Transcript
Hello.
My name is, doctor Glenn Lachey.
I'm a professor of clinical psychology at the University of North Carolina Wilmington.
It's a pleasure to be here to go through this presentation with you.
Our focus today will be on the selection of objective measures, that are used to help return to play decisions.
And the main focus I'm hoping that you'll see this, presentation in a little bit of a different light.
My goal today is to help show essentially show you some of the research literature, really the expansive research literature that tells a very different story compared to common practices that we do in terms of healthcare professionals and making return to play decisions.
In fact, some of the decisions we make at the front end when we're deciding what measures to use go a long way to actually affecting the decisions we make with that patient down the road.
Before I get started, let me highlight a few disclosures.
We've received grants from, multi health systems in Canada.
Received those through the University of North Carolina Wilmington or UNCW for short.
They've supported, doctoral student training.
And we've also been looking at the efficacy of a few different tests by multi health systems, including the CPT 3 and the TOMB 2 and the use of mobile technology.
I'm also a consultant minor shareholder for SportGate and Lifegate.
And I head up their research consortium through the university.
Sportgate is also a tenant at the Center of Innovation and Entrepreneurship at the university.
And the UNCW, the University Research Foundation, is a minor shareholder for Sport Kate and LIFE Kate.
I'll be reporting, several studies today, most of which will become from the broader literature.
But when you see the research from our own consortium, I also want to note that that is, spork gate data that we will be presenting.
We have some learning objectives, for you today.
So identifying multiple domains that should be assessed in a post concussion RTP evaluations.
I'm gonna clarify your understanding of the scientific literature on RTP timelines and how that varies by domain and measure.
We're gonna take a look at how we should be using self report symptoms relative to objective domain specific measures and how to best sort of integrate this information when you make an RTP decision.
Alright.
So as I mentioned at the outset, I'm gonna ask you to kinda put aside some of the ways you might typically think about approaching the practice of evaluating athletes and returning them to play and to just consider the research with, with an open mind.
And one of the things that I'm hoping to illustrate is that when you make the decision to approach and say, hey, we're gonna use this measure, whatever that measure happens to be or not use a particular measure.
That's actually going a long way to, in fact, probably a major deciding factor to actually determining when you're gonna return someone.
Because one of the things that you're gonna realize is, obviously, as a health professional, you'd like to think that when we return someone, make a decision about returning someone, it's based on what's going on with that person.
Unfortunately, that gets confounded with whatever you use to measure that particular person.
So the specific measure you select and how good that measure is, obviously, if it's not particularly sensitive, not particularly good, well, then it's not gonna pick up problems that are actually there.
Likewise, which domains you measure, you choose to measure and which domains you choose not to measure.
Well, that also will drive the RTP decision because it turns out different domains have different recovery, timelines.
And so that also has implications again by the decision of the measure that's selected.
So the selection of the measure, even how you choose to use them because obviously you can, you know, think of, well, how do I combine all of this information?
So just make this really concrete for you.
If, hypothetically, you choose a measure that the research says doesn't work beyond 1 week, then by definition, it's either, a, not gonna inform you at all after 1 week or, b, misinform those decisions after a week because if it can't pick anything up after a week, it's gonna look clean.
And, thus, you would conclude, well, the person must be better.
That would be an erroneous conclusion because the measure itself has a limit of not being able to pick up something even when it's there.
So just to make that really concrete, that's what we're gonna be looking at.
We're gonna run through some of the research on this.
Now, some of what I'm about to present is gonna look like a bit of an existential crisis of like, wow.
Are we, you know, doing this thing wrong?
And a lot of times, points of crisis lead people to just kinda bury their head and say, well, I don't wanna, you know, deal with this.
But really, we have a tool for dealing with these points of crisis and that tool is science.
Science can lead us out of can lead us down the path of doing things properly and solve these problems so that really they're not problems.
And the advantage is we're not just doing this as a, you know, let's patch something up and fix it, but rather that we can actually develop, better standards of care just by applying the scientific findings.
We can therefore optimize optimize outcomes for individual patients and even, help guide some of the standard language and state legal requirements, etcetera.
So we wanna make sure we conform to them, but also science can help guide those those as well.
Okay.
So we'll begin with a concussion.
Obviously, if you're an athletic trainer, for example, you you have a lot of experience with this, but it's important to recognize when we talk about a traumatic brain injury.
So first of all, a concussion is a traumatic brain injury.
It's typically caused by some type of physical contact or jolt, and most typically to the head, but, of course, it could also be to the body.
What's the critical feature here is that that contact results in essentially a movement of the brain inside the skull.
And so, of course, a direct hit can do that, but also a sudden deceleration can cause that.
And we expect to see consequences, for the brain at the point of contact.
It could also be on the exact opposite side of, the brain as well, and of course, in various other areas depending on how you're angled.
So things like as the brain is moving inside the skull, it can rub up against the skull and cause damage, what's called axonal shearing, the shearing of neurons.
But from on this brain damage, brain cells are damaged, during a concussion.
And what is typically focused on is not so much the idea of what is damaged, but rather the idea of what are the functional consequences of those damages.
So where what impairments might occur, what changes in functional abilities might occur.
Those don't always go exactly hand in hand.
And so, you know, again, if someone's having no functional problems, we usually worry less about that.
But the functional most of the assessments that we see that are used, and rightfully so are functionally based.
So you're probably well very familiar with the kinds of signs and symptoms we see with concussions, dizziness, nausea, headaches, confusion, disorientation, processing speed, concentration, attention.
We see also motor disturbances, that affect things like gait speed and power, symmetry, balance.
We see symptoms like lack of energy, depression, mood, and personality changes.
These tend to not occur immediately.
They tend to be a little more delayed.
And really that's true for many of the symptoms even though the the mood ones are consistently delayed.
Some of the other cognitive symptoms also tend to show up a little more, 24, 48 hours down the road sometimes referred to as a symptom bloom.
May, in fact, may peak in the next day or or 2 days out.
This is one of the reasons why premature returns really early would be a very dangerous thing because we don't know if that symptom bloom is coming.
And obviously, a premature return within that period of time would would be concerning to miss that.
It's also the case that researchers in the last few years have suggested that maybe we have different types of concussions, so concussion subtypes.
This actually is an interesting and important articulation, especially if we go back to the comment I made at the outset, which is that when we select certain measures that are in particular domains, if we really think of these as concussion subtypes, we can really be thinking about completely missing a subtype.
So if I have a cognitive measure and that's all I'm doing as far as an objective measure, I could be missing other concussion subtypes that have other features like neuromotor or visual spatial or other components that are not cognitive in nature as an example.
Now one of the reasons we wanna make sure we're measuring the functional consequence of concussion properly is that it then informs a timely return as opposed to a premature return or even holding people out, needlessly for too long.
But that premature return is really the, you know, biggest concern because it has some very clear consequences.
It's been linked to increased risk for dementia down the road, as well as other types of cognitive decline, mood disorders, movement disorders, and even death.
So there's morbidity associated with early return.
And we see this particularly when there are multiple concussions, when the individuals returned prematurely.
And this really highlights the fact that the issues and problems that we have with concussion aren't so much with the occurrence of a concussion, but rather they're with the mismanagement of that concussion.
That is in it's really in the hands of health professionals to recognize, hey, we've got a problem here.
It's a it's a brain injury, and we really shouldn't be returning people until they're clearly recovered.
And so it's that mismanagement that can cause some of the most dire consequences.
Now we estimate about 4,000,000 concussions occur in the US on a yearly basis.
If we're thinking about sports environment, there are some differences, gender differences in the most common ones.
Football is most common for males, soccer and cheerleading for female athletes.
Please keep in mind all sports have the potential for concussions to occur.
These are just where they're reported at the highest incidence.
It's also important to know, and this helps us recognize that the risk really can be in any sport, is that the far higher incidence of concussions is in everyday life.
And we see this in slip trips and falls, motor vehicle accidents, assaults, and that actually counts for over 50% of all reported concussions.
Now it's also critical that we see that most concussions actually don't get reported.
Part of that, of course, is because they don't have the benefit of, let's say, having a health care professional like flight trainers on the standby and ready there to notice some things.
And when people are left to their own devices, they often are less likely to seek out medical care for a wide range of reasons.
When we talk about a concussion, we usually refer to it in the context, the broader contracts of a of the term, traumatic brain injury and most specifically a mild traumatic brain injury.
Mild essentially means that the symptoms will be less severe than what we tend to see in moderate or severe traumatic brain injuries.
There's a few other differences as well in terms of typically less, or no evidence of imaging to support the presence of it with a mild traumatic brain injury.
But the critical feature is it's mild, subtle, means we're gonna have to have some pretty good measures to to pick it up.
So sport related concussions, the estimate is somewhere around close to 90% are going to be in that mTBI mild category.
Still a brain injury, so we wanna take it seriously.
The critical feature here, and here's how I want you to start putting on your thinking hats about how you use your instruments and how you use self reported symptoms.
It's the first thing is to recognize that the these measures, when you pick a measure and you're gonna use a measure, those measures are most useful when symptoms are either mild or completely absent.
They're less useful when symptoms are present, especially if they're severe because the bottom line is if someone's reporting symptoms of a concussion, that's reason enough not to return them at that point.
Right?
So if I've got double vision, a bit of a headache, you wouldn't wanna clear me and put me back in.
That's reason enough for me not to be used.
So where the instruments are of use, particularly use, is when those symptoms abate.
When they're absent, then I wanna look at that.
And I'm gonna try and sort of set that up for you in terms of the use of this in RTP decisions.
Now, objective valid test data to capture the consequences of concussion.
That's where there are paramount importance.
We need good measures to do this.
We wanna assess concussions in a multiple domains, not just one.
Single point solutions aren't good, especially as we consider that there could be multiple concussion subtypes.
We wanna make sure the measures are reliable, meaning they produce consistent scores.
They they as an instrument are reliable.
They're valid, meaning they actually measure what they're supposed to measure and that they have excellent norms that they represent the people that we're assessing.
Now, it is the case that post concussion, it's recommended that there be multiple assessment points.
Obviously, if you have a baseline data point, that's helpful too.
It's not necessary if you have a good instrument, good normative data, but it's it can be helpful.
But you certainly don't wanna do a one and done approach post incident.
You wanna have multiple data points, because individuals presentations can change as we saw at the beginning.
Symptom blooms can occur, etcetera.
And so you you don't wanna have just a single data point to make that decision.
Because of that, it's also important that your test not have practice effects.
You don't wanna have instruments that basically people get better at just because they're taking them multiple times.
Keep in mind, practice effects are really consequential because they'll look like a recovery.
If I get better, the more I take a test, the more frequent I take a test, well, it's gonna track like I'm improving even though you would see that if a test has practice effects just as a function of taking the test repeatedly.
So we wanna obviously avoid, test with practice effects.
Here are a few of the domains that you should consider having objective measures to assess.
So neurocognitive functioning, executive abilities are the area that research suggests are particularly sensitive post con concussion.
And you could make those comparisons come or normative data.
So how the average person with your demographics performs and also how you perform over time.
Again, whether you have a baseline or even if you're in recovery compared to previous scores.
We it's important to get some neurobehavioral data.
So this could be gait, balance, especially dynamic postural stability is a critical one.
So it involves movement.
I've mentioned mood.
We often see those present both as independent symptoms, but also the fact that other concussion symptoms tend to last longer when mood symptoms are present.
Of course, you wanna ask about concussion history makes a big difference.
Person's had 4 or 5 concussions or if it's their first concussion in terms of how you might consider treating, not just treating them, but then also the RTP decision and and their active, concussion symptoms.
I wanna jump to a study that was conducted by, Steven Broglio and published in 2023 and and colleagues.
And this find it's a really informative study.
It's a large study, but I want you to take a look here at the average time to return to baseline scores.
So you get baseline data, an incident occurs, and you track how long it takes for scores to come back to baseline.
Now I want you to note that when we're looking at things like the number of symptoms or symptoms severity, that all those values are less than a week.
So essentially 6 point something days.
And if you even look at the range, on those values, it's a pretty tight range.
Doesn't go over 7 for any of for males overall.
It's just the first column.
And when you look at males and females, there are some important differences but on other measures but not here.
So essentially virtually everybody takes about 7 days to recover symptom wise, meaning they return to baseline on those symptoms.
Now you might look at this and say, oh, okay.
Well, then people get better symptom wise in in about a week.
The rest of the literature actually doesn't tell us that.
What it does consistently tell us is people stop reporting symptoms after about a week.
That doesn't mean that they're better.
And, again, this is gonna be one of those hopefully moments, that we'll have, today.
Now there's a number of other measures summarized here, and you're gonna see similar findings just about all of them somewhere between 3 days to 7 days are gonna return to normal.
At the, the very bottom, you will see, so you see the best is in there as well.
Many people use that.
SAC is in there.
You see impact on here as well.
And, again, you'll notice that things like verbal memory tend to return pretty quickly.
Visual motor speed tends to return very quickly.
Now there are one exception.
One that really stands out here is reaction time.
So there is a reaction time measure on, impact testing.
You'll notice that it has values that are closer to well, they range, for female athletes as slow as, or they return to baseline as quickly as, 4.8 days on average, and for male athletes as long as, 21 just over 21 days.
But the vast majority of the data essentially tell us that scores return relatively quickly.
So knowing this, knowing that most people symptoms return there, what it means is, well, if you pay attention to these things and we know, in fact, most medical professionals rely primarily on self report symptoms, well, that's gonna tell you that if that's what you're leaning towards, that 1 week return would not be unusual.
Okay?
So most individuals would be returned within that period of time if you're focused on symptoms.
If you're looking at other measures, you can see, well, all except for possibly a reaction time measure, on impact, All the rest of them will also tend to lead you to return even within a certainly, 1 to 2 weeks would not be unusual.
And not surprisingly, we, you know, we see that that is the common practice.
Most people are returned within a couple of weeks.
Now one question, of course, is how you decide to use all these different data points.
If you're just kinda thinking, well, the preponderance of data, the bulk of the data, it's gonna tell you people are ready to return.
But what I'm hoping to show you is that really what it's telling us is that it's revealing the limits of these instruments and what we're relying.
Self report symptoms, people tend to stop reporting.
Whether they're having them or not is a separate issue.
Most instruments tend not to work beyond that week, 2 weeks at most.
And, again, it's a it's we're gonna see it's a function of the instruments.
So in a sense, when you choose to use these things, you're gonna return most people in that period of time because that's when these things tend to return to normal.
So, I'm I'm sure you have different approaches.
Some some of you decide to combine your data and use the average of kind of what the data are telling you.
Some of you might use the quickest recovery data to guide you.
Some might rely on the slowest.
But in many of these scenarios, again, you're gonna return relatively quickly.
We're gonna see in the literature that doesn't necessarily jibe with what's occurring.
So we do know when we look at the literature that it's widely acknowledged that, the consequence of concussion will will persist typically beyond that 7 to 10 days and persist beyond when patients are no longer essentially reporting symptoms.
So our reliance on the absence of symptoms or or the cessation of reporting symptoms is a huge mistake.
In fact, there was a very large study.
It was published back in 2022.
We see Brollio again involved in that, looking at almost 35 1,000 athletes.
That estimated that recovery is probably closer to a month.
And, again, that would be a completely different practice than what we're currently doing.
And researchers have been for a long time saying, hey, look.
We need to be reconsidering these quick RTP timelines.
And it's especially true for younger athletes who are the estimates might be they have an even longer recovery.
So obviously, these this has some pretty big implications if we're returning people within 1 to 2 weeks.
Let me just kinda break this down very clearly.
So if self report symptoms return to normal within 6 to 7 days, There are basically 2 conclusions you can make of this.
1 is, okay, the patient's recovered.
Alternatively, it's the sensitivity of self report expires after about a week.
And that means that they're not necessarily recovered, but we've just reached the limit of self reported symptoms.
And, thus, we have to start looking at something else.
So if we're relying on symptoms, if present, they're important because it tells us there's something going on.
Don't return.
If they're absent, it means they haven't necessarily recovered.
Maybe they have.
But the next step is we need to focus on other information that has better sensitivity that goes beyond the week.
Okay.
So, obviously, I'm sort of picking on measures and saying, well, maybe maybe we need to do something better.
We need to focus on measures.
The problem is that some of the most commonly used tests and I'm gonna use impact and scat to represent that they are the 2 of the most widely used tests, whether you're doing sideline evaluations, baselines, etcetera.
They're very popular.
But the the clinical letter when you when you actually look at the research literature, at best, it's equivocal.
Most cases, it's very critical of these measures.
Essentially, the reason it's critical is because that they tend not to be particularly good measures.
They they don't pick up symptoms and certainly don't pick up symptoms over a longer period of time.
And again, these are 2 of the instruments that have really been called out for maybe not working beyond that sort of 1 to 2 week time period.
And I'll show you the data that that speaks that.
Let's start with some of the reasons why the test may not actually be picking up what we think they're picking up.
They have high rates of misclassification specifically for impact.
And number of studies here that are shown for you that you can feel free to look up.
The scores don't relate to concussion history.
That that signals a little bit of a problem because we know concussion history should be related to functional consequences.
They don't work particularly in fact, they work less well than self report symptoms within the 1st week.
They fill fail to predict scores on well validated measures.
They're supposedly assessing the same constructs.
There are ceiling and practice effects.
This is a huge problem.
When a test has ceiling and practice effects, as I've said earlier, practice effects basically mean that test scores will get better just because you repeatedly take the test.
So you can see that's gonna be a confound in making it look like someone's getting better.
I apologize.
I guess I'm sitting still too much here.
Ceiling effects basically mean the test too easy.
So So people are able to essentially improve too quickly.
And again, as we saw in that large data set from the study in 2023, that the vast majority of scores do return to normal pretty, pretty quickly.
SCAT, likewise, has some problems.
In fact, published studies suggest that after, 8 days at most, they really doesn't predict and that's we see this with more recent versions of the SCAT, not just the previous versions, SCAT 3, but also with the more recent ones.
And, in fact, speaking to that paper in late 2023, the, concussion and sport group made a con, consensus statement that indicates that the SCAT 6, this is for the adult and child version data, only should be used within the first 72 hours and at most up to 1 week post incident to help drive decisions.
In other words, they're not it's not considered informative beyond this period of time.
Now if if the authors of the instrument are telling you, don't use this after this period of time, one piece of advice, if you wanna legally cover yourself, don't use this instrument after that period of time since we know return to play rarely occurs within a week.
And in fact, most recoveries is expected to occur within closer to a month.
What this tells us is this instrument is not gonna help you in that decision.
And and that's a very clear con conclusion.
And, in fact, when you look at some of the broader literature, it's published both of these instruments have some real limitations, in picking up sensitivity beyond that 1st week.
So, again, this leads us to the conclusion that if symptoms aren't giving us the information beyond a week and 2 of the most commonly widely used measures aren't giving us that information.
And if these are kind of in your bundle, you've got misinformed RTP decisions.
You're likely to make premature decisions, for practice effects, return to baseline that automatically happens.
And so it looks like people are recovering essentially when they're not.
And then we can go back to that slide that shows all the problems when we return people when they're not actually recovered.
So what's the solution here?
Well, the research literature helps us here as well.
There's a really long standing literature that tells us, first of all, if you're gonna look at cognitive measures, there's a very clear place to look.
Reaction time measures that get at executive functioning are particularly effective at doing this.
And we see this this is not new.
This research dates back to in the first references I have here goes back to 1956.
They were using, continuous performance tests, CPTs for short, to, examine the presence of brain injuries.
So, over a half century ago, they were doing this.
Studies have come out using, continuous performance tests and linking it to hard measures like cortical thickness, that is associated with post, traumatic brain injury.
They've linked CPT scores on improvement over several hours immediately following mild traumatic brain injuries and also associating it with, negative, imaging.
They found that the scores correlate with presence and variability in gray matter concentration in those with TBI histories.
Specifically continuous performance test scores on things like errors of commission and detectability and variability.
They predict TBI severity.
And I should mention a continuous performance test essentially, which, the company MultiHealth Systems in Canada makes one of the more popular ones, the Connors Continuous Performance Test.
It's essentially a sustained attention task.
One of the reasons we don't, haven't seen it along this literature is because they kinda took off in their popularity to help diagnose or aid in the diagnosis of attention deficit disorder.
But in fact, those are some of the very features that we can see with, concussion.
And that's why we have this over half a century of data that's essentially repeatedly telling us these things work.
The use of CPT converges with also the consensus guidelines that I just quoted earlier because one of their conclusions is if you're gonna use a measure and you wanna get to the cognitive sequelae, your best shot with computerized measures are these reaction time executive functioning measures.
So they came to that conclusion as well, reflecting the findings in the literature.
Now one question might be, well, why are continuous performance tests so effective?
Well, one of the reasons that they're effective is they can quickly collect a lot of data.
So just as an example, the research we're going to show you from our research consortium uses the Connors Continuous Performance Test.
The full test has 360 trials and, we use that in some of the medical settings where we're collecting data.
We also have validated, a short form that has a 180 trials.
So you're collecting essentially a 180, data points on reaction time.
That's a lot of data.
Only takes about 7 minutes to get those 100 because it's they're pretty quick trials that are occurring.
Doing a lot of trials has a lot of advantages because it gives us a better estimate of reaction time.
You know, if you're gonna estimate something, the more trials you have, the more data points you have to estimate the value.
I mean, technically, I can give you 5 trials and calculate a mean on those 5.
But if I do a 180 trials, that average is gonna be a lot more accurate.
It also allows me to measure the variability in the reaction time, how much it changes.
Again, you need a lot of trials to do that robustly, to do that measure robustly, and that variability is even a better predictor than just react the mean reaction time.
So multiple trials quickly collected gives us much more robust measures.
Also, you can build in practice trials so that you can eliminate practice effects, meaning if the test data won't have practice effects in it, if you give someone a practice trial before you do the test, they'll get up to speed in that practice trial, and then you no longer see the practice specs in those remaining 180 trials.
Yeah.
And you would suspect That's what happened.
So I That's what happened.
So I'm just gonna quickly review a couple of the studies we've published already on this in the consortium, that we, that we have led.
So these are medical and sports providers that we've collected data from the first studies.
We did this was for the CPT computer, version of the CPT, the full CPT.
We had a 113 children, adolescents.
They were aged 6 to 17, and 29, were being evaluated post, concussion.
The other 84 were doing baseline testing, And they used the CPT 3 from the SportGate platform.
What they were able to do was essentially, in this research, we could predict a lot of variability in concussion outcomes with a very large effect size, Cohen's d of 1.05.
That's almost unheard of value.
These large predictive values are because you have such robust measure with a lot of trials.
By the way, these findings emerged even though the average assessment occurred more than 40 days following the excuse me, 30 days following the concussion.
Obviously, the effect sizes are going to get smaller the further out you are from the injury.
So here we're showing, yeah, you can see these effects 30 days out.
That's a really good indicator of, look, there's still some neurocognitive problems if you have a good sensitive measure to capture them.
And so this again starts to tell us, wow, if these other instruments are sort of capping out at 7 days, 14 days at most, It's not because the cognitive symptoms are gone.
It's because this the measure that was being the measures that were being used weren't sensitive enough to see them.
We did a follow-up study now looking at the short CPT.
So basically, we've instead of 360, trials, we we dropped down to a 180 trials.
They're still counterbalanced for order and amount of time following the stimulus.
Here we had a much larger study, a little over, almost a 1000 participants controls those with concussion.
So now they're getting this, short, CPT 3, with 108 trials.
It's within the support gate module.
And again, you can see again still large effect sizes.
There are very large effect sizes that are occurring, still explaining a lot of the variability in concussion outcomes.
And, we find these big effects get even larger as I alluded to in the previous day that if you look at shorter time.
And so if you test people within a week, you can explain even more variance.
Again, that makes sense.
The effects are strongest.
The symptoms, if you will, the consequence of those symptoms are strongest as you're closer to when the concussion occurs.
They taper off as you move away.
That's largely due to recovery.
But again, even here, we had an average of more than 21 days assessing people post.
So now we're talking still 3 weeks and still seeing these big effect sizes, good classification, efficiency.
The last study I'll describe, this one's using a mobile version of the CPT 3.
Again, it's in the SporeGate platform.
This is now collected on either iPhones or Androids.
They've a platform for both of those.
And, again, using this mobile device, so now you're taking the same test, still large effect sizes as you can see.
We're still able to predict, individuals' experience of those that we suspect as having concussions where we can differentiate individuals who are having more severe versus less severe consequences from that.
And we basically are replicating the same findings we found with the other, versions of this test.
Now we've continued to work on this.
We've collected normative data for this particular mobile version that involves, almost 25 100 individuals, aged 8 to 72 and, also, controlling for sex, as well because there are some subtle differences.
Now that's neurocognitive performance.
I alluded to earlier in this talk that there are some other domains where we see, concussion consequences sometimes referred to as other subtypes.
And so it turns out, gait functioning and balance are some of the other areas where we expect to see some of these effects.
So, several studies here are showing, everywhere anywhere from one to several months consequences that are associated with, balance, posture, gait changes that occur as a function of, concussion.
And it turns out that you we can do an even better job if we use sensitive, measures, think like accelerometers, sensors to pick up those differences as opposed to eyeballing them or using a stopwatch to look at things like gate speed.
So I'm gonna briefly tell you about 2 studies that, have recently come out using those accelerometers.
The, SporGait platform has something creates something called a biokinetic rep, BKG, kind kinda looks like an EKG.
Essentially, it's picking up the rhythm of your walk and it gives you outputs on power, speed, stride, etcetera.
So our consortium has been studying the effects of this, and we've studied this both with static sensors that are attached.
That's the study that you're seeing in 2023.
And then also with a mobile version where we collect the data on your phones.
You're holding the phone to your chest, and that's the study in 2024.
The short summary of this, and you can certainly peruse this in more detail, is that you can get some very reliable test findings, meaning consistent scores.
You can see our test retest reliability range from 0.72 to 0.91 with a mean of 0.8 o.
Those very good consistency scores.
If you're it's important that the individual is walking from, more from, more stabilizing or destabilizing footwear.
We also showed that in a sample of over a 1000 patients, we could use this BKG to predict concussion outcomes and that we out predicted measures like the balance error scoring system using all six stances, the cushion, the non cushion.
We could do, significantly 2 to 3 times better than that.
Could also out predict the NIH 4 meter gate test, which can get out of the NIH toolbox.
And there have been other studies as well that have shown that that sensors, to assess gate can now predict things like the NBAS.
More recently, we've collected data, normative data, again on iPhone and Android phones of over 4,000 individuals to collect normative data and test retest reliability on mobile device for the BKG for the gate task.
And, again, you can see some very high figures there, 0.79 for measures of stride, power, symmetry, and balance and normative data of close to 25100 individuals stratified by sex and spanning 8 to, to 72.
What's critical here is the amount of information that's being collected in a very short period of time.
So when you take a walk holding the phone to your chest, and the sensors on the phone are picking up, you know, again, speed, power, balance, These are tens of thousands of data points that are being collected every second.
And so in just that brief 10 second walk there and back, there's a lot of data to be analyzed and used just as I referred earlier to the multiple trials that we get from the CPT.
So the advantage here with this now mobile assessment is getting a lot of data in a very short period of time.
So a couple of critical take home points then as you consider your work.
On average, we know concussion symptoms tend to return to baseline within 7 days.
Not necessarily meaning people have recovered, but just that symptom sensitivity kind of expires in that period of time pretty consistently.
Research, though, tells us consistently that our recovery is probably closer to a month.
And so I want you to start rethinking not as we often do now, which is, wow, if someone's out for a month, why are they out so long?
We should actually be thinking about this in another way, which is if we're returning someone in 1 week, you should have pretty darn good reason for doing that because that's really atypical.
That's not what the data tell us most people recover in that timeline, even though that might be when many people are returned.
We also know that some domains are even more sensitive in terms of some longer recovery.
Neuro motor functioning is one of those domains.
So when you're assessing things like gait, it gives us an even better assessment.
Cognitive functioning also can capture longer periods of time if you use the right measures.
And, again, from the concussion and sport group, they're telling you, look, reaction time measures that get an executive functioning.
That's the that's the golden nugget.
That's what works best.
And so, obviously, tests that have a lot of those trials where you can get not just a robust estimate reaction time, but it's variability.
And we wanna use this information across multiple domains.
I wouldn't encourage you to take a liberal approach of, you know, the best measure, but really look at some of the weak links, you know, to make sure that individuals have recovered.
And part of the strategy is pay attention to symptoms that 1st week to keep people out.
When the symptoms go away, turn your attention to those objective effective measures.
That's how you can do clinically sound decision making that's gonna be legally supported, legally justified, help protect you in that way, and it's supported by the literature.
So hopefully, that's a helpful way to consider the use of these data.
Obviously, a big part of this, work is that science is not a period.
It's an ongoing sentence.
We are still doing lots of research, collecting lots of data.
We got papers in the works.
And we believe that science will always lead us, will always be heading us in the right direction.
One of the areas that we've identified recently as a bit of a shortcoming is a lack of representation of minorities and female, athletes in a lot of the, instruments that are used to essentially evaluate their recovery.
This is a pretty big limitations.
In fact, we reviewed 11 norm studies published over the last 20 years of some popular measures.
Males represent about 75% of the data.
So females are largely underrepresented there.
And the non majority group members in terms of racial composition also very underrepresented.
In fact, in those 11 studies, norm studies, there were only a total of a 127 subjects that were racial minorities.
That's it all across all 11 states.
So, clearly, we know a lot less about recovery trajectories and just normative values for females and racial minorities.
So we were, fortunate enough to receive a grant, through the University of North Carolina Wilmington, where we applied through, to the Chuck Knoll Foundation and also the TB 12 Foundation.
And essentially, we're targeting, populations that have more diverse norms.
So if you are working with, sports organization, for example, or medical practice where you have good minority representation or a high rate of female athletes, please do talk to, some of, the representatives of, Sportgate.
They are, part of this study.
And so we have an IRB approved, research that's already ongoing.
We would love to have you be part of that research project.
Thank you very much for your attention in this presentation.
And if there are questions, they can, certainly be fielded by some of the representatives.
You can also email me, and I'd be happy to, address questions as well.
You have a wonderful day.
Thank you.
How the Selection of Objective Measures Drives Time to “Recovery”: Improving RTP Decision Making at the Front End
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