were age and use of allografts.  So the younger someone suffered a primary ACLR and if an allograph was used, they were at a higher risk.

So, what does this mean and what is the take home for us.  First, is that when making the decision on whether or not to have an allograph, hamstrings graft or patellar tendon graph, at least according to this study, if you choose an allograph you are more likely to have subsequent surgeries down the line.  Second and more profoundly, is that if you have an ACLR earlier in life, you are more likely to have subsequent surgeries and OA down the line.  That said it again highlights why prevention of these injuries is the key.

This study, as well as others highlights the importance of being able to identify those at risk.  One major flaw in studies of this nature is that we evaluate demographic (age/gender) and physiological information (weight, graph type) related to the patient and attempt to deduct risk factors based on.  Yet, these types of injuries and subsequent injuries are “movement” related injuries.  Yet, movement is the one thing we don’t look at as a causative factor.  No matter how good the surgery is or the age of the athlete, if they move like the athlete above, anyone can see she is at higher risk for re-injury.

What can we do today to impact the lives of our athlete’s tomorrow?

About the author:  Trent Nessler, PT, DPT, MPT.  Trent is a practicing physical therapist with 14 years in sports medicine and orthopedics.  He has a bachelors in exercise physiology, masters in physical therapy and doctorate in physical therapy with focus in biomechanics and motor learning.  He author of a textbook “Dynamic Movement Assessment™: Prevent Injury and Enhance Performance”, is associate editor of the International Journal of Athletic Therapy and Training, Member of the USA Cheer Safety Council and founder/developer of the Dynamic Movement Assessment™.

Reference:

Hettrich C, Dunn W, Reinke E, Spindler K.  The rate of Subsequent Surgery and Predictors After Anterior Cruciate Ligament Reconstruction.  Am J Sports Med.  41:1534-1540. 2013.

Holm, I; Oiestad, B; Risberg, M; Gunderson, R; Aune, A.  No Difference in Prevalence of Osteoarthritis or Function After Open Versus Endoscopic Technique for Anterior Cruciate Ligament Reconstruction: 12 Year Follow-up Report of Randomized Controlled Trial.  Am j sports med.  2012; 40:2492-2498.

McCullough, K; Phelps, K; Spindler, K; Matava, M; Dunn, W; Parker, R; Reinke, E.  Return to High School – and College-Level Football After Anterior Cruciate Ligament Reconstruction: A Multicenter Orthopaedic Outcomes Network (MOON) Cohort Study.  Am j sports med.  2012; 40:2523-2529.

Predicting Hamstring Injuries in Collegiate and Professional Football Players

In the July issue of the American Journal of Sports Medicine, there was a great research study published called Isokinetic Concentric Quadriceps and Hamstring Strength Variables From NFL Scouting Combine Are Not Predictive of Hamstring Injury in First – Year Professional Football Players.  This study begins to address the question of whether or not the methodology we currently use in pre-participation physicals is truly assessing or providing us with the information we are seeking.  Questions like this have plagued those of us that work in the sports medicine realm for years.  How do you predict something that has never occurred?  Is the current methodology we use in pre-participation physicals truly predicative of athletic injury? 

Whether your sport is football, soccer, basketball or baseball, hamstring injuries are common place amongst all the sports.  There are many causative factors for these but we know that once one does occur, the likelihood of re-injury is high.  In football, since most of these occur during pre-season (78.9%) and over 70% occurring in the first month of practice, identifying those at risk is essential for player health, subsequent injuries and overall team performance.

Studies back in the late 90s and early 2000s suggested that a strength imbalance between the quadriceps and hamstrings is a predictive measure for risk of hamstring strains.  These studies suggest that a hamstring to quadriceps ratio [H/Q] of <.6 placed a player at higher risk for hamstring injury.  As such, it is an accepted standard of practice in the NFL combines, to obtain preseason Cybex isokinetic concentric strength tests for the quadriceps and hamstrings.  The purpose of this study was to do a retrospective analysis and see if this is a reliable and valid measure for hamstring injury risk. 

In this study, the authors worked with 32 NFL teams that identified players that were selected in the first 5 rounds of NFL draft who also had hamstring injuries during their first professional season.  Of these, 162 of those players with previous hamstring injuries also had Cybex data from their previous year’s combine.  They performed a retrospective analysis on the data in order to determine the sensitivity and specificity for the hamstring to quadriceps ratio, as determined by the Cybex isokinetic test, predicting hamstring injury. 

What the authors found was that the sensitivity and specificity for the hamstrings to quadriceps ratio predicting hamstring injury were .513 and .524.  From this the authors suggest there is no predictive relationship with H/Q ratios and risk for hamstring injury.  So, if this is a excepted standard of practice and it is not predictive, should we be looking at something else?  Most would say yes, but what?  That is the true question.  When looking at this test in particular, does it really test how the hamstrings function in a closed kinetic chain?  No.  Does it account for the co-contraction between the quadriceps and hamstrings that must occur during athletic activities?  No.  Does it test the mechanism of most hamstring injuries (eccentric in nature)?  No.  Based on the above, are we really surprised that this does not have a predictive value for hamstring injuries?  So how do we test?

Many believe that attempting to predict injury risk and prevent injuries should parallel tests sports performance.  The two are so closely correlated. Knowing the research behind movement assessment and it’s tie to injury prediction and prevention, would this give us a better “true and full” assessment of the athlete?  If those same mechanics that result in abnormal force attenuation along the kinetic chain were identified and improved, would this also result in improvement in force production?  Although the answer seems logical, it has yet to be proven in the research.

Albert Szent-Gyorgi, who won the Nobel Prize in 1937 for discovering vitamin C, once said “Discovery consists in seeing what everyone else has seen and thinking what no one else has thought.”

About the author:  Trent Nessler, PT, DPT, MPT.  Trent is a practicing physical therapist with 14 years in sports medicine and orthopedics.  He has a bachelors in exercise physiology, masters in physical therapy and doctorate in physical therapy with focus in biomechanics and motor learning.  He author of a textbook “Dynamic Movement Assessment™: Prevent Injury and Enhance Performance”, is associate editor of the International Journal of Athletic Therapy and Training, Member of the USA Cheer Safety Council and founder/developer of the Dynamic Movement Assessment™.

Reference:

Zvijac J, Toriscelli T, Merrick S, Kiebzak G.  Isokinetic Concentric Quadriceps and Hamstring Strength Variables From NFL Scouting Combine Are Not Predictive of Hamstring Injury in First – Year Professional Football Players.  Am J Sports Med.  41:1511-1518. 2013.

Using The Dynamic Movement Assessment ™ to Prevent Injuries and Improve Performance With Division 1 Soccer - Part II

Last week we presented the first part of a business case using the Dynamic Movement Assessment™ in D1 Soccer.  This article, we will review the methods and both the impact on injuries as well as financial cost to the university.

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Methods:

Subject pool consisted of female soccer players playing at the Division 1 level.  There were 102 female sophomore, junior and senior soccer players ranging in age from 18-24 years old.  Average years of play for all the athletes was 6.5 years.  Average number of seasonal non-contact ACL injuries for the intervention group ranged from 2-4 per season for the last 8 seasons.  As part of the standard procedure, each student athlete was put through an annual pre-participation physical and orthopedic examination by the team physician.  Consent to participate in the DMA™ was received from each athlete.  Each athlete then participated in a DMA™ and Fatigue DMA™.  The DMA™ and Fatigue DMA™ consisted of 6 essential movements which were filmed and scored using Dartfish™ video technology.  The DMA™ consisted of:

·         8 min warm-up on bike

·         Performing the DMA™

Three days after performing the DMA™ participants then performed the Fatigue DMA™.  The Fatigue DMA™ consisted of:

·         8 min warm-up on bike

·         Performing the Functional Agility Short Term Fatigue Protocol (FAST-FP)

·         Performing the DMA™

Results:

Analysis of the initial data in comparison of the DMA™ with the Fatigue DMA™, showed the following trends:

·         N = 102

 

·         Average perceived rating of exertion for the DMA™ was:

• Range of 5-7/10
• Average 6/10

·         Average perceived rating of exertion for the Fatigue DMA™ was:

• Range 7-9/10
• Average 8/10

·         Rating players pre fatigue resulted in:

• 25% of athletes categorized at risk
• 2% of athletes categorized high risk

·         Rating players post fatigue resulted in:

• 5% of athletes categorized at risk
• 36% of athletes categorized high risk

 Of the athlete’s tested, 48 were provided with an intervention over a 2 year period.  The results were as follows: 

·         N = 48

·         Injuries:

• 100% reduction of non-contact ACL injuries over 2 years – prior 8 seasons averaged 2-4 ACLs per season
• 58.2% reduction non-contact musculoskeletal injuries in comparison to prior 8 seasons

·         Performance impact

• 2 best seasonal performances in comparison to the last 5 years. 
• Coaches and ATCs correlate this to the ability to keep key players on the field and off the DL

·         $200K health care cost savings over 2 years with just one sport

• Savings related to both ACL injury and other non-contact musculoskeletal injury reduction
• If continue 1 more year with reductions will result in university having decrease in premiums for 1^st time in 10 years.

Although the rate of reduction is not statistically significant (prevented 4 of potential 8), the cost savings is.  As the study continues, the statistical significance will be more evident.

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Use of DMA™ and Impact on Injuries & Health Care Costs for Universities

Research indicates that identifying those with movement dysfunction or pathokinematics can have a dramatic impact on injury rates, individual performance and team performance.  The preliminary data collected in this current business case appears to support previous findings.  Although not statistically significant due to the low sample size and previous seasons ACL injuries, as time goes on, the investigators suspect the current trends will become more significant over time. 

However, there are no studies currently in the literature that look at the health care savings associated with these injury prevention initiatives.  With rising health care costs associated with injuries for the university, the athlete and primary policy holder, closer attention to the impact these initiatives can have on overall health care cost and future premiums paid by the university as well as policy holders will become more imperative.  With budgetary restraints and high costs associated with athletic programs and small profit margins, many universities and professional teams are looking at proactive measures to contain and control these costs.  Knowing that ACL injuries are one of the most costly lower extremity athletic injuries (average $25,000 to $50,000 per injury) and which have causative factors (pathokinematics) that also lead to other non-contact injuries, many teams are focusing efforts on initiatives that impact these specific injuries.  By doing this, the thought is that there will also be a downstream impact on reducing other non-contact lower extremity injuries.  The current business case highlights that.

In the current business case, in just 2 years, with one university and one sport (women’s soccer), the total health care savings for the intervention group was >$200K compared to previous years.  This reduced cost is associated with both the reduction in ACL injuries (MD visits, MR, surgery, rehabilitation, etc.) as well as a 58.2% reduction in other non-contact lower extremity injuries.  If expanded to other high risk sports (football, volleyball, basketball) the annual savings could be much greater.

With the cost of this assessment at $5000 per team or $10,000 over 2 seasons, the total ROI was a $190K in measurable cost savings to the university.  When considering the total ROI, one must also consider the human capital savings (long term health to the athlete), team capital (keeping key players in longer resulting in better seasonal performance with enhanced revenue) as well as overall health care savings.  Although collectively this is not as quantifiable, most agree it is just as valuable in the overall ROI analysis.

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Conclusion

The current business case highlights the importance of injury prevention initiatives at the collegiate and professional level.  When looking at the rising health care costs, the fiscal impact to the department or team is growing exponentially.  When looking at factors that are not as easy to quantify financially (insurance premiums, paid time on the DL, fiscal impact to seasonal performance with key players lost) as well as the human toll, it becomes apparent that proactive management is imperative.  Although there are many systems out there that are used, the following business case highlights the impact of the Dynamic Movement Assessment™ on health care costs, injury prevention and performance improvement. 

Several key factors that lead to the current results are:

·         Engagement of the coaching staff, strength & conditioning team, athletic trainers, team physician and athletic director – due to the training of the key stakeholders in the movements, pathokinematics and impact on performance/injury prevention all were engaged in the program’s success.

·         Engagement and compliance of the athletes with the program – due to the training of the team on their individual results and importance of preventing pathokinematics during activities the players became engaged in helping their team mates be successful with the training.

·         Flexibility of the DMA™ and it’s integration into existing practice and strength & conditioning schedules by the developers of the DMA™, this allowed them to adapt to the needs of the team and university while maintaining the integrity of the program.

Based on the results with the intervention group, the university will be expanding use of the DMA™ to additional high risk and high health care dollar per athlete sports.  These include football, volleyball and basketball with the anticipation that one additional year of reduced health care spending will result in a decrease in their annual health care premiums.

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References 

1. Ahmad, C.; Clark, M.; Heilman, N.; Schoeb, S.; Gardner, T; Levine, W.  “Effect of Gender and Maturity on Quadriceps to Hamstring Ration and Anterior Cruciate Ligament Laxity”.  Am J Sports Med. 34:370-374, 2006.
2. Beckett M, Massie D, Bowers K, Stoll D. Incident of hyperpronation in the ACL injured knee: a clinical perspective. J Athl Train. 1992;27:5862.
3. Borel S, Shcneider P, Newman C.  Video analysis softwar increases the interrater reliability of video gait assessments in children with cerebral palsy.  Gait & Posture.  33:727-729, 2011.
4. Brophy, R; Schmitz, L; Wright, R; Dunn, W; Parker, R; Andrish, J; McCarty, E; Spindler, K.  “Return to Play and Future ACL Injury Risk After ACL Reconstruction in Soccer Athletes From a Multicenter Orthopaedic Outcomes Network (MOON) Group”.  Am j sports med.  40:2517-2522, 2012.
5. Chappell, J. D., Yu, B., Kirkendall, D. T., and Garrett, W. E.: A comparison of knee kinetics between male and female recreational athletes in stop-jump tasks. Am. J. Sports Med. 30:261-267, 2002.
6. Chappell, J. D., Herman, D. C., Knight, B. S., Kirkendall, D. T., Garrett, W. E., and Yu, B.: Effect of Fatigue on Knee Kinetics and Kinematics in Stop-Jump Tasks. American Journal of Sports Medicine. 33:1022-1029, 2005.
7. Chaudhari, A. M., Hearn, B. K., and Andriacchi, T. P.: Sport-Dependent Variations in Arm Position During Single-Limb Landing Influence Knee Loading: Implications for Anterior Cruciate Ligament Injury. Am J Sports Med. 33:824-830, 2005.
8. Chmielewski, T; Myer, G; Kauffman, D; Tillman, S.  “Plyometric Exercise in the Rehabilitation of Athletes: Physiological Reponses and Clinical Application”. JOSPT.  36:308-317, 2006.
9. Earl, J; Hock, A.  A Proximal Strengthening Program Improves Pain, Function and Biomechanics in Women with Patellofemoral Pain Syndrome.  Am J Sports Med. 39:154-163, 2011.
10. Giphart, E; Stull, J; LaPrade, R.  Recruitment and Activity of the Pectineus and Piriformis Muscles During Hip Rehabilitation Exercises.  Am J Sports Med.  41:1022-1033, 2012.
11. Grindem, H; Eitzen, I; Moksnes, H; Mackler, L; Risberg, M.  “A Pair-Matched Comparison of Return to Pivoting Sports at 1 Year in Anterior Cruciate Ligament-Injured Patietns After a Nonoperative Versus an Operative Treatment Course”.  Am j sports med.  40:2509-2516, 2012.
12. Grindem, H; Logerstedt, D; Eitzen, I; Moksnes, H; Axe, M; Mackler, L; Engebresten, L; Risberg, M.  Single-Legged Hop Tests as Predictors of Self-Reported Knee Function in Nonoperatively Treated Individuals with Anterior Cruciate Ligament Injury.  Am J Sports Med. 39:2347-2354, 2011.
13. Hart, J; Kerrigan, C; Fritz, J; Ingersoll, C.  Jogging Kinematics After Lumbar Paraspinal Muscle Fatigue.  Jour Ath Train. 44:475-481, 2009.
14. Huegel M, Meister K, Rolle G, Idelicator P, Hartzel J. The influence of lower extremity alignment in female population on the incidence of noncontact ACL tears. Sun Valley, ID: 23rd Annual Meeting of the American Orthopaedic Society for Sports Medicine; 1997.
15. Holm, I; Oiestad, B; Risberg, M; Gunderson, R; Aune, A.  “No Difference in Prevalence of Osteoarthritis or Function After Open Versus Endoscopic Technique for Anterior Cruciate Ligament Reconstruction: 12 Year Follow-up Report of Randomized Controlled Trial”.  Am j sports med.  40:2492-2498, 2012
16. Konopinski, M; Jones, H; Jonhson, M.  The Effct of Hypermobility on the Incidence of Injuries in Elite Level Professional Soccer Players.  Am J Sports Med.   40: 390-402, 2012
17. Kristianslund E, Krosshaug, T.  Comparison of Drop Jumps and Sport-Specific Sidestep Cutting: Implications for Anterior Cruciate Ligament Injury Risk Screening.  Am J Sports Med.   41: 684-688, 2013
18. Lucci, S; Cortes, N; Van Lunen, B; Lucci, S; Ringleb, S; Onate, J.  Knee and hip sagittal and transverse plane changes after two fatigue protocols.  Jour Sci & Med in Sport.  14:453-459, 2011.
19. Mandelbaum, B. R., Silvers, H. J., Watanabe, D. S., Knarr, J. F., Thomas, S. D., Griffin, L. Y., Kirkendall, D. T., and Garrett, W., Jr.: Effectiveness of a Neuromuscular and Proprioceptive Training Program in Preventing Anterior Cruciate Ligament Injuries in Female Athletes: 2-Year Follow-up. Am J Sports Med. 33:1003-1010, 2005.
20. McCullough, K; Phelps, K; Spindler, K; Matava, M; Dunn, W; Parker, R; Reinke, E.  “Return to High School – and College-Level Football After Anterior Cruciate Ligament Reconstruction: A Multicenter Orthopaedic Outcomes Network (MOON) Cohort Study.  Am j sports med.  40:2523-2529, 2012
21. Myer G; Ford, K; McLean, S; Hewett, T.  “The effects of plyometric versus dynamic stabilization and balance training on lower extremity biomechanics”. Am J sports med.  34:445- 455, 2006.
22. Padua, D; DiStefano, L; Marshall, S; Beutler, A; Motte, S; DiStefano, M.  Retention of Movement Pattern Changes After a Lower Extremity Injury Prevention Program is Affected by Program Duration.  Am J Sports Med.  40: 355-368, 2012.
23. Quammen, D; Cortes, N; Van Lunen, B; Lucci, S; Ringleb, S; Onate, J.  Two Fatigue Protocols and Lower Extremity Motion Patterns During a Stop-Jump.  Jour Ath Train.  1:32-41, 2012.
24. Quatman, C; Ford, K; Myer, G; Hewett, T.  “Maturation leads to gender differences in landing force and vertical jump performance”.  Am J sports med.  34:806-813, 2006.
25. Sell, T; Ferris, C; Abt, J; Shen Tsai, Y; Myers, J; Fu, F; Lephart, S.  “The effect of direction and reaction on the neuromuscular and biomechanical characteristics of the knee during tasks that simulate the noncontact anterior cruciate ligament injury”. Am j sports med.  34:43-54, 2006.
26. Sheehan, F; Sipprell, W; Boden, B.  Dynamic Sagittal Plane Trunk Control During Anterior Cruciate Ligament Injury.  Am J Sports Med.  42:2145-2153, 2012.
27. Thijs, Y, Pattyn, E; Tiggelen, D; Rombaut, L; Witvrouw, E.  Is Hip Muscle Weakness a Predisposing Factor for Patellofemoral Pain in Female Novice Runners? A Prospective Study.  Am J Sports Med.  39:1877-1890, 2011.
28. Westin, S; Galloway, M; Noyes, F; Corbett, G; Walsh, C.  “Assessment of the lower limb neuromuscular control in prepubescent athletes”.  Am j sports med.  33:1853-1858, 2006.
29. Westin,S; Noyes, F; Galloway, M.  “Jump-land characteristics and muscle strength development in your athletes: A gender comparison of 1140 athletes 9 to 17 years of age”.  Am j sports med.  34:375-384, 2006.
30. Withrow, T; Huston, L; Wojtys, E; Miller, J.  “The relationship between quadriceps muscle force, knee flexion, and anterior cruciate ligament strain in an in vitro simulated jump landing”.  Am j sports med.  34:269-274, 2006.

Using The Dynamic Movement Assessment ™ to Prevent Injuries and Improve Performance With Division 1 Soccer - A Business Case

The following 2 blogs will highlight a current business case being conducted using the Dynamic Movement Assessment ™ in a D1 College setting. 

Injury Rates in Athletics, Health Care Costs & Impact on Performance

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Participation in athletics presents an inherent risk for injury. In high school athletics, football has the highest severe injury rate per 1000 athlete exposures, followed by wrestling, girls’ basketball, and girls’ soccer.  Among comparable sports, females sustain a higher severe injury rate than boys do, with the knee and ankle accounting for over 41% of them most common severely injured body sites.  Decades of research has been devoted to identification of intrinsic and extrinsic factors that predispose athletes to injury. Intrinsic factors include lower extremity malalignment, ligament laxity, lower extremity muscle strength/endurance, neuromuscular control, hormonal influences, intercondylar notch width, and biomechanical technique of sport-specific performance.  Published return to play percentages following an Anterior Cruciate Ligament Reconstruction (ACLR) has traditionally thought to be favorable but recent studies indicate those numbers are much lower than previously thought.  The MOON (Multicenter Orthopedic Outcome Network) group recently published results of a multi-site study indicating that 20% of females who have an ACLR will have a second one within 3 years.  In a 12 year follow up study published in 2012, investigators found that 79% of those who had an ACLR had osteoarthritis on the involved side.  Besides the human toll, there is a huge health care cost associated with.   Annually, over 250,000 to 300,000 suffer an ACL injury. With the average cost of $20,000 to $50,000 per injury, the health care cost is well over $5-10B for the initial injury only.  This does account for the downstream cost of re-injury (which 27% have) or complications from OA (which 79% develop in 12 years).  Although there are some intrinsic factors that cannot be changed, there are many that can be positively influenced with training.  Specifically identifying those athletes with pathokinematics (pathological movement patterns or poor mechanics) and implementing a training regime that targets their specific deficits can and will reduce injury rates.  Over the last decade, there has been a plethora of studies showing that implementing targeted training programs can result in over 80% reduction in non-contact injuries.  If implemented correctly and simply decreasing the incidence by 10% would result in a $500M to $1B health care savings.  So prevention and post-operative rehabilitation are essential to restoration of function and ability to return to sport. 

Although the association of pathokinematics to injuries has been well established, until recently, the association to poor athletic performance has not.  Studies are now indicating that the same pathokinematics that add to increased risk for injury also add to decrease in athletic performance.  Studies indicate that simply improving these pathokinematics results in improved efficiency in the system which has the net result of increased power output and maximal force production.  Improving individual performance and keeping key players off the DL would suggest this could lead to improved team performance.  Knowing there are multiple factors that feed into the complexity of the issue, we must find ways to thoroughly assess all the contributing factors that can be influenced with training and have a reliable method to do such.  We also need to be able to use this not only to assess athletes but also to re-assess the effectiveness of our interventions. 

Hence, this is the reason for development of the Dynamic Movement Assessment™ or DMA™ and the following business case for use in college and professional athletics. 

 

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What Tools Are Currently Available

There are numerous movement screens and tools available to assess movement.  The major drawback with the majority of these falls into three categories:

·         Subjectivity of the scoring methodology. 

·         Inability to assess the “true athletic profile” of how the athlete looks during the game or later in the game post fatigue.

·         Lack of Single Leg Testing – in 2013, several studies showed that single leg testing gives a much more reliable and valid measure of pathokinematics related to lower extremity injuries than bilateral testing.

Current movement systems out there include (but are not limited to):

·         Functional Movement Screen (FMS)

·         SportsMetrics

·         Star Excursion Balance Test (SEBT)

·         Dynamic Movement Assessment™ (DMA™)

As we know, endurance plays a major role on movement and yet all of the movement screens (with exception of the DMA™) fail to tap into to the athlete’s true athletic profile following exertion or mid-game or end of the game pathokinematics where we know most injuries occur. 

With this business case, the DMA™ was chosen for the intervention for the following reasons.

The DMA™ proposes to:

• Capture the mechanics we “know” are related to injury and performance issues
• Be challenging enough that it taxes the system in a way that mimics sport (80 reps and 3 min of planks) vs. 3 reps of an isolated movement
• Improve interrater reliability – use of Dartfish technology has been shown to improve interrater reliability with movement and gait assessments.
• The intensity of this movement system taxes systems in the way that is similar to sport
• Use movements that are sport specific, FWB and incorporates single leg.
• 50% of the test is performed on one leg and therefore more accurately accesses pathokinematics associated with injury

Although these are ‘major differentiators” from the other system, it also:

• Considers the magnitude of the deviation (amount of lateral shift and adduction to mid-line or past) in the score
• Considers the # of deviations in the scoring
• Provides visual feedback which is essential for motor learning, mental rehearsal and changes in motor patterns
• When used with the fatigue protocol, it puts the athlete in competitive sport like condition with similar endurance and strength demands – average D1 college athlete rating of exertion was 8/10 on over 150 subjects
• Provides flexibility for integration into the existing university’s strength and conditioning program

The next article will highlight the methods, results and conclusion.

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References

1. Ahmad, C.; Clark, M.; Heilman, N.; Schoeb, S.; Gardner, T; Levine, W.  “Effect of Gender and Maturity on Quadriceps to Hamstring Ration and Anterior Cruciate Ligament Laxity”.  Am J Sports Med. 34:370-374, 2006.

2.       Beckett M, Massie D, Bowers K, Stoll D. Incident of hyperpronation in the ACL injured knee: a clinical perspective. J Athl Train. 1992;27:5862.

3. Borel S, Shcneider P, Newman C.  Video analysis softwar increases the interrater reliability of video gait assessments in children with cerebral palsy.  Gait & Posture.  33:727-729, 2011.
4. Brophy, R; Schmitz, L; Wright, R; Dunn, W; Parker, R; Andrish, J; McCarty, E; Spindler, K.  “Return to Play and Future ACL Injury Risk After ACL Reconstruction in Soccer Athletes From a Multicenter Orthopaedic Outcomes Network (MOON) Group”.  Am j sports med.  40:2517-2522, 2012.
5. Chappell, J. D., Yu, B., Kirkendall, D. T., and Garrett, W. E.: A comparison of knee kinetics between male and female recreational athletes in stop-jump tasks. Am. J. Sports Med. 30:261-267, 2002.
6. Chappell, J. D., Herman, D. C., Knight, B. S., Kirkendall, D. T., Garrett, W. E., and Yu, B.: Effect of Fatigue on Knee Kinetics and Kinematics in Stop-Jump Tasks. American Journal of Sports Medicine. 33:1022-1029, 2005.
7. Chaudhari, A. M., Hearn, B. K., and Andriacchi, T. P.: Sport-Dependent Variations in Arm Position During Single-Limb Landing Influence Knee Loading: Implications for Anterior Cruciate Ligament Injury. Am J Sports Med. 33:824-830, 2005.
8. Chmielewski, T; Myer, G; Kauffman, D; Tillman, S.  “Plyometric Exercise in the Rehabilitation of Athletes: Physiological Reponses and Clinical Application”. JOSPT.  36:308-317, 2006.
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