How Do We Know When Is The Time To Return To Sport? - Part III

In last week’s blog we talked about the impact that injury has on return to sport and specifically the impact on performance.  This led to the question, how do we make return to sport calls.  Is there a way to assess both biomechanical risk factors in a closed kinetic chain and performance measures?  What does the research tell us? There are several ways this is being done today. 

One of the standards of practice is the use of the Functional Movement Screen. But is this a good predicative tool for determining return to play?   

• Bardenett et al - Int J Sports Phy Ther 2015 - looked at the FMS as a predictive tool in high school athletes.  Of the 167 high school athletes that were assessed during the pre-season, the results showed the FMS was good at recognizing asymmetry in the movements tested.  But they found that the results were not a good at predicting injury.
• Dorrel et al - J Ath Train 2015 - performed a systematic review and meta-analysis of research from 1998 to 2014.  What the results showed was that the FMS demonstrated low predictive validity for injury prediction and leading the authors to conclude that this should not be used for injury prediction.
• Bushman et al Am J Sports Med 2016 - looked at the FMS as a predictive tool in active male soldiers.  Of the 2476 soldiers assessed, the FMS demonstrated low sensitivity and low positive predictive value.  This lead the authors to conclude this could lead to misclassification of injury risk in military personnel.  If they are assigned to hazardous duty as a result of this misclassification, it could potentially place the soldier at greater risk.
• Wright et al Bri J Sports Med 2016 - in this clinical commentary based on the literature review showing a low sensitivity of 24% led the authors of this paper recommending that this should not be used for injury prediction or for making return to sport calls.

On clear example of this is a recent paper, Dobson et al, Ortho J Sports Med 2016, that looked at injury rates, specifically ACL injuries in NFL players.  Despite implementation of the FMS, biodex testing of quad to hamstring ratios and other such tests, NFL ACL injury have risen dramatically.  Up till 2010, ACL injury rates were occurring at a rate of ~10 ACL injuries per year.  From 2010-2016 there have been a recorded 219 ACL injuries (~36/yr).  So despite having access to all the latest information, they are still not impacting them in a positive way.  What gives?  Simply stated, we are NOT looking at the right things.  When a player can score a 17 on a screen and yet his knees nearly touch on a broad jump, then we are obviously not looking in the right direction.

In 2011 Grindem et al published a paper looking at the single leg hop tests as a predictor of knee function.  In this study the authors compared the single leg hop test to the International Knee Documentation Committee (IKDC).  The IKDC is a self-reported outcome measure that has been shown to have a very sensitivity and specificity to actual knee function.  The authors compared the results on the single leg hop to IKDC scores for those who had ACLR.  The following diagram indicates the single leg hop tests that were performed.  This study showed that symmetry in single leg hop for distance predicted self-reported knee function on the IKDC with a high degree of sensitivity and specificity.   The single leg hop for distance is a great measure of power output in the horizontal.  This same measure of power output can also be obtained with a single leg for height.  One is great for forward propulsion (hop for distance) and one is great for vertical propulsion (hop for height).  Both of these are critical in sport but when also considering mechanics (adduction in the frontal plane) how do you quantify that with either of these tests?  Or is that even possible? With the advent of technology, it is possible, at least for the vertical single leg hop.  Taking a look at the picture here, we can easily capture not only quantify the mechanics with the single leg hop but we can also quantify her vertical displacement during the test.  Having both of these factors performed over multiple repetitions, we can then get a biomechanical assessment of risk as well as comparison of the right limb to the left limb in terms of power output.   But how do we do that objectively and with a high degree of reliability?

As we have stated in previous blogs, frontal plane motion is not the only risk factor.  Rohman et al Am J Sport Med 2015 showed that symmetry in single limb performance is a critical measure for risk.  We also know from Kristinaslund et al Am J Sports Med 2013 that one of the best indicators of risk and athletic performance is performance in single limb testing.  We can watch and record these movements with various technologies (like Dartfish) but that is often time consuming and takes a higher level or expertise to be able to do it in a fashion that is efficient and reliable.  In addition to 2D technology, we are seeing a plethora of new 3D wearable sensor technologies hit the market that are extremely reliable.  Many of these use IMU (inertial measurement units) with accelerometers, gyrometers and magnetometers to detect motion, rotation and acceleration data.  With these technologies, we can now quantify movement with lab quality results and are able to quantify both the magnitude of valgus that occurs in addition to the speed at which that motion occurs. 

As we see a further blending of these types of technologies with the movement sciences is when we will really see an impact on both lower limb injury rates and improvements in athletic performance.  Next week we will explore this a little more.  For more information on this topic and more, make sure to follow us on twitter @ACL_Prevention or on Instagram @bjjpt_acl_guy.  

Dr. Nessler is a practicing physical therapist with over 20 years sports medicine clinical experience and a nationally recognized expert in the area of athletic movement assessment.  He is the developer of an athletic biomechanical analysis, is an author of a college textbook on this subject  and has performed >5000 athletic movement assessments.  He serves as the National Director of Sports Medicine Innovation for Select Medical, is Chairman of Medical Services for the International Obstacle Racing Federation and associate editor of the International Journal of Athletic Therapy and Training.   He is also a competitive athlete in Jiu Jitsu.