Okay, so I'm going to keep rock and rolling because I'm getting myself behind, which I don't want to do. We're going to look at some challenging cases and some weird stuff and how I deal with this. As background, when I do federal black lung evaluations, which always includes spirometry, and the question is, what do I do when somebody has an anatomic difference, and how do I address that in their spirometry? And we'll kind of go through a bunch of different options here and things I've had to figure out. You may decide to do this in a slightly different way, but this is the way that I have figured out to do it so far. Okay, first thing we're going to look at is somebody has had a lobectomy. They come in, they say, hey, I had a, they diagnosed a lung cancer, it's a cold minor, got diagnosed with lung cancer, they did a lobectomy, that's all his treatment was, but he's missing a lobe. How do you interpret their spirometry? That's my question. So, here's their spirometry. I wrote down on the edge because they, unfortunately, I wrote down the percent predicted on the edge because we're having some computer problems, and we, so the guy had his lobectomy, and what I've got now is an FEC of 65% predicted, and it is less, and it's less than the lower luminal, I can't touch the screen. And then he's got a FEV1 that's less than, that's 57% predicted and a ratio of 63%. So his, when I look at this initially, I go, well, his pattern would be restrictive. Now if they've taken out a load, that kind of makes sense. And so my question is, is his spirometry abnormal post-lobectomy? So Carl goes into the literature and tries to find papers about this. And this was his, these were the curves that went with that, because everybody, whenever I talk to, if there's ever a pulmonologist in the room, they always want to see the curves. Numbers don't got it, you got to have curves. So this is where I went into the literature, and so there's a couple of different articles I looked at. They both looked at people, they did, in some places, they were doing spirometry pre-surgically so that they knew how, what the surgical risk was of the patient. And so they're doing that, and then they went and they said, okay, a year later, we'll check them again. And because I wanted studies to, I don't want to know what there were two days later. I want to know what they were, well, I mean, they're not coming to see me while they still got staples in. They're seeing me, you know, a long time later. And so they found about a 15% decrease in both FEV1 and FEC. That's the first paper by Dracul. The second paper, they also, they found about a 15% decrease in FEV1. Okay, so 15-ish percent is the decrease these guys are finding when spirometry, when you take out a lobe. Fun fact, it doesn't matter what load they take out. They're all the same. They're all about 15%. And this is a different article than this one. The first two were looking at what I'm going to call conventional surgery. This one's looking at this video-assisted thoracic surgery or VATS, and they did it, they wanted to see if they were better. So when they did their studies, they found, if you look at it carefully for a lobectomy, about a 20% decrease in FEV1 and FEC. I'm not sure if that's better, but anyway. And so they did this, but the one thing they didn't, they compared themselves to like other lung procedures, but they did not compare themselves to normals. So I don't exactly know. They didn't do just a population of normals, so you can say, well, okay, normal was this and they were a little different. So what I calculated here is they figured it out to be about 20% difference for a lobectomy. You can do a lot of things with those three sets of numbers. You could divide them, you could add them together, you could say it's 17 and a half, you could put 15, you could put 20. What I did was I used, it's 15-20%, that's pretty solid between those three studies. The ratio should not change. So the ratio, you don't have to adjust the ratio ever, but you may have to adjust the FEV1 and FEC. And I recommend using either 15 or 20%. I use 20% because it's the most conservative. If you kind of think about the way the math works, it's the least likely to make the person look bad, look abnormal, which is where, because I, invariably, we're going to end up talking to lawyers about these things and getting deposed. If I do something like this, and I want them, I want it to be the most defensible when I talk to the attorneys, okay? So I use 20% for a lobectomy, and what I do, and I'll show you the math in just a second, is I adjust the predicted values, I never change their actual value, I correct the predictions. So I can correct the percent predicted, I can't, I'm not smart enough to predict, to correct the lower limit of normal, because that's statistical, and I'm sure somebody could do it, it's not me. But I will fix, I can at least give them an adjusted percent predicted. The other thing I can do for my black lung guys, because for them, I have a chart. It's Knudsen 83 at 60%, but I have a chart. I can do this math to those values, and take, you know, take, divide by 0.2, and make those numbers a little bit less, so that it'll, and then figure out if they're still bad enough or not. I hope nobody wants me to work through that math. If you do, it's written, how I did it, it's all written there, out there, go look it up. So the next thing I want to talk about is people who are transgender, and I'm going to start this with a case, and I said before, this is, this is why I said, just hold on for that, we'll, I'll get back to that in a minute. So this is, this is somebody whose spirometry was done, and they, if you look at the bottom, the results show a mild restrictive pattern of impairment, indicated by, and then please ignore the rest of it, because it's horribly written in English. And so mild restrictive pattern of impairment is the key part to take home. So they mentioned to you, to your nurse that they're trans, that they're transgender man, and they had used, because the guy, the person came in with a beard and everything, they'd use the M category. And so let's talk for just a second about transgender individuals. So gender and gender identity is how the person's, their internal sense of being male, or being a man, a woman, or something else. Gender expression is how they present their outward appearance. Sex is male or female or indeterminate, and it's based on constellation of physical symptoms and physical findings, and is, we used to use the term biological sex, now they use the term sex assigned at birth. And transgender is when somebody is, somebody's sex assigned at birth and gender identity do not agree in the usual way, okay? I think I've got all the wording correct there. Tiptoed very well. Thank you. And so these are, these are the vocabulary we're going to use here. It's about 1.4 million adults in the United States, which is a bit less than 1% of the population currently. So as of right now, all spirometry predictive equations use gender as a key determinant, or sex. It depends on what they, what word they used. So incorrectly using the male equation may result in the power of restrictive disease, and if you incorrectly use female, you may miss disease. So that's the concern. ATS, and this is actually true up through the one that just came out a couple weeks ago, recommends using sex assigned at birth or birth sex for spirometry. NIOSH actually is more nuanced in their recommendation. And so that's actually probably okay if the people did all of their gender transition things after puberty. But for people who did their gender transition things, and what I really mean there is medication, not puberty, it's different. So the recommendation, the big key question is, what was their hormonal status at puberty? If they went through puberty under the influence of estrogen, they're going to have female sized lungs. If they went through puberty under the influence of testosterone, they're going to have male sized lungs. Does that sort of make sense? Do you have data to support that premise? Yes, a little tiny bit, because there aren't very many people today who were adult enough who went through puberty as a different gender. But it's literally, it would not yet be a case, it would be a case report. It would not yet even be a case series. Now some back, because a lot of those people are still very young. And those people get into their 20s and 30s, then we're going to have real data. There is, I hate to say it this way, sort of a registry of people that are, people are aware of this issue, and their data will be collected as the people get older. You had a question? I was just wondering, extending that thought pattern, if someone went through chemo at a young age prior to puberty, then they would have possibly the size of a lung or somewhere a different type of birth. The question was whether chemo would have a similar effect. And I would say the, I don't know the answer to that question. It's an interesting question. I don't know. I've not looked into that yet. Maybe that'll be the next, the new segment on the end of this thing a year from now. Absolutely. Yes, another question. Some states it's illegal to do any reassignment before the age of 18. So the question was, there was a statement, some states it's illegal to do gender reassignment before the age of 18. That is true. This has nothing to do with surgery. This has to do with hormones. I understand what you're saying. I'm telling you what, I'm not, I'm not worried. I'm not worried about that issue. Not my issue. All I'm saying is if they went through puberty under testosterone, use male. If they went through puberty under, under estrogen, use female. That's the take home message from this. Another question. You're correct. This is the person in front of you. They can come from any location. We're just dealing with the person in front of you right now. Yeah. I'm not worried. That's a political thing. It's not a medical thing. I'm talking about the medical part. Asian phenotype. I understand. What do you mean by Asian phenotype? Well, last I studied genetics in the human being, there are basically two types, XX and XY. Matter of fact, what we do is in our office, we go X, X, Y, O, circle two. We ask the person, what were you born? Okay. Okay. So what, what I'm saying is I'm trying to be more nuanced here and give you interpretable spirometry results. That's all we're talking about spirometry. They went through gender. They went through puberty as under testosterone, use male. If they went through test through puberty under estrogen, use female. That's our current recommendation. Come back to me in 20 years when we'll actually have tables. We don't have tables yet. Yes, sir. Before you go, wouldn't it be helpful to run the test the way you're saying and then run the test as well as what they're assigned just to compare just for you? Well, it's going to change the normals. Only it's going to change. So you can, you can compare if you want to. Yeah. And, and, and if you, if you get a large enough population, please publish the one thing is it's for our tree and kids is, is complex. They don't have, as you're well aware, if you've ever been to a middle school, there are kids at the middle school that look like they're, they look like they're four and there's kids at the middle school. It looked like that looked like they could try out for the, you know, the, the, the basketball team there for the NBA. So, so during youth, youth, youth ishness, spirometry for you to the spirometry is very difficult to have normals for what they typically do when they're treating people is they use that there there's, there's something about height. So height will help with that, but doesn't, isn't perfect. And so they often will follow, compare that person to themselves much more fastidiously than we do in adult medicine. Okay. So we had the discussion with their, the patient, they are transgender man, but they started hormonal therapy after puberty. So they went through feed, they went through puberty under estrogen. And so we say we should compare them to the female normal equation. And then I have them read, redo this and set that to F okay, rerun the report. And now they come back as normal, which is great. One little tiny thing you got to remember here is confidentiality. Okay. So if I have to share this with the, with the employer, I may have to get out my I may have to find a way to make it look like they're still male so that I don't out anybody who didn't want outed with their employer. Okay. Just be thoughtful of that. Cause if you send that back to the, to when they send, you know, Bob over to get his spirometry with a big beard and they get back to the thing that says female, there's a, he screwed this up. Why do you send me Bob's results as female? And so you don't want, you don't want to ever have to answer that question. So just think about how you're going to correct the report. So it, so that it's both accurate, medically accurate, and not outing anybody that doesn't want to be outed. It wasn't an employer, it's the care adaptor. Just wipe it all out of a scratch, you know, they don't need it at all. There are lots of things you could do, but just probably don't send it back with their not, they're presenting gender. Why don't just have the patient worker not bring satchel on these? That's cause that's, that doesn't, it depends on the arrangement between the employer and the medical office. Cause a lot of places they say, you need to go to your spirometry. You're in the blank standard, right? You can't not release it back. If the employer has a way to manage it. Not all do. It depends on the standard. But I'm just saying, and some of them require the employer to have it and some of them don't require the employer to have it. That's why this gets a little fuzzy. Okay. Let's go to the next case. I want to talk for a second about obesity. I'm going to try to go fast with this because this is one of my favorite ones, but I've got way too many slides and I get lost in this one. So person comes in for black lung exam, the never smoke or BMI of 32, FEC is 54% predicted, the ratio is normal, TLC is reduced at 56% predicted and their, their ILO and their ILO finds a one, one QQ x-ray. So they don't have large capacities. And I said they have black lung disease manufacturing as restrictive lung disease. So far we're pretty normal. The company doctor wrote back to say, all of this barometry abnormalities are because of their obesity. I don't think that's a problem, but let me look. And that there was no contribution from their coal mine dust exposure, had nothing to do with it, despite the positive x-ray, but we'll not worry about that for right now. So I went back to the, to the literature. My question was, how can I fix this? Like is there a correction equation or a way I can correct it like I did for lobectomies? And what impact does obesity have and how big are they? So unfortunately this goes back a long, long, long time, back to 1810. And they talked about a guy who kept falling asleep while the doctor was talking to him. This is, this is, you know, this is from, this is back when you wrote in a letter to the journal about a patient you had seen and they would publish them. That's where this came from. In 1956, Sidney Burwell identified, documented this thing that he called Pickwickian syndrome, which we've all probably heard about in medical school. This was well discussed. So this person was described as having an increase in birth by loss of respiratory reserve that increased, when increasing stream, it may lead to a state of relative ventilatory insufficiency. And you can also see this in pregnancy, in later pregnancy and with ascites. They're the other two medical conditions besides obesity. And they listed all these things at the bottom. You have marked obesity, somnolence, twitching, cyanosis, periodic respirations, secondary polycystemia, RV hypertrophy, and failure, right? That's, that's, that's actually okay. Came from literature. It was in something called the posthumous papers of the Pickwick Club, and they were describing a guy named Joe, who was described, if you look, if you read the thing, and I will admit, I've only read pieces of it. He apparently would fall asleep while knocking on a door. Like he would start knocking and then fall asleep standing there. They also called him a lot of other names relative to his somnolence. Yes, young opiometer and young dropsy. Anybody here ever diagnosed dropsy? So he was, he was, he was short and rather obese. This is Burwell's case report, not the guy, not Joe from the book. Five foot five, 263 pounds, which is a BMI of about 43. He was florid, which I had to look up, means he had a red or flushed complexion, cyanosis of the nail beds, but no clubbing, and he would fall asleep in the middle of conversations. He was hospitalized on a strict 800-calorie diet, because you could do that back in 1956. Whoops. And they, for whatever reason, they must have just gotten a spirometer at the hospital because they kept testing him. And this is the, this is the data they reported. So as he lost weight, his, the things they've got there are, we've got his weight, his mitochondrial capacity, that's FEC, right? Which went up a lot, because it was like, I don't know, 1.4 liters or something in that bottom one over in that, I'm sorry, that top one over there, maximum breathing capacity, alveolar oxygen saturation. I don't know how they did that in 1956, but they did somehow, arterial CO2, tension. And you can see that over time, he lost, his BMI went from about 43 or 44 to 38 while they had him hospitalized. And look at how much better he got. The key thing to keep in mind about this is the N is one, okay? This is one guy. It's not even a series, it's one guy, okay? And what this guy really had was obesity hyperventilation syndrome, that's what we would call it now, right? So, which is, the way I think of this is it's really bad sleep apnea, so bad that you screw up your blood gases while you're sleeping, and then they can't correct during the day. That's really what, what, what obesity hyperventilation syndrome is. These are the diagnostic criteria, and as I said, that's my summary kind of at the bottom. So, that's what we call this today. CPAP fixes this very easily, or CPAP or BiPAP or some top thing. And so, this is now a correctable, treatable medical condition, okay? I went back looking to—so, one of my questions I was trying to figure out was, so, how—what does it really impact? What lung function tests are impacted by this condition? And so, thankfully, Dr. Sud out at the—out in New Mexico has done some studies of this. And so, things I expect is vital capacity normal or maybe a little decreased. The FEC—I'm sorry, the FEV1 normal or decreased, the ratio is normal increase or decrease. That's like—that's a crapshoot, right? Or the total lung capacity will be normal or slightly decreased, okay? So, I'm not necessarily—it's not like a death sentence. And this is kind of a summary thing. So, let me just mess off. Hold on. Okay. So, this is one of the tests. This is one of the papers—the other papers I found. They compared pulmonary function tests before and after bariatric surgery. So, this is not going to be the people with a BMI of 31. This is going to be people with significant BMI increases. And so, if you look at their pre, the residual volume and TLC were basically normal. The functional residual capacity ERV were a little bit abnormal. So, those are the key take-home points, is the total lung capacity was 93% predicted before. So, I shouldn't see restrictive disease, right? And it got better, like better than normal after the surgery. The NHANES data—I went back and looked at the original paper, and they looked at height and weight, including them in the equation, and they found them to be—height and weight were similar in terms of improving the R-squared with little improvement if they used both. So, they used height because it's easier to measure. Yes, sir? I'm just wondering about lung capacity. What about these morbidly obese upper centers? They have normal lung capacity. It doesn't get smaller. That's what this says. These are people getting bariatric surgery. It was 93% predicted. That's normal. Yeah, I mean, so, the total lung capacity doesn't really change. I don't—yeah, maybe they've got more—one of the things you'll notice in just a second is the FEV1 does go up, so maybe they've got a little more oomph to push the air out, reach that high C, or high A, or whatever, you know, those high notes. Okay, so, what they found was that most of the people for pre-bariatric surgery had normal spirometry, lung volumes, and gas exchange, and they didn't find any relationship between body size and spirometry. Keep going on. So, now I found a different paper where they looked at spirometry compared with BMI. So, what you'll notice across the top is BMI, and then they looked at the various things. So, if you kind of look in that 30 to 32 range, the vital capacity is 92% predicted. There's a slow decline in vital capacity. Total lung capacity declines slowly. Now, the exhaled residual volume, the ERV, towards the bottom, it goes way down as you gain weight. It's one of the lung volumes we don't use very often clinically, but it's one of the things they report. It does change with body size. Interestingly, DLCO, the fatter you are, or the more obese you are, the better your DLCO is. Not sure why, but that's what they found. Maybe you don't move as much air, so you're more efficient at getting it out. I'm not sure. So, the thing I look at is these things are normal when I'm doing my—so, the ratio should not change, and the DLCO shouldn't change. That's not an impact of obesity. There is some decrease in the vital capacity. There is some increase in FRC and ERV as you gain obesity. Yes, sir? On that chart, the normal weight category still wasn't 100%. I mean, it's— Correct. That is true. So, the comment was that the normal—that the people in the normal weight category were not completely normal, and I would expect that. I mean, they're almost normal. I guess 2.5% of the total. Well, I mean, still, it's 97.8% predicted. That's pretty normal. It's a comical variation. I mean, yeah, that's just variation within a dataset. I'm not—to me, that part is normal. And if you looked at the—officially, the left-hand side, the 20 to 25 would be not the normal range, right? And some of them are a little below normal. Some are a little above normal. I think that's okay. Keep in mind, weight is not one of the variables in the equation, so they don't consider that. So, obese people would be part of your normal set that you use for predictive equations, if that makes any sense. Okay, different study. And here, they looked—this is where they took data over time. This is a meta-analysis, and they were just looking at obesity in pulmonary function tests. So, two out of four studies found the vital capacity to decrease. Four out of seven found the FVC to decrease. So, when two of them decreased, they disagreed between FVC and VC. In the United States, we almost exclusively use FVC, so it's a forced maneuver. In Europe, they'll often do a VC as a separate test, where you just blow as long as you can without the forced part at the beginning. The reason that they use that test is some people with bad lung disease do a good VC, and they can't do an FVC to save their lives. So, that's why they do that test as a separate maneuver in Europe. They still believe in the FEV1, and you need the forced maneuver to get the FEV1, but you don't need it—if you really think about it, the forced part at the beginning really doesn't add anything to the FVC. You can do a VC, and it's just as good. My point is that this actually—so, what we've got here, if you look at this, for the forced vital capacity or vital capacity, there's no reliable change. It's the same, pairing obese to non-obese. I mean, two out of four greater, which means two out of four less, right? Four out of seven, which means three out of seven went the other way, and then two studies actually disagreed with themselves. So, there's no reliable change based on obesity. The FEV1 did show a little bit of a decrease, at least six out of nine studies. It's better than half a little bit, but still not a reliable change. So, Piquicain syndrome really does exist, or I should say obesity hypoventilation syndrome really does exist. It is readily treatable now. Obesity in and of itself does not really cause any changes that are clinically significant until you get over a BMI of 40. If we get over a BMI of 50, we'll definitely talk. I'm willing to accept that a BMI of 50 is really going to cause an impact on somebody's pulmonary function tests. A BMI of 32 doesn't do anything. The BMI of 32 doesn't do anything. So, back to my case. So, my conclusion was that the literature really does not support any visible impact of spirometry on the BMI of 32, and certainly would not be the cause of his having an FEC of 54% predicted. It might have something to do with a coalmine dusty breathe in. Next. Any questions? So, do you ever interact with the company physician and just ask his data set and why he said that? Just curious. Oh, well, A, I don't get to ever talk to them directly, and B, they're probably going to go back to Burwell. Curious. Yeah, a lot of it is to say, well, the literature says that with obesity, there's a decrease in FEC. That's as far as you get. Most of them, they tend to fall apart pretty fast. And 32 BMI isn't that bad as obesity. No, 32 is about me. If you're a doctor for us in Brazil, an obese person, they'd still give you 32 BMI. Correct. If you want to look at the obese version of that, 32 is about my BMI. So, it kind of gives you a vague idea. But it's not the wider than tall. That's a bigger number. So, from the health side, I don't do black lung, but would OSHA look at black lung the same way they would as hearing conservation? Meaning, if he's in the area where he most likely has contact with coal dust, regardless, it would be suspected that or assumed that it would be from coal dust. The question was, would it be assumed that the coal dust had an impact on his lungs? And actually, it depends on how long they were mining. The law is 10 years of coal mining, 10 years the way the government counts, coal mine exposure, there's a presumed exposure to dust. At 15 years of coal mine dust exposure, there's a presumed that whatever's wrong with your lungs, the coal dust impacted that. It's actually in the law. It was in for a while, and then it was out for a while. Then it actually came back in in Obamacare, and it's still there. Those presumptions, they're called the presumptions in the law. Okay. So, now we're talking about pneumonectomy. And so, I had a patient who came in and had a right pneumonectomy for lung cancer, and I'm still trying to do his black lung exam. How do I fix this? I'm seeing him about six years later, so he's well out of the perioperative period. And his chest X-ray is a 1-slash-0 QS. So, it's a barely positive chest X-ray. Two different things that are going to happen to this guy. One is, when you think about it, as you take a chest X-ray and you expand the amount of space that that lung gets to occupy, perfusion will go down because things can space out again. I don't know that you can see that that much in somebody that's had just a lobectomy, but in a pneumonectomy, there's a whole lung missing. It's going to spread out a little bit. So, he may actually have had a little bit more black lung than we could see. I'm just adding that. So, how do I figure out his pulmonary function test? So, back to the library. Okay, the online library. I only found one good article about this, and the problem was a lot of studies did preoperative spirometry and then discussed surgical outcomes. But I couldn't find very many that then went back and did a postoperative one. Found one. And what they found was about a 41% decrease in FEC for right, and about 34% for left pneumonectomy, and similar changes in the FEV1. And that makes sense because you've got your right lung is bigger than your left lung because the heart's in the way. And I did similar math. I go and I do the same thing as I fix the predicted equations and fix the cutoffs. I don't do, that's a lower lung than normal because that's above my pay grade. And so, at the end of the day, this guy ended up with, so I ultimately end up saying I think that he had a normal pattern based on the corrected expected lung volumes. And I mean, so it's 65% predicted I think was expected having had a lung removed. So, I did not say that this was restrictive disease. Okay, next case, stroke. So, 80-year-old male, you've got a 32-year-old mining tender, never a smoker, some moderate left hemiplegia, uses a wheelchair. He's rather deconditioned but cognitively intact and cooperates well. Did take three of us to get him up onto the stool to take his x-ray, his chest x-ray. So, here's his spirometry and you'll notice he's got a pretty decreased FEC and FEV1. Here's the curve because you always have to have curves and they are, you know, they show good effort. I don't see any major problems in the curves that worry me. I went back to literature. There's essentially no literature on stroke and spirometry. The problem is strokes are a non-standard event. We took out a lobe as a standard event. You had a stroke as a non-standard event because the impacts are all different. There are a bazillion scores to classify strokes that are hard to use. They're all for research purposes. There's no easy system. There's not like a GCS, tell me these three things I can classify the stroke. And there are some articles where they looked at rehab after a stroke and they'd look, use spirometry as a marker for that. We're going to do, you know, arm movements and see if their FEC gets better or whatever. All they did was ever compare that person to themselves. They had a 7% improvement or a 2% decrement. They never compared them to anything else or to a population and you didn't have pre-stroke values to compare them to. So there's no literature there. I found one study. I don't know what to make of it. The standard deviation is greater than the difference. So I don't, it's, they did what they could with the numbers they had. But I can't, I can't tell you anything about what was going on in that person's lungs. So for me, stroke is a crapshoot. I don't know how to fix it. I don't know how to interpret their results because it's just all over the place because strokes are just too variable. That's, so that one I didn't, I don't have a recommendation for that. Last one I think is Parkinson's disease. I might even be done on time. I'll make, pick my time back up. So Parkinson's disease, I, this is one I see not infrequently. And as you, as everybody I'm sure is aware, Parkinson's disease is a disease that ranges from, I have a little bit of, a little bit of cogwheeling and nothing else is really wrong to people that are wheelchair bound, bed bound. It's got a whole spectrum there. And so the basic problem is this function of the chest wall muscles and how well they're working which can limit forcible respiration. You're thinking of both weakness and rigidity, which, which makes the FEC more difficult to do. I can, sometimes it can impact testing. And I learned, I didn't know this. There's a thing called the H and Y scale. We're fine. There's an H and Y scale that's a way to assess disease severity that is used in research all the time for Parkinson's disease. And it's simple enough. I can understand it. So you can, you rate the people anywhere from one to five on the severity of their disease. And this is backed up by a really cool study where they did spirometry. Okay. And so this is for, and each of these ones, like if you look in just the upper left-hand little graph, so H and Y one down through H and Y five. Okay. So I'm going to go back just a quick second here. I'd mentioned that my guy was in a wheelchair and it took three of us to get him up onto the stool to sit on the stool to get his x-ray done, his chest x-ray. Okay. So just, so that's the level of function. He can't, he's wheelchair bound. He can't stand and he can't, he can't transfer on his own. Okay. So my guy was an H and Y five. Okay. Now back to this graph. So I can look at the values here and they've got vital capacity, FEV1, and I can, I zoomed into the one for vital capacity. And so they found the mean difference between a one and a five, whoops, I hate this. I hate touchscreens. Anyway, to be 1.64 was the difference and that's in liters. Okay. So I can just do a little math and I can divide the original value by the new expected value. And I say for him, I expect the FEC to be about 55% predicted. FEV1 about 56% predicted just based on his Parkinson's disease, having nothing at all to do with his coal mine dust exposure. And the ratio should be about normal. So his lung volumes were actually a little low, but not horrible bad. Just a little low. And my question is, is this okay? So I did my math. This is how I did the math to figure out that I would expect him with an H and Y one to have about 47% of his FEC remaining. His, so my, I, so expected percentage, I made 48%. And this guy was right at 48%. So we're, we're fine. He did not have restrictive disease that I can say based on the spirometry, because the predicted, the, the expected change from his Parkinson's is exactly what his expect, what his showed out to be. Yes. Do you remember approximately what year this article describing the original H and Y? H and Y, the H and Y system is old. I never, I didn't go back to the original article. This is, I got the, I got the descriptions actually from the nursing literature because they, they, they use it a lot, but they're okay. It goes, you know, when you look at the statistical aspects of it, they're conflagrating both endocortile ranges, which you refer to medians and means, which are referring to continuous data. And you, thou shalt never mix modes like that. That's a fundamental law of statistics. You can't do it. You'd be surprised that that got published, period. Nobody should have caught that. I don't understand the question. What I'm saying is when you have continuous data, you use mean, median, okay, use mean and standard deviation when you're having other things, when you had a, if you look back at the slide, the word, the left most columns there are referring to things that are dealing with endocortile ranges, not, you know, medians. When you have whisker plots, you're dealing with a different type of data. I invite you to write to the author. I, I, I'm not able to, I'm not able to take, I understand the question. I'm not able to answer your question, but what I was looking for was anything that would help me understand spirometry. And that you may be right. There may be a statistical problem. I don't know, but I'm going to accept that is okay for the, for my purposes as a simple document doc, who's trying to under who's trying to fix spirometry for somebody with a pretty profound. Neurologic disease. So, okay. So, so he ended up, he was as expected. So he was, he was actually, he was fine. He was 50. I expected 48. He got 55% for the FEC. I'm good. He did. Okay. Any questions.

spirometry

anatomical differences

black lung evaluations

lobectomy

pneumonectomy

obesity

transgender individuals

Parkinson's disease