CV Update: Dr. Hartman Refutes Drs. Erickson and Massihi's Claims

You. It's great to be with everybody this morning. Before I get started, I do want to start with a basic apology. I usually don't put out responses to direct individuals or articles or things like that that are more on the social media or pop culture kind of event. But I've just had so many patients ask me specifically about this interview with Dr. Erickson and Masihi. To the extent that I feel compelled to have some kind of response. I did watch the video and to be honest with you, I wasn't able to go through the whole thing because I got a little upset. So I'm just had to calm down a little bit. So this is my calm thing. But I want to apologize in advance. This is going to have some bias in it. It's going to have some opinions. I try to just put out facts and information and let people interpret for themselves. That's part of our value here at Richmond integrative functional medicine is to educate, encourage and empower. And so I try not to give you my opinion. I try not to say this is what I think and do it in a fashion that that affects people's thoughts. I try to inform people. We all have bias. We all have our own bent to things and that's impossible to get around because we're humans. But I try my best not to purvey my biases as I educate people. And so this is gonna be a little different. I'm gonna be sharing my biases a little more directly. So I'm gonna apologize in advance for that. To all those who are my patients who see me in the office, as well as to those who follow me on social media. So basically the doctors Erickson and Masihi, there are some urgent care physicians, prior ER physicians in California that basically want to go back to work and they posted their opinions. And so I just want to begin with a statement from American College of Emergency Physicians. So this is the group that represents pretty much all the ER physicians in the country. And they came out strongly against these two guys video as well as their information. I'm going to actually post that below. I don't want to read that to you all because you all can read, but it's just really, that's how bad this. This kind of is literally a national organization of ER physicians feels compelled to speak out against this misinformation. That's kind of how bad it is. So. And there's statements that gonna be actually a little more biased than my statements. So I think my. So I have a couple, I have Seven or eight points I want to go through. Nine points, actually, I want to go through. I could literally talk about this for hours because that's how much fodder is in there. So my first, the first thing is just the general misrepresentation of the facts. Any, any research article, anything's going to have bias. But the goal is to actually go through the bias and just tell the facts as best you can. You know, saying that, you know, this is the worst event in the last decade. This is the worst, worst event in the last. This is a black swan event. This is something that into last year, I mean, my wife talks about. I've been telling her since we've been married that I'm expecting a pandemic because we usually get these every 30 to 50 years. So, of course, I've been expecting this for the last 10 years. So is the American College of Immunology, the ILADS. I mean, all these organizations have been expecting this. But it's one thing to say you've been expecting something and two to say, well, to describe it as a uncommon common event. This is a black swan event. And we have nothing to compare with this. So we have to be careful when we make comparisons because we literally have nothing else to compare. Shutting the entire world economy down, you know, asap. And so the response has basically been a pretty severe response based on our fact that we thought we would have 8.4%, maybe 11% mortality. And that's what we had with data that was misrepresented to us from China through the World Health Organization. So, yes, this whole thing started with a massive misrepresentation. The data today says mortality maybe 0.6, 0.7, as high as 1.4, probably closer to 0.6. It's still worse than the flu. And we'll get to some of their data below for those who want these. I tend to also as well put articles and put references to all the stuff. I say I'm not doing this because this is an opinion piece, but if you go back and look at our videos, all the data points, I have articles. And that's one of the things as well. With this piece they did. There were no articles I saw attached saying these are. It was just basically a piece of paper with someone saying, this is what I think. Well, this is what I think. I mean that you can't make public opinion or policy or public health decisions based on that. You need actually people to be able to digest and chew up the data. So I think the first misrepresentation is. This is like nothing we've ever seen before. So we're going to stumble, we're going to fall. Anytime there's a disaster, the the government messes up, localities mess up, physicians mess up, that's going to happen. When you have an event that no one's ever seen in the history of the world before. And that's what this is. This is not a once in a lifetime event. This is not a once in a decade event. This is a once in the history of the world event that we've never seen ever before. We have to keep that perspective. We have errors, we have mistakes, we have to minimize the effects of those errors and mistakes. I think that's a better perspective. The second misrepresentation is. That was pretty big. The sheltering place suppresses your immune system. No articles were quoted. How does sting in your home for a month suppress your immune system? That's my question now to think about as a functional medicine practitioner. Yeah. If you're in your house and not going outside, you're exposed to a lot of chemicals. There's a thing called sick building syndrome where the off gassing from VOCs from the walls can suppress your immune system. Yeah. If you're not outside, you're not making vitamin D and vitamin D is important for your immune. But there are reasons for sheltering place making you sick, where you're not getting exposed to things, which is a. I'll talk about logical fallacies here in a second. But it's a pretty huge misrepresentation that if you don't go outside, you're going to be immunosuppressed, immunocompromised without any data. The second. Yeah, the second misrepresentation. The third misrepresentation which is going to happen was that there's going to peak. This is going to be. This is an interesting one. When we get out of the shelter in place, everybody agrees there's gonna be a spike in the number of cases because New York City, 22% of people have probably gotten this to date. But the rest of the country it's maybe 2, 3, 4, 5%, some places less because they're not population centers or hubs. That's the reason we need to test as they get that incidence to figure out how prevalence or how prevalent this thing is. So we all agree there's gonna be a spike once we go out? They said, no, the spike's going to be because our immune systems are so suppressed from sheltering in place. That's a massive misrepresentation. That spike is not going to be from all the Americans having suppressed immune systems, from, you know, gaining 10 to 20 pounds, drinking too much alcohol, which are all bad things which are happening. It's more going to be because that's just how infectious diseases work. If you pull away, you flatten the curve. Once you go back out, you'll see a spike again. And everybody's been talking about that. That's not new information. The fourth misrepresentation is that 6.5% of all their patients tested positive in their sample size. That's a huge thing. It's a selection bias. Now, I didn't talk about bias. One thing I want to mention really quick is preconception bias. And what the preconception bias is, is if I believe kind of mostly what you believe, even if you say a bunch of things that are wrong, I'm going to generally agree with you because, you know, on the same political party you're in, and I kind of sort of agree with you. So I basically jump on your bandwagon. Even though you might say a lot of wrong things, whether it's Democrat or Republican. This is a huge preconception bias where probably, you know, this is a very become a political thing. We have a 40, 40, 47, 53 split in our country. Left, right, up, down, inwards, outwards, whatever. You know, however you want to divide us, because that's what people like to do these days is divide us. So basically, if you. If probably half our country is ready to go back to work and we say, I think we should go back to work, the preconception bias is, well, there. I'm gonna therefore agree with everything else you say, and I think we need to be careful about that because I think that's one of the reasons why this is kind of going viral, is because a lot of us say, hey, it's time to get back to work in some form or fashion, not open the floodgates. We need to maybe do like Sweden has done, which Sweden has kept their sick elderly people away from the younger people. And that was not mentioned this at all as well. But. But the kind of bias that they have here is a selection bias. At their urgent care center right now. People are not going to the hospital unless they're sick because they're scared. It's really hard. Our office has been open, We've been doing lots of telemedicine. People are scared. So in an urgent care place where people are scared that are going to and they're collecting data, you only get the People who are sick enough to feel like they need to be seen. So that's kind of a selection bias. And yes, 6.5% of all their patients are testing positive. That does not mean that 6.5% of the entire state of California is going to test positive or their county is going to test positive. That's a huge selection bias. You can't apply stuff like that. Their error is actually the exact opposite of the World Health Organization's error. When they said, look, Wuhan province, Look, Italy, mortality 11.4%, 5.4%, 8.2%. These massive death rates. Well, the difference was these organizations were saying, but we think the numbers are 10 to 20 times greater, maybe 50 times greater numbers are going to come down. And we've seen the numbers coming down slowly to now we're at the 0.6%. I did see some California numbers suggesting maybe 0.06, but that was a one off and you need multiple data points before you can actually say something. The gist is that they're doing the exact opposite bias. We're saying, look, in our population, 6.5% of people are positive. Therefore, look, this is throughout the whole state at the exact same rate. Therefore, look, the Death rate is 0.03, 0.06. And that's, that's just bad scientists, bad statistical analysis. It's a massive misrepresentation. And we've been talking about this in our video series we've been doing. We've been looking at different countries like Sweden, like North Korea, like Germany, and comparing how through the last two months how the numbers are changing, each country, each locality. And we talked about how New York City is almost like Lombardi Italy, population density, travel. And we can't look at New York City and say it's the same as New York State or LA or central Virginia. And that's one of the things as well is they're not recognizing that different cities are different, different localities are different, different countries are different. They're saying, look, we got this number, therefore this is the data for the entire state, maybe the country. That's a huge selection bias. And that's what that logical error is called, the selection bias. The fifth thing they did is we all know that the rural college projections were off and the world health organizations were off and the University of Washington projections were off. We've been seeing them come down again. We all knew that the death mortalities were being projected at 2.4 million, then 1 million. Now it's like the 60,000 mark. It's probably going to pop back up. Now the projections are going up because we're now saying, hey, the assumptions were that we'd be social distancing through June, July, August. Now we're going back out. So we're seeing those numbers go back up, you know, saying, you know, that the errors that they had, errors like that. There's a thing called false. There's a logical error called false attribution. And what they do is you recognize one error group and say, therefore, because of this error our stuff is right, or because of this error, everything else is wrong. They started their stuff high and coming down again, this group is doing the exact opposite and saying, look, we have these numbers, we're going to generalize them similar to what these organizations did, but we're not going to recognize our error or fault. We're going to say, look, because of this, therefore our numbers are more accurate. And that's called a false attribution. Again, that's misleading people to think that, hey, this is not as dangerous, you know, as it could be if you're young and healthy. Yes, it's not that dangerous if you're a young female, it's not that dangerous if you're my dad, who's 80, you know, if he gets hospitalized, he has, if he gets this thing, he has about a 15% chance of dying from it. You know, that's not good. So this is not. We have to interpret the data based on where it's coming from localities. And they were not, they were generalizing all their stuff very extremely. The next issue I have with them is they introduce calculation errors to combat faulty projections. So basically because the faulty projections I mentioned before, they introduced their own calculation errors saying, look at our population and did the exact opposite error type. And that's what's kind of funny to me is that literally they're saying this is wrong, therefore I'm going to do the exact same error on this side. And that's how politics works, right? You know, if you believe, you know, you know, everybody should own machine guns. And then the other response is that we, no one should have guns at all. And we tend to go on these extreme, extreme stream sides. The reality is there's some middle place and they're doing that area where they're going to one extreme and saying, look, look, look, we're going to do the exact opposite area this side. And you can't have a debate or discussion with just reintroduction of more and more errors. You know, we need to come with, there needs to be some Middle ground. In our political discourse, there needs to be some middle ground. In our education discourse, there needs to be middle ground. And just how we interact with people and going to the exact opposite extreme, that's a, that's a political maneuver that we see in politics a lot. Physicians should not do that, academics should not do that. Philosophers, people, thought leaders shouldn't do that. That's my basic point. So we talk about that. You know, one of the things, we've been following the data in China and Sweden and England this whole time and putting videos out about it. So if anybody wants, I think we put 30, 40 some videos out on all these data points and we've been tracking this stuff. And so what we've been doing, we've been going forward with the dad interpreting as changing. What this group has done is they've started on the front end of things and they're now looking back. It's actually called eisegesis in theology. This error is actually an isogenical error where you go back and read into stuff what you want to say versus following along and taking the word, the dad information for what it actually is. And in order to not do that kind of error, you basically have to be familiar with the topic, you have to be following the entire time and you have to know the history of the evolution of the topic you're looking at as well. And all the different geographical, political, all different things that make the data the data. And they have not done that. And that's another type of false equivalence error as well. So another false equivalence error was this one here. Yeah. So another one is they're looking at the data, they're looking as if we're already through this thing. And that's a big. If you look at the data from the University of Washington Worldometer, all those things, if you see the graphs, you'll see they kind of stop. Halfway through New York City is probably the closest to being at herd immunity, which herd immunity, you need about 70% of the population to have this, to have herd immunity. As of last week, they're like maybe 22%. So if you look at these graphs and charts, you see we're not, you know, we're not halfway through this yet. That's the reason why we think we have a spike. That's the reason why Sweden probably won't, because they're hoping to get to herd immunity by the end of the summer. And so to make your data and say, look, I'm going to project this out as if we've already done this, which is what they kind of were doing in their mortality numbers, their number is going to at least triple or quadruple based on the fact that, well, actually in California and there they're at. From the data we have, maybe 2, 3% of the population has actually been exposed based on blood bank testing, not testing sick people coming to urgent cares. And so what we see is that's another false equivalence. We're not looking at apples and apples. We're not comparing the data trend in lines. So what are my other thoughts about this? And then comparing this with flu seasons again, we can't compare a partial season of anything with the complete season of anything else. I mean we're basically starting the season late. So we did like a partial late winter and we're going to get right, we haven't gone through a whole Covid season yet. So to compare this and say, look, these are my numbers, this is the way it's going to be. When the reality is, you know, Virginia, for example, if you look at our graphs and charts, it looks like we've maybe gone a third of the way through it with a shelter in place, meaning without the shelter in place, there's a lot more to go through. That's the reason we need antibody testing to figure out the prevalence of this in the population to really know where we're at. The ninth one I'm going to stop here because I could keep on going is the Sweden. They're taking the Swedish testing comparison. That's a bad, that's a non starter looking at Sweden because they've just been open, they've been pushing the non testing model, they've been pushing the herd immunity model. So you can't say we're going to use Swedish data for a testing model when literally their leader said we're not doing this. We're going to let everybody get this and keep the healthy people out there, keep the sick people in. And so you can't look at their testing and say look at their testing, their data. Let's compare with that because literally we don't know. They're absolutely prevalent. So we don't know because they're basically waiting to get to the hospital before they start testing. Not really doing the degree of stuff people forget. The United States has tested more people than any other country in the world. We are now number one. Number one. Right. So how do you, how do you compare us with someone else who's not even doing the same model, doing a radically different model? And the answer is you can't. So I could go on and on. Yeah. Then the whole comparison with Sweden and California, I mean, Sweden has 10 million people. California has 39 million people. Sweden is homogenous one ethnic group. California is like, I mean, it used to be part of the Spanish empire. I mean, it's this huge state that represents like as I think as a country, it has like the fifth or sixth most powerful economy in the world or had. Population wise. It's like, you know, 40. It's like over 10% of the American population is in one state. Like, how can you compare Sweden, the small country, homogeneous, with California? Just, it's. You can't do that. That's not how population medicine works. That's not how ecological based medicine works. That's not how stuff works. So I could go on and on, but the point I think is, is that the reason we've been doing our videos is for this reason, to educate people with good information so you can interpret stuff. So I'd encourage you if you kind of, if anything I've said kind of resonates with you, maybe go back and look at some other videos. You know, I know I talk kind of fast, I slur. I'm trying to work on talking better. You know, people tell me that unfortunately a lot. But the point is we're hopefully giving people information that you can become educated and make your own decisions, not be swayed to and fro by the winds, you know, or by different opinions, which is what tends to happen in the Twitter world, social media world, etc. So hopefully this is helpful. You know, I'm not going to really probably I might continue to talk about this depending on what people want me to talk about. Because ultimately I want to educate people to help them with their anxiety and help them kind of get through this. That's one of the reasons we're doing this, is for our patients and people that are following us. Give us your feedback. I'd love to hear it because that's what got me following this. The reason I started following this in January is because people ask me about it. The reason I started doing it more commonly because people told me that was helping with their anxiety. The reason I actually addressed this, Drs. Erickson and Messini, is because people ask me. So just place your thoughts comments below, let me know what you're thinking. That'll be helpful to us. If you like this. Follow us Share this Follow us on social Media Check our website out. We've got a lot of health resources there for patients. We're trying to be there for you in this time to help us all get through this, because we have to get through this together and we want to do the right thing. On end, though, my personal bias is I do think it's about time for us to reintroduce ourselves to society. I think we have enough data. So ultimately their goal, I kind of sort of agree with it, but I disagree with 99% of everything else they said, which is a weird place to be in. Right? That's my bias, you know. But we have to do it smart. We have to do it where we only let the healthy people go out, the young people, the people without comorbidities. If your BMI is over 30 and you're a male, you're high risk of being a male. Higher than female obesity, more than not if you're over 60, that increases your risk. If you're over 65, even more. If you're 80 or 80, 85, even greater if you've got metabolic syndrome. These are all things that increase your risk. We should protect the vulnerable. And that's one thing they didn't talk about as well. When we start reintroducing ourselves, we need to keep the people that are high risk at home. Maybe the testing is used to figure out who has been infected already, that can safely go back to work. You know, again, we talked about the testing. Please refer to those videos. But I think we need to have a logical, well thought out plan and not make emotional decisions, and not make decisions based on our personal biases or, or our preconception biases, but based on what we know. I think we have enough data to go back out and start reintroducing ourselves. And actually that's happening this week and next week and the next week. So it's already happening. So it's not as if we need to force it to happen. We need to have it happen. Maybe a little more logical. Sure. Anyway, I can stop there. Hope you all have a great day again. Give us some feedback, let us know your thoughts. Any further questions you may have. Share this with friends. If someone's been watching the other videos, please share this with them. The only way we get this information out is if you share it. One of the things I've learned is just calling this COVID 19 automatically. For Instagram and other media, it just kind of gets filtered out. So you have to share it. So please share it and you all take care.