 Welcome everybody back from break and thank you for your participation in the trivia poll, more than 1200 people participated in the poll. 81% of you experts picked the winner of the only US gold medal in 1968 as Miss Peggy Fleming figure skater. Interesting factoid Peggy Fleming moved to Colorado Springs, Colorado to go to high school to train at the Broadmoor Figure Skating Club and and then 52 years ago won her gold medal in figure skating. So we are jumping into our next session. Focus on strength and conditioning and biomechanics and I am honored to introduce our first panelist Dr. Matt Jordan. Matt has been a strength and conditioning coach and applied sports scientist working with international athletes over six Olympic winner games. He's currently the director of sports science at the Canadian Sport Institute in Calgary. Matt has consulted with more than 30 Olympic and world championship medalists. Dr. Jordan, thank you for joining us. Hi, my name is Matt Jordan. I'm the director of sports science at the Canadian Sport Institute Calgary, which is one of four Olympic training centers in Canada. And it's a real pleasure to be here today to share some outcomes from a paper that we published recently in frontiers and sports and active living, looking at monitoring the return to sport transition after ACL injury in an alpine ski racer. So over the next 15 minutes, we're going to talk about why it's important to have objective metrics to support the return to sport transition for ski racers, the importance of not adding to the uncertainty around ACL injuries, the importance of a team approach and how we use monitoring to help support the athlete in their transition back to health and to performance. So why this matters? Alpine ski racing is a high risk sport for traumatic injury in general. But ACL injuries are the most common injury type. And what we know is that 20 to 40% of these athletes will go on to suffer an ACL re-injury, often to the other side. These athletes are constantly managing risk. It's a very demanding environment, fatigue, high forces. And it's a very technically and tactically demanding sport. And as previously mentioned, ACL injuries occur frequently. Injuries often happen like the video you're seeing on the screen, a very high energy injury mechanism, the athletes landing in the back seat and suffering a catastrophic right knee injury. When you talk to skiers about this, oftentimes they downplay it. Sounds like, you know, getting your wisdom teeth pulled like everybody goes through it. But what we know is that it's much, much more than just an ACL injury. There's often trauma to other knee joint structures. These athletes often go on to have arthritic knees within a few years after their injury. And it's about restoring confidence and function to help them make this transition, you know, not only back to health, but back to sport in this high risk environment. What we want to avoid is what's often been referred to amongst our team as the regrettable cases from the past, you know, where athletes have been potentially cleared too soon to get back to snow and then suffer a re-injury. This athlete that you're seeing on the screen right now had a left side ACL injury and you see him now holding the right knee. So he's just suffered a knee injury, a contralateral knee injury. And this happens all too frequently in Alpine ski racers. And it's at this transition back to sport where mistakes happen in our judgment. It's very easy to get bought in emotionally to the athlete's journey back to sport. And oftentimes, you know, we want nothing more than to give them the green light to get back on snow doing something they love. But it's here that it's critically important for us to be able to have measures, to have objective measures to help support our decision making account for our confirmation bias and make sure that we are doing everything we can to support this athlete back to sport in a healthy and safe manner. So we gave in the paper, we talked about this idea of a bucket of blue chips and red chips that we could boil down a risk profile for an athlete in a really simple conversation using an analogy or a picture of a bucket of blue chips and red chips so that we could help manage discussions around when an athlete should return to sport. And this is critical because, you know, after an ACL injury, what's the first thing that the athlete says? When am I coming back? And, you know, they might look to the media and hear stories of athletes coming back at four months and five months post-surgery, these very aggressive timelines. And obviously, we have to be able to contextualize this to the athlete. So how do you contextualize uncertainty? This case study was built around the athlete that you see on the video here. And she's given me permission to talk about her case study for the purposes of science and education. Here she's suffering a right-side ACL injury and actually a shoulder dislocation. So the question would be, you know, how are we going to contextualize the uncertainty around when this athlete's ready to get back to sport? Well, if we use this idea of a bucket of blue chips and red chips, the bucket on the left side is the rough risk profile for an athlete who's not had an ACL injury in ski racing. It's the rough risk profile for suffering an ACL injury, roughly one to two skiers per 20 skiers per season. What we know is after that first ACL injury, the risk for a second ACL injury goes up about 14 times. So now, instead of pulling out of the bucket on the left, the athletes who's had an ACL injury is actually now pulling out of the bucket on the right. And based on the pictures, what you see is you get a blue chip, you're all good, you get a red chip and you've got an ACL injury or re-injury. So should I get back early? You know, should we go back after four months, six months, eight months? Maybe we should wait 24 months. Well, what it boils down to is being able to contextualize this risk in a productive way to an athlete and within a performance team that's there to support them. So imagine we're talking about an early return. Well, we might be pulling from the bucket on the left. Here, represented on the bucket on the left is the notion that the athlete had a limb symmetry index of less than 75%, which means that their asymmetry and quadriceps strength in this example is more than 25% from side to side. So, you know, there are blue chips in the bucket, meaning if the athlete reaches in there, grabs a chip, there's no chance they could pull out a blue, but we just see a whole lot of red. Now imagine that we wait until the athlete clears that 75% limb symmetry index. So now they're above that threshold. We see that the risk profile has changed looking at the middle bucket. And then let's take the bucket on the far right where we wait till the limb symmetry index is more than 90%. So less than 10% different side to side and quadriceps strength. Now we see the athletes pulling from a much more favorable bucket, but it's important to know that there's still red chips in the bucket. And that's one of the challenges around contextualizing risk is sometimes that we feel that, you know, if we do everything right, everything should go right, but it's just not the case. You know, the reality is that even on the bucket on the right where you've tried to check all the boxes, there are still red chips in the bucket. And that's an important thing to contextualize when we're talking about the risk of ACL re-injury and how to manage a transition back to sport. So the question becomes, what bucket do you want to pull from? The bucket on the left or the bucket on the right? Also, in addition to sort of having this conversation around risk of re-injury, it's important to have a multidisciplinary team that can help support the athlete. In this case, we highlighted the role of the nutritionist, the strength and conditioning coach, the psychologist, the sport medicine physician, the orthopedic surgeon, and the physical therapist. And we proposed this idea of it being a holocracy or a flat leadership structure, which would mean that at any given point in time, any of the team members could step up to voice an opinion or lead a situation, depending upon what was called for. And that this was one way that we could sort of support and avoid, support the athlete and obviously avoid making a poor decision around when an athlete's prepared to get back to snow. The other idea with this performance team is being able to create alignment and purpose with the use of data. And this is just one example that we used. And what you're seeing on the screen right now is data from our database collected at the Institute on athletes with ACL injury, in this case ski raisers. And we're looking on the left-hand panel at the asymmetry in the concentric phase of a counter movement jump and the symmetry in the late phase of a squat jump shown here on the right panel. The black horizontal line represents 0% asymmetry. And in this case, asymmetry was calculated as an average between five and 10 jumps. And we can see here, when we look at on the x-axis of days from surgery, that there is a recovery in the functional asymmetry as time progresses. So here, early on post-surgery, some athletes are approaching nearly 40% asymmetry in the counter movement jump. Some athletes had asymmetries of more than 50% in the squat jump. And we could see that there's a recovery in the functional asymmetry as time progresses. So with this data, we're able to now contextualize what the recovery rate looks like for an athlete. So rather than having returned to sport be sort of like a final exam where the athlete crams for months and goes and tries and goes to try to pass a battery of tests, we propose this notion of monitoring. So here, we can now track the trajectory and the recovery rate of the athlete to be able to have a conversation around, is the athlete tracking according to expectations, behind expectations, or maybe they're tracking rate on what we would expect. And this was a way that very early on is the athletes recovering that we're improving the quality of the discussion and improving the team's ability to support the athlete. This example looking at vertical jump functionally symmetries is just one example of metrics that go into this idea of a risk profile. But the important thing is having the capacity to monitor these simple things consistently over time. And in the paper, we did highlight the importance of making sure that we are considering the time from surgery. That's another important factor in a successful return to sport after ACL injury is ensuring sufficient time for tissues to heal. But blending this idea of a time-based approach and also a functional milestone-based approach for the athlete. And we propose this idea that in this environment where decision-making is often comes with added pressure and added anxiety, that we could communicate this timeline and milestone-based approach for return to sport in advance, like many, before an injury even happens, at the start of the season to a team of non-injured athletes. To discuss the idea that not only are we going to be considering the time from surgery, which will be guided primarily by the orthopedic surgeon and the sport medicine physician, but also the functional milestones. And then at that point where we see a transition back to sport, that it would involve not only just a medical viewpoint of how the athlete was adapting, but also their physical and mental performance status as well at that point. And importantly, we use this word transition. Transition meaning that in this phase as the athlete makes her way back to snow, there's the possibility of both progression and regression as they make their way back. And then at the very bottom here, and we'll speak to this in just a couple of slides, is the important of having monitoring. So rather than, again, this sort of clearance approach where a bunch of testing happens at a discrete time point, how do we monitor the athlete to support them in this journey back after injury? So with our case study, we have here on the screen a counter movement jump, which was one of our core monitoring tests that we used in our return to sport testing battery. So we had plenty of pre-injury data for this athlete, but also were able to get multiple time points as she was recovering after her injury. And you'll see here on the left hand panel, a representation of her vertical jump profile at about five months post-surgery. And here on the right, the vertical jump profile at seven months post-surgery, right where she was about to make a transition back onto snow. And you know, in this case, the green and the blue line represent the ground reaction force from the right and left limbs. In this case, the blue line representative of the ACL reconstructed limb. And we were able to use this data to build a risk profile for this athlete along with other data points. So take a moment just to consider her data from vertical jumping. Again, we have the asymmetry index shown on the vertical axis and all of her jump tests going back to, you know, May of 2012 all the way to May of 2019. The black horizontal line represents 0% asymmetry calculated over at least five jumps. The black dash line is plus and minus 10%. And what we have here in panel A is the eccentric deceleration phase of a counter movement jump, the concentric movement phase of a counter movement jump in panel B. And then the early and late takeoff phase of the squat jump shown on the bottom two panels. So the squares here represent her pre-injury data. And so these are all the tests that she would have done before the injury. Here we have is the black dash line, where the injury occurred. The second black dash line shows the return to sport transition. And the solid black line shows where she is at 18 months post-surgery. So this is an 18 month post-surgery measurement shown here on May of 2014. And, you know, this data shows a couple of important things. First of all, if we just take, for example, a look at her concentric phase of her counter movement jump, you can see here flirting with just about 10% asymmetry after her ACL injury, which isn't horrific. But we can clearly see that the profile, even though the asymmetries are low, she's not looking like she did before until she's about 18 months post-surgery. And that's an important concept. Because in this particular study, while the functional asymmetries that we measured were low in this athlete, we did see some very interesting trends surrounding her quadricep and hamstring strength. So on the left panel here, panel A, we see quadriceps and hamstrings maximal strength. And on the right hand panel, we are showing rate of force development or explosive strength. The solid line is her knee extension torque. And the dash line, which you'll see in a second, is her knee flexion torque. Now importantly, we see a small gradual recovery in her knee flexion torque. We see a nice robust increase in her knee extension torque for her ACL reconstructed limb at 18 months post-surgery. But the really important part of this case study was the de-training that occurred in both quadriceps maximum strength and explosive strength over the post-injury period. And as you meant, as I said earlier in the presentation, 20 to 40% of these athletes will go on to suffer an ACL re-injury. And very often, that's to the contralateral limb. So the important message in this case study is the critically important viewpoint of measuring strength not only in the injured limb, but also the non-injured limb. As we come towards the end of the presentation, I just wanted to briefly touch on another part of the case study that was important. We talked about measuring workload. And in this case, we did that through the Session RPE method. But what I wanted to point out is the fact that in her return to sport training plan, it was periodized. So we had periods of recovery and unloading shown here, in this case here with a circle around the dot. And we talked about the importance as this athlete was coming back through the return to sport transition that prior to getting back on snow, we had ensured she had restored her physical work capacity to comparable values that we would have seen in previous seasons to support the return to snow and the on-snow training environment. So just to kind of touch on the final point here about some of our losses, I just wanted to point out the importance of debriefing. That was a comment that we made in the paper is how important it is not only to focus on the things that we've done well, but also on the things that we could do better. And debriefing is a critical part of this process when it comes to supporting athletes after ACL injury. So with that, I just want to wrap it up. Thank you very much for your attention. This sort of gives us a summary of where we came from today. I'd like to acknowledge all of the individuals who helped support me with this presentation today. And a big thank you to all of you for your attention. And hopefully now we can open it up to a few questions. Thank you.