1 00:00:01,840 --> 00:00:08,720 Speaker 1: Also media, Hello and welcome to the podcast. It's me 2 00:00:09,039 --> 00:00:12,440 Speaker 1: James today and I'm very lucky to be joined by 3 00:00:12,480 --> 00:00:15,200 Speaker 1: a couple of people who I'm about to introduce to 4 00:00:15,280 --> 00:00:18,919 Speaker 1: discuss the very important topic of does Tyler and old 5 00:00:19,000 --> 00:00:21,960 Speaker 1: give your baby autism? I think we probably already know 6 00:00:22,000 --> 00:00:23,640 Speaker 1: the answer, but nonetheless we have half an hour to 7 00:00:23,960 --> 00:00:28,840 Speaker 1: talk about it. So you were here, doctor Carve Hoder laughing, 8 00:00:29,040 --> 00:00:30,840 Speaker 1: that's uh, that's cave. 9 00:00:31,040 --> 00:00:31,240 Speaker 2: Yeah. 10 00:00:31,640 --> 00:00:33,080 Speaker 1: Many of you will know him, but he's a medical 11 00:00:33,120 --> 00:00:36,440 Speaker 1: doctor and host of the House of Pod podcast. And 12 00:00:36,520 --> 00:00:39,080 Speaker 1: I'm also joined by Tyler Black, who's a psychologist in 13 00:00:39,320 --> 00:00:43,920 Speaker 1: British Columbia. Welcome Tyler, chiatrist, psychiatrist. Fucked it up? 14 00:00:44,720 --> 00:00:47,080 Speaker 2: Them fighting words, James them fighting. 15 00:00:47,080 --> 00:00:49,760 Speaker 1: Yeah, no, I know, yeah, this is yes. Like when 16 00:00:49,800 --> 00:00:53,000 Speaker 1: people call me a sociologists, I understand, or even worse, 17 00:00:53,120 --> 00:00:54,240 Speaker 1: an anthropologist. 18 00:00:54,640 --> 00:00:56,560 Speaker 3: It's a pleasure to be here and no worries. 19 00:00:56,680 --> 00:00:59,720 Speaker 2: Tyler is Canadian, so to see him correct somebody on 20 00:00:59,760 --> 00:01:01,120 Speaker 2: something and makes me happy. 21 00:01:01,800 --> 00:01:02,560 Speaker 3: I'm very sorry. 22 00:01:02,640 --> 00:01:03,840 Speaker 1: Yeah, but that's why we get him on. 23 00:01:03,960 --> 00:01:06,640 Speaker 2: He's very sorry, he's very sorry about that. I love 24 00:01:06,720 --> 00:01:10,119 Speaker 2: Tyler very much. He comes on my show not infrequently 25 00:01:10,560 --> 00:01:13,200 Speaker 2: and one really pleasant thing that's happened. One little bright 26 00:01:13,240 --> 00:01:15,760 Speaker 2: spot in the last I don't know, five years of 27 00:01:16,040 --> 00:01:21,000 Speaker 2: terror that have been happening medically is seeing Tyler gradually 28 00:01:21,040 --> 00:01:25,119 Speaker 2: over time become grumpier and I'm more willing to fight. 29 00:01:27,959 --> 00:01:30,000 Speaker 2: That's the only bright spot I've had. Thank you Tyler 30 00:01:30,080 --> 00:01:30,320 Speaker 2: for that. 31 00:01:30,400 --> 00:01:34,600 Speaker 1: Yeah, I imagine that's the side effect of your consumption 32 00:01:34,640 --> 00:01:35,640 Speaker 1: of a seat of metaphana. 33 00:01:35,880 --> 00:01:36,840 Speaker 3: Maybe send me to you. 34 00:01:37,280 --> 00:01:39,640 Speaker 2: Yeah, I got a cut back, bro got cut back. 35 00:01:40,000 --> 00:01:42,399 Speaker 1: Yeah, all right. For those not familiar, why are we 36 00:01:42,480 --> 00:01:44,920 Speaker 1: talking about Tyler and All? Might be the name you're 37 00:01:44,959 --> 00:01:47,440 Speaker 1: familiar if you, especially of your American people, like to 38 00:01:47,560 --> 00:01:50,040 Speaker 1: use brand names a little more. I still find that 39 00:01:50,160 --> 00:01:52,040 Speaker 1: very confusing, and I've lived here for a better part 40 00:01:52,080 --> 00:01:54,600 Speaker 1: of two decades. But why are we talking about time 41 00:01:54,680 --> 00:01:54,920 Speaker 1: and all? 42 00:01:55,120 --> 00:01:57,240 Speaker 2: Tyler? Do you want to introduce this concept? 43 00:01:57,560 --> 00:02:02,800 Speaker 3: Sure so, Yeah, tilan all goes by Parascenamol in UK 44 00:02:03,240 --> 00:02:06,400 Speaker 3: and other places in the world. It's a seed of 45 00:02:06,480 --> 00:02:09,560 Speaker 3: minifin here. So it really is not talking about talent, 46 00:02:09,600 --> 00:02:13,280 Speaker 3: although the shorthand that the political people who've been talking 47 00:02:13,320 --> 00:02:15,960 Speaker 3: about it have specifically called out the brand Talentol, which 48 00:02:16,000 --> 00:02:20,720 Speaker 3: is bizarre. But this stems from both a mission that 49 00:02:21,080 --> 00:02:24,280 Speaker 3: RFK Junior when he took over as the HHS sort 50 00:02:24,320 --> 00:02:27,720 Speaker 3: of had, which was to find the cause of autism, 51 00:02:28,200 --> 00:02:33,399 Speaker 3: which is his political quest to find some environmental cause. 52 00:02:33,440 --> 00:02:35,480 Speaker 3: I mean, he started as an environmental lawyer. I don't 53 00:02:35,480 --> 00:02:38,760 Speaker 3: think he's doing this disingenuously. I think he truly believes 54 00:02:39,080 --> 00:02:42,360 Speaker 3: there was an environmental cause to autism. But of course 55 00:02:42,880 --> 00:02:46,040 Speaker 3: RFK wheeled science probably driven by the brainworm, and so 56 00:02:46,200 --> 00:02:49,799 Speaker 3: he has this way of having a conclusion and finding 57 00:02:49,840 --> 00:02:53,480 Speaker 3: the science to support it. And it was very clear 58 00:02:53,560 --> 00:02:57,720 Speaker 3: that he was going to point towards vaccine vaccine schedule, 59 00:02:57,760 --> 00:03:00,600 Speaker 3: and at some point this is definitely coming. I think 60 00:03:00,600 --> 00:03:02,359 Speaker 3: this might be a roundabout way to do it through 61 00:03:02,400 --> 00:03:06,120 Speaker 3: fevers and talinol. But the talental link is something that 62 00:03:06,320 --> 00:03:09,760 Speaker 3: has been a question mark. So a really quick aside 63 00:03:09,800 --> 00:03:13,640 Speaker 3: will be that when drugs are regulated, the drug companies 64 00:03:13,680 --> 00:03:16,440 Speaker 3: have very little natural interest to study it in pregnant people. 65 00:03:16,480 --> 00:03:19,240 Speaker 3: It only brings them risk. There's no reason to do it. 66 00:03:19,320 --> 00:03:22,040 Speaker 3: You are required to submit what studies you have on 67 00:03:22,200 --> 00:03:24,680 Speaker 3: animal toxicity in utero and these types of things, but 68 00:03:24,760 --> 00:03:27,520 Speaker 3: not really that much for humans, and so the drug 69 00:03:27,520 --> 00:03:30,079 Speaker 3: companies usually put their hands up and go talk to 70 00:03:30,160 --> 00:03:32,720 Speaker 3: your doctor about using this, and then the rest of 71 00:03:32,800 --> 00:03:35,760 Speaker 3: us in medicine have to take that information that's been 72 00:03:35,800 --> 00:03:38,720 Speaker 3: generated about this medication and try and interpret it on 73 00:03:38,920 --> 00:03:43,360 Speaker 3: pregnant people. And it creates this system where we create 74 00:03:43,400 --> 00:03:45,760 Speaker 3: the evidence over the next twenty years in what we 75 00:03:45,800 --> 00:03:50,320 Speaker 3: call pharmacal vigilids or post marketing studies, where we basically, 76 00:03:50,960 --> 00:03:53,480 Speaker 3: has there been a problem, did we find any birth effects? 77 00:03:53,480 --> 00:03:53,640 Speaker 2: You know? 78 00:03:54,040 --> 00:03:56,680 Speaker 3: And we kind of do it backwards. It's kind of 79 00:03:56,720 --> 00:03:58,960 Speaker 3: makes sense because you couldn't really do an RCAT on 80 00:03:59,120 --> 00:04:01,200 Speaker 3: pregnant women to star with if you didn't know any 81 00:04:01,240 --> 00:04:05,080 Speaker 3: reason for the drugs. So it's one of those sort 82 00:04:05,120 --> 00:04:08,320 Speaker 3: of loopholes. And so this natural conversation has resulted in 83 00:04:08,360 --> 00:04:11,600 Speaker 3: science that points in a number of directions. Does the 84 00:04:11,640 --> 00:04:14,840 Speaker 3: cedamnifite cause autism? Can't be answered by the current science 85 00:04:14,840 --> 00:04:17,599 Speaker 3: because it's all cohort data, it's looking backwards, it's looking 86 00:04:17,680 --> 00:04:22,120 Speaker 3: at populations. It's confounded. However, the best study was published 87 00:04:22,120 --> 00:04:24,120 Speaker 3: in twenty twenty four, which makes the timing of this 88 00:04:24,120 --> 00:04:26,960 Speaker 3: announcement really awkward. There was two point five million people. 89 00:04:27,560 --> 00:04:31,600 Speaker 3: It was a believe it's a Danish study Swedish study. Okay, 90 00:04:31,760 --> 00:04:34,760 Speaker 3: and in that study there was a small link found, 91 00:04:35,200 --> 00:04:37,560 Speaker 3: but because they had two point five million people, they 92 00:04:37,600 --> 00:04:40,720 Speaker 3: could check that link by looking at sibling pairs within 93 00:04:40,800 --> 00:04:43,480 Speaker 3: that two point five million. So in that group they 94 00:04:43,520 --> 00:04:46,919 Speaker 3: had sixteen thousand sibling pairs both exposed to and not 95 00:04:47,080 --> 00:04:50,960 Speaker 3: exposed to acetaminifin, and lo and behold they found that 96 00:04:51,000 --> 00:04:53,760 Speaker 3: there was no relationship there. So this really is one 97 00:04:53,760 --> 00:04:58,000 Speaker 3: of the more definitive correlational studies that says pretty much, 98 00:04:58,000 --> 00:05:01,800 Speaker 3: any effect we're seeing is probably confounded. It probably isn't 99 00:05:01,839 --> 00:05:05,080 Speaker 3: due to a cinemenifin. Though there are some animal studies 100 00:05:05,120 --> 00:05:07,280 Speaker 3: that might hint at it, it appears to be minor 101 00:05:07,279 --> 00:05:09,239 Speaker 3: and k I see are about to say something. 102 00:05:09,320 --> 00:05:11,600 Speaker 2: Yeah, First of all, that's exactly right. I think that 103 00:05:12,400 --> 00:05:14,919 Speaker 2: there are a lot of things that Maha and RFK 104 00:05:15,080 --> 00:05:17,800 Speaker 2: Junior talk about that are just insane, and you can 105 00:05:17,880 --> 00:05:21,120 Speaker 2: dismiss out of hand. This is a topic that is 106 00:05:21,160 --> 00:05:24,320 Speaker 2: not complete rubbish. It is something that has a little 107 00:05:24,320 --> 00:05:27,120 Speaker 2: bit of nuance and we can talk about as Tyler 108 00:05:27,200 --> 00:05:30,040 Speaker 2: was just mentioning, there is some evidence that there might 109 00:05:30,080 --> 00:05:34,680 Speaker 2: be a small relationship, but the real key is determining 110 00:05:34,720 --> 00:05:37,640 Speaker 2: if it's a causal relationship or just correlative. Are they 111 00:05:37,720 --> 00:05:40,720 Speaker 2: just related for some reason or another, or are they 112 00:05:40,800 --> 00:05:43,799 Speaker 2: caused by each other? And that study that he talked about, 113 00:05:43,800 --> 00:05:46,160 Speaker 2: that Swedish study looked at about one hundred and eighty 114 00:05:46,200 --> 00:05:50,920 Speaker 2: thousand infants that had parents that were exposed to a cinemenafin. 115 00:05:51,440 --> 00:05:54,320 Speaker 2: What's really elegant about that is that it looked at 116 00:05:54,320 --> 00:05:57,320 Speaker 2: the siblings. That's why it's such an important study. And 117 00:05:57,360 --> 00:05:59,880 Speaker 2: that's what I say, it closes the door on the matter. 118 00:06:00,200 --> 00:06:03,440 Speaker 2: I agree with Tyler. I think the preponderance of evidence 119 00:06:03,480 --> 00:06:06,400 Speaker 2: now is that there is no connection between town law 120 00:06:06,440 --> 00:06:09,239 Speaker 2: and autism. But I don't know if this study totally 121 00:06:09,240 --> 00:06:12,599 Speaker 2: closes the door. It is really well done though. So 122 00:06:12,720 --> 00:06:15,880 Speaker 2: they showed that if you look at siblings, if you 123 00:06:15,880 --> 00:06:19,120 Speaker 2: look at a family, there's no connection. You take out 124 00:06:19,160 --> 00:06:21,120 Speaker 2: some of the variables, you take out some of the 125 00:06:21,120 --> 00:06:25,600 Speaker 2: confounders there that can obfuscate or confuse an issue. You 126 00:06:25,640 --> 00:06:27,640 Speaker 2: take those out of the picture, and you see that 127 00:06:27,680 --> 00:06:31,520 Speaker 2: there's no relationship between town lam menaphin. What's interesting in 128 00:06:31,520 --> 00:06:34,560 Speaker 2: that same study that sweet To study, if they then 129 00:06:35,040 --> 00:06:38,480 Speaker 2: put those back in, if they didn't account for the siblings, 130 00:06:38,839 --> 00:06:40,960 Speaker 2: then Yeah, showed that there is a little bit of 131 00:06:41,040 --> 00:06:47,280 Speaker 2: evidence a small basic relationship between you know, senomenaphin and 132 00:06:47,560 --> 00:06:51,400 Speaker 2: developing autism. But once you start accounting for some of 133 00:06:51,440 --> 00:06:55,240 Speaker 2: these these really tough to account for variables, then you 134 00:06:55,320 --> 00:06:58,480 Speaker 2: start to see that that falls apart, and that implies 135 00:06:58,520 --> 00:07:01,160 Speaker 2: that most of these other studies are not causal but 136 00:07:01,560 --> 00:07:03,280 Speaker 2: correlative relationships. 137 00:07:03,440 --> 00:07:06,640 Speaker 3: The sort of twenty twenty five update is and I 138 00:07:06,680 --> 00:07:09,039 Speaker 3: think this might have I think as that we learn 139 00:07:09,080 --> 00:07:10,720 Speaker 3: more about it, this might have been something that was 140 00:07:10,760 --> 00:07:16,120 Speaker 3: either solicited or developed in tandem with RFK and his goals. 141 00:07:16,160 --> 00:07:19,600 Speaker 3: But there was a publication in twenty twenty five by 142 00:07:19,760 --> 00:07:23,160 Speaker 3: I think the Harvard Dean of Medicine, who has been 143 00:07:23,160 --> 00:07:28,320 Speaker 3: a plaintiff's witness for attorneys battling talentol in developing autism. 144 00:07:28,360 --> 00:07:31,120 Speaker 3: So there is a bit of a financial conflict of 145 00:07:31,160 --> 00:07:35,480 Speaker 3: interest there, right, Yeah. Baccarelli, Yeah, doctor Baccarelli, who published 146 00:07:35,480 --> 00:07:38,480 Speaker 3: a study called a Navigation Review, and it's basically a 147 00:07:38,600 --> 00:07:41,280 Speaker 3: science y version of let me tell a story, and 148 00:07:41,280 --> 00:07:44,360 Speaker 3: here's the evidence that supports it. Basically, what they did 149 00:07:44,440 --> 00:07:48,080 Speaker 3: is they took the number of studies, they counted the 150 00:07:48,160 --> 00:07:50,840 Speaker 3: number that pointed towards talinol as a factor, and they 151 00:07:50,840 --> 00:07:53,720 Speaker 3: counted against it, and they found about twenty something in total. 152 00:07:54,280 --> 00:07:57,000 Speaker 3: The majority of them found a link to talent al 153 00:07:57,040 --> 00:08:01,120 Speaker 3: and autism, and then a minority found no link. But 154 00:08:01,200 --> 00:08:03,880 Speaker 3: of course that's not really how we do science. In 155 00:08:03,920 --> 00:08:07,240 Speaker 3: twenty twenty five, if we had two studies and you 156 00:08:07,240 --> 00:08:09,440 Speaker 3: can actually look at his studies, and some of these 157 00:08:09,440 --> 00:08:12,239 Speaker 3: studies are two hundred people, three hundred people, five hundred people, 158 00:08:12,840 --> 00:08:14,800 Speaker 3: and then you have this other study that's two point 159 00:08:14,800 --> 00:08:18,880 Speaker 3: five million people. You know, in the real world that 160 00:08:19,040 --> 00:08:22,239 Speaker 3: larger study would dwarf the significance of the other ones. 161 00:08:22,280 --> 00:08:24,640 Speaker 3: But in the way that this navigation study was set up, 162 00:08:24,640 --> 00:08:27,400 Speaker 3: they're all kind of equal. In fact, he treats the 163 00:08:27,760 --> 00:08:32,600 Speaker 3: non confounded sample that Cave was mentioning as its own study, 164 00:08:32,960 --> 00:08:36,560 Speaker 3: and then he treats the controlled sample with siblings as 165 00:08:36,640 --> 00:08:40,080 Speaker 3: its own studies. So the same study from Sweden was 166 00:08:40,120 --> 00:08:44,120 Speaker 3: cited twice, one four and one against. You can see 167 00:08:44,120 --> 00:08:47,000 Speaker 3: how you could shape a narrative, which is what a 168 00:08:47,080 --> 00:08:50,240 Speaker 3: narrative review is. It's when you shape a narrative. It's 169 00:08:50,280 --> 00:08:52,240 Speaker 3: not a very sciencey way to do things. We like 170 00:08:52,320 --> 00:08:55,959 Speaker 3: to do systematic reviews, and this did provide a bit 171 00:08:55,960 --> 00:09:00,280 Speaker 3: of cover because now everyone in AHHS can point to words. 172 00:09:00,320 --> 00:09:02,880 Speaker 3: This study by the Harvard Deed of Medicine, published in 173 00:09:03,360 --> 00:09:08,600 Speaker 3: BMC Environmental Study is peer reviewed showing that a navigational 174 00:09:08,640 --> 00:09:11,120 Speaker 3: study shows that there could be a link. But it 175 00:09:11,160 --> 00:09:14,200 Speaker 3: really if you read the study, any scientists reading it like, yeah, 176 00:09:14,200 --> 00:09:16,040 Speaker 3: there could be a link, but the largest study in 177 00:09:16,080 --> 00:09:17,920 Speaker 3: that group suggests there is no link. 178 00:09:18,720 --> 00:09:21,400 Speaker 1: Right, yeah, in terms of someone's playing games with evidence 179 00:09:21,520 --> 00:09:24,080 Speaker 1: when they've already decided what they completly would it be. Yeah, 180 00:09:24,640 --> 00:09:29,640 Speaker 1: let's talk about this fascination with autism that exists in 181 00:09:29,679 --> 00:09:33,000 Speaker 1: the MAHA. Right, make America healthy again. For those who 182 00:09:33,000 --> 00:09:37,280 Speaker 1: are not familiar what's happening here, people are probably diagnosed 183 00:09:37,280 --> 00:09:39,640 Speaker 1: with autism at a higher rate now than they were 184 00:09:39,800 --> 00:09:43,160 Speaker 1: when these people were young. Right, that is not however, well, 185 00:09:43,280 --> 00:09:45,360 Speaker 1: I will let you guys explain that. Explain how that 186 00:09:45,400 --> 00:09:48,319 Speaker 1: doesn't mean that we're giving children autism If that is 187 00:09:48,360 --> 00:09:49,240 Speaker 1: my understanding is. 188 00:09:49,160 --> 00:09:53,360 Speaker 3: Correct, sure, I mean I'll jump in first. So there's 189 00:09:53,440 --> 00:09:55,360 Speaker 3: a number of ways to test whether or not the 190 00:09:55,440 --> 00:09:57,880 Speaker 3: rate is truly increasing. So the first thing to say is, 191 00:09:58,120 --> 00:10:01,840 Speaker 3: over the world, I've seen a gradual increase in the 192 00:10:02,440 --> 00:10:06,920 Speaker 3: global population that has autism from about zero point eight 193 00:10:06,920 --> 00:10:09,960 Speaker 3: percent of the population to about two percent of the population. 194 00:10:10,520 --> 00:10:12,960 Speaker 3: That's what's happened over the past twenty five years of 195 00:10:13,000 --> 00:10:16,360 Speaker 3: studies across the world. Now, that's not exactly the exponential 196 00:10:16,480 --> 00:10:18,880 Speaker 3: rise that you often hear about in the United States. 197 00:10:19,200 --> 00:10:21,280 Speaker 3: The United States has a lot of unique features though. 198 00:10:21,320 --> 00:10:23,280 Speaker 3: You have a ton of people working in this area, 199 00:10:23,320 --> 00:10:25,360 Speaker 3: you have a ton of researchers, lots of people have 200 00:10:25,440 --> 00:10:28,559 Speaker 3: access to healthcare. There's many reasons why global numbers might 201 00:10:28,600 --> 00:10:32,320 Speaker 3: not look like American numbers, but the general idea behind 202 00:10:32,320 --> 00:10:35,679 Speaker 3: this increase rate of autism. Most of that increase is 203 00:10:35,760 --> 00:10:37,960 Speaker 3: due to our change in diagnostics in the way that 204 00:10:38,000 --> 00:10:41,240 Speaker 3: we label things. So when RFK was a kid, there 205 00:10:41,240 --> 00:10:43,600 Speaker 3: were kids that were excluded from school because they were 206 00:10:43,640 --> 00:10:47,320 Speaker 3: literally called retarded. They were not allowed to come to school. 207 00:10:47,320 --> 00:10:49,559 Speaker 3: They were known as spass and goofs, and they were 208 00:10:49,559 --> 00:10:52,240 Speaker 3: the ones that were made fun of and they struggled 209 00:10:52,240 --> 00:10:55,199 Speaker 3: throughout life. Now that were they called autistic, No, did 210 00:10:55,200 --> 00:10:57,680 Speaker 3: they have the same symptoms that the kids today that 211 00:10:57,720 --> 00:11:01,320 Speaker 3: are being diagnosed with autism have And the way that 212 00:11:01,360 --> 00:11:03,800 Speaker 3: we can control for that or there's some really elegant studies. 213 00:11:03,840 --> 00:11:08,439 Speaker 3: One is we take diagnostic criteria from children and then 214 00:11:08,480 --> 00:11:11,839 Speaker 3: we ask adults currently living today to go through a 215 00:11:11,880 --> 00:11:14,800 Speaker 3: structured interview looking for those things. And yes, what we 216 00:11:14,840 --> 00:11:17,480 Speaker 3: find the same rate in adults that we see in kids. 217 00:11:18,000 --> 00:11:22,000 Speaker 3: This idea that it's an exponential rate. Now, I think 218 00:11:22,040 --> 00:11:25,360 Speaker 3: the rate is also increasing, but I think it's increasing gradually, 219 00:11:25,400 --> 00:11:27,800 Speaker 3: and this is because the extreme of ages are having 220 00:11:27,920 --> 00:11:30,360 Speaker 3: kids more often, especially at the older end. And we 221 00:11:30,400 --> 00:11:33,480 Speaker 3: do know that older age is related to autism, especially 222 00:11:33,520 --> 00:11:36,719 Speaker 3: older age of the father. And we also know that 223 00:11:37,280 --> 00:11:41,800 Speaker 3: premature babies and babies with significant developmental disabilities are surviving 224 00:11:42,080 --> 00:11:45,680 Speaker 3: their post natal period as soon as they're born. Instead 225 00:11:45,720 --> 00:11:49,400 Speaker 3: of instantly dying or dying during childbirth or not being 226 00:11:49,440 --> 00:11:52,520 Speaker 3: able to be resuscitated, they're kept alive and survive and 227 00:11:52,720 --> 00:11:55,240 Speaker 3: this is good. But this does mean that there's more 228 00:11:55,400 --> 00:11:58,200 Speaker 3: neurodiversity in the world because of course these children have 229 00:11:58,480 --> 00:11:59,960 Speaker 3: encountered significant harm. 230 00:12:00,000 --> 00:12:01,840 Speaker 2: And I agree with that. I do think that the 231 00:12:01,920 --> 00:12:05,560 Speaker 2: diagnostic criteria has expanded and that's part of why we 232 00:12:05,679 --> 00:12:09,040 Speaker 2: see more. But yeah, I think the two things we 233 00:12:09,120 --> 00:12:14,000 Speaker 2: know that are related are some genetic predisposition. If there's 234 00:12:14,080 --> 00:12:16,160 Speaker 2: people in the family that have it, and the older 235 00:12:16,200 --> 00:12:18,880 Speaker 2: age of patients, and as we get older. I'm an 236 00:12:18,880 --> 00:12:23,480 Speaker 2: older father myself. You know, you see more with older patients, 237 00:12:23,480 --> 00:12:25,680 Speaker 2: and that's more common now than it's ever been before. 238 00:12:25,720 --> 00:12:27,640 Speaker 2: So these are all a part of it. And once 239 00:12:27,720 --> 00:12:29,880 Speaker 2: you take a look, for example, going back to that 240 00:12:29,920 --> 00:12:32,839 Speaker 2: Swedish study in twenty twenty four that was so good, 241 00:12:33,360 --> 00:12:36,000 Speaker 2: that sibling study, looks at the genetics of it, And 242 00:12:36,040 --> 00:12:38,320 Speaker 2: once you count for the genetics of it, you start 243 00:12:38,360 --> 00:12:40,520 Speaker 2: to be able to say, Okay, maybe that's other stuff 244 00:12:40,559 --> 00:12:43,800 Speaker 2: like tile mall isn't important? Yeah? 245 00:12:44,080 --> 00:12:47,240 Speaker 1: Yeah, is there a gender element to this as well? Yeah, 246 00:12:47,320 --> 00:12:50,800 Speaker 1: I may have misfremenbed here. My understanding is that women 247 00:12:50,880 --> 00:12:54,080 Speaker 1: FEN people tended to be diagnosed at a lower rate 248 00:12:54,400 --> 00:12:55,559 Speaker 1: until relatively recently. 249 00:12:55,880 --> 00:12:58,839 Speaker 3: Yeah, So not only is there a gender component, but 250 00:12:58,880 --> 00:13:01,200 Speaker 3: I do think that the bio logical sex of the 251 00:13:01,440 --> 00:13:04,640 Speaker 3: child has an impact on the genetic expression, because it 252 00:13:04,679 --> 00:13:08,640 Speaker 3: seems like the transmission to males is higher than the 253 00:13:08,640 --> 00:13:12,000 Speaker 3: transmission to females. So there might be something buffering about 254 00:13:12,000 --> 00:13:14,240 Speaker 3: that extra X chromosome. You know, we have this shrimpy 255 00:13:14,240 --> 00:13:16,760 Speaker 3: little Y chromosome that makes us all degenerates. You only 256 00:13:16,760 --> 00:13:21,120 Speaker 3: have one Y chromosome, Sorry, are you a super male? 257 00:13:21,200 --> 00:13:24,480 Speaker 4: I have two wys caves y Why you know, Harry, 258 00:13:24,520 --> 00:13:26,920 Speaker 4: My ears are so there are a number of disorders 259 00:13:26,920 --> 00:13:30,840 Speaker 4: that the extra X chromosome is protective for, and I 260 00:13:30,880 --> 00:13:33,000 Speaker 4: do wonder if that's the case for autism. 261 00:13:33,320 --> 00:13:36,400 Speaker 3: But what's also true is we have stereotypes about what 262 00:13:36,520 --> 00:13:39,280 Speaker 3: girls should be and what boys should be, and that 263 00:13:39,360 --> 00:13:44,000 Speaker 3: leads to boys being diagnosed with autism more frequently than girls. 264 00:13:44,000 --> 00:13:46,520 Speaker 3: So the girl that's quiet and awkward and anxious is 265 00:13:46,559 --> 00:13:50,360 Speaker 3: labeled as an anxious kid a lot more quickly than 266 00:13:50,480 --> 00:13:52,600 Speaker 3: when you see that in a boy that the parents 267 00:13:52,640 --> 00:13:55,120 Speaker 3: think autism or the clinician thinks autism. So there could 268 00:13:55,160 --> 00:13:58,400 Speaker 3: be some social reasons for that discrepancy as well. And 269 00:13:58,440 --> 00:14:00,440 Speaker 3: then the last thing I really wanted to say is 270 00:14:00,520 --> 00:14:03,560 Speaker 3: that the really tragic thing about all of this is 271 00:14:03,960 --> 00:14:07,640 Speaker 3: profound autism, which autism is the spectrum. Profound autism is 272 00:14:07,679 --> 00:14:11,959 Speaker 3: extremely disabling for people around the person. Generally, autistic people 273 00:14:12,040 --> 00:14:15,240 Speaker 3: enjoy their lives, especially if the world is set up 274 00:14:15,280 --> 00:14:17,120 Speaker 3: in a way so that they can live safely and 275 00:14:17,160 --> 00:14:21,960 Speaker 3: without impediment. Autistic people are perfectly content to be autistic, 276 00:14:22,360 --> 00:14:27,479 Speaker 3: and this whole idea of autism being this travesty, this epidemic, 277 00:14:27,600 --> 00:14:31,160 Speaker 3: this blight on society, is really doing a disservice to 278 00:14:31,280 --> 00:14:34,240 Speaker 3: the wide variety of people that we're now calling autistic, 279 00:14:34,560 --> 00:14:38,720 Speaker 3: because when our criteria expanded, we created a whole space 280 00:14:38,760 --> 00:14:42,320 Speaker 3: of autistic people who are very what we would call 281 00:14:42,640 --> 00:14:45,840 Speaker 3: non profound autism. These are people that have difficulties in 282 00:14:45,880 --> 00:14:48,760 Speaker 3: social communication or do the same thing over and over 283 00:14:48,840 --> 00:14:51,920 Speaker 3: despite it being at an abnormal level, but it's what 284 00:14:51,960 --> 00:14:54,440 Speaker 3: they need to soothe themselves, you know, that will be 285 00:14:54,480 --> 00:14:55,160 Speaker 3: called autism. 286 00:14:55,200 --> 00:14:55,400 Speaker 2: Now. 287 00:14:56,160 --> 00:14:58,920 Speaker 3: Now, would a parent want a child who's in a 288 00:14:58,960 --> 00:15:03,160 Speaker 3: home constant rocking back and forth and just soothing themselves 289 00:15:03,160 --> 00:15:06,520 Speaker 3: by licking their fingers or whatever, you know, some very 290 00:15:06,560 --> 00:15:10,080 Speaker 3: severe autistic behavior. No, that probably wouldn't be the parents ideal. 291 00:15:10,640 --> 00:15:13,160 Speaker 3: But I've worked with so much autism in my life. 292 00:15:13,200 --> 00:15:15,760 Speaker 3: I'm a child anadists and psychiatrist. They've seen so many 293 00:15:15,840 --> 00:15:19,520 Speaker 3: artistic kids. They can live happy, happy, happy lives autistic, 294 00:15:20,000 --> 00:15:22,240 Speaker 3: So I'm not a fan of the blight sort of 295 00:15:22,280 --> 00:15:23,280 Speaker 3: messaging of it either. 296 00:15:23,600 --> 00:15:26,200 Speaker 1: Yeah, I'm really glad you mentioned that, because that's one 297 00:15:26,200 --> 00:15:28,160 Speaker 1: of the worst things about in a sense, one of 298 00:15:28,200 --> 00:15:30,160 Speaker 1: the most damaging things about is where people who are 299 00:15:30,200 --> 00:15:34,880 Speaker 1: living happy, healthy and fulfilled lives are being like slandered 300 00:15:35,000 --> 00:15:38,880 Speaker 1: or pathologized to rided by the government of this country. 301 00:15:38,920 --> 00:15:42,360 Speaker 1: And that's fucked yeah, and I'm sure will have an 302 00:15:42,400 --> 00:15:44,040 Speaker 1: impact on those people because it would have an impact 303 00:15:44,080 --> 00:15:48,040 Speaker 1: on anyone to see this condition that, as you said, right, like, 304 00:15:48,200 --> 00:15:50,160 Speaker 1: maybe difficult for people who are not familiar with it 305 00:15:50,200 --> 00:15:51,920 Speaker 1: to navigate, but it doesn't mean that you can't have 306 00:15:51,960 --> 00:15:57,160 Speaker 1: a fulfilling and happy and very pleasant life. Suddenly suggested 307 00:15:57,200 --> 00:16:01,160 Speaker 1: it some kind of massively disabling and terror travesty and 308 00:16:01,200 --> 00:16:03,600 Speaker 1: that the person who gave birth to you is to 309 00:16:03,600 --> 00:16:05,160 Speaker 1: blame for this, right. 310 00:16:05,520 --> 00:16:07,960 Speaker 2: Right, That's what really bothers me, is like we're always 311 00:16:07,960 --> 00:16:12,080 Speaker 2: trying to find ways to blame mothers. This is this 312 00:16:12,160 --> 00:16:14,880 Speaker 2: is this is a mantle and I apologize for that. Listener, 313 00:16:15,000 --> 00:16:18,760 Speaker 2: please don't at me for that. But part of what 314 00:16:18,800 --> 00:16:23,240 Speaker 2: this is is like control over women. And you know, 315 00:16:23,320 --> 00:16:26,440 Speaker 2: while that Swedish study of mention may not completely close 316 00:16:26,440 --> 00:16:28,640 Speaker 2: the issue, I think it's pretty clear that the evidence 317 00:16:29,000 --> 00:16:31,960 Speaker 2: pretty strong against there being a connection between taal Mual 318 00:16:32,240 --> 00:16:37,440 Speaker 2: and to make a whole sale governmental recommendation that as 319 00:16:37,480 --> 00:16:40,640 Speaker 2: a country, for us to move this way, to make 320 00:16:40,720 --> 00:16:42,920 Speaker 2: such strong claims, to have a president come out and 321 00:16:43,000 --> 00:16:46,600 Speaker 2: just say grit your teeth and bear it. To women 322 00:16:47,040 --> 00:16:49,440 Speaker 2: in regards to the one medicine that we've told them 323 00:16:49,480 --> 00:16:52,920 Speaker 2: they can use during a pregnancy is insane to me. 324 00:16:53,600 --> 00:16:57,800 Speaker 2: So there's the autism issue and the insult essentially to 325 00:16:58,000 --> 00:17:01,120 Speaker 2: that community, but also to women in general. It's insane 326 00:17:01,160 --> 00:17:04,480 Speaker 2: to me that this is happening right now. Again, there 327 00:17:04,560 --> 00:17:06,440 Speaker 2: is a bit of nuance to this issue. As I mentioned, 328 00:17:06,480 --> 00:17:09,080 Speaker 2: it's not like totally insane to ask about and question it, 329 00:17:09,400 --> 00:17:14,520 Speaker 2: but to make a wholesale directional change in how we 330 00:17:14,600 --> 00:17:19,320 Speaker 2: recommend managing patients with our pregnant is is nuts. It's 331 00:17:19,440 --> 00:17:19,959 Speaker 2: just nuts. 332 00:17:20,160 --> 00:17:22,880 Speaker 3: Yeah, And to piggyback on that, you know, like it's 333 00:17:23,000 --> 00:17:26,600 Speaker 3: really normal. It was normal advice in twenty twenty four 334 00:17:26,960 --> 00:17:29,520 Speaker 3: for us to say, yeah, you can use talan all, 335 00:17:29,520 --> 00:17:32,040 Speaker 3: but try to use it sparingly. We're not really sure 336 00:17:32,520 --> 00:17:34,240 Speaker 3: use it when you need it though, because we do 337 00:17:34,320 --> 00:17:36,280 Speaker 3: know that pain and fever and these types of things 338 00:17:36,280 --> 00:17:38,399 Speaker 3: are bad for the baby, right, you know, So this 339 00:17:38,920 --> 00:17:41,679 Speaker 3: kind of way in which it's now been massaged, So 340 00:17:41,720 --> 00:17:44,560 Speaker 3: I saw a letter from doctor Marty Mackeriy, who's another 341 00:17:44,960 --> 00:17:49,600 Speaker 3: grifter who's now in the American political system. There has 342 00:17:49,600 --> 00:17:53,920 Speaker 3: written a letter basically saying at the bottom, use it judiciously, 343 00:17:54,040 --> 00:17:56,159 Speaker 3: and it is the only one that's proved so. But 344 00:17:56,160 --> 00:17:58,160 Speaker 3: that's exactly where we were before. There was no need 345 00:17:58,200 --> 00:18:01,880 Speaker 3: for a past conference every doctor saying, use talanol sparingly, 346 00:18:01,920 --> 00:18:02,880 Speaker 3: but you can use it. 347 00:18:03,440 --> 00:18:06,600 Speaker 2: James, Can I tell you what's driving me crazy about this? Yeah? 348 00:18:06,640 --> 00:18:06,960 Speaker 1: Please? 349 00:18:07,000 --> 00:18:10,360 Speaker 2: This administration has done something. Trump in general has done 350 00:18:10,400 --> 00:18:15,200 Speaker 2: something that has blown my mind, which is somehow, time 351 00:18:15,280 --> 00:18:19,640 Speaker 2: and time again, I find myself defending people and things 352 00:18:19,720 --> 00:18:24,200 Speaker 2: that I would never want to defend. Like, first of 353 00:18:24,200 --> 00:18:27,160 Speaker 2: on watching Jimmy Kimmel, I don't know how that happened. Yes, 354 00:18:27,200 --> 00:18:32,200 Speaker 2: I blame Trump for that. Second, like tylanol is a 355 00:18:32,320 --> 00:18:36,960 Speaker 2: dangerous medication. I'm a liver doc. Yes, ideal, Like tylanol 356 00:18:37,040 --> 00:18:41,280 Speaker 2: overdose is causing acute liver injury and acute liver failure 357 00:18:41,640 --> 00:18:45,680 Speaker 2: is a massive, real issue across the world, and it is. 358 00:18:46,080 --> 00:18:49,159 Speaker 2: It's it's a real thing. So there are reasons that 359 00:18:49,200 --> 00:18:51,479 Speaker 2: we should be watchful of tailanol, but this is not 360 00:18:51,520 --> 00:18:52,880 Speaker 2: one of them. Right. 361 00:18:53,160 --> 00:18:56,560 Speaker 3: Yeah, personally, I'm a champion of all tailanol should be 362 00:18:56,600 --> 00:18:59,240 Speaker 3: like the UK, it should be in individually wrapped pieces 363 00:19:00,080 --> 00:19:02,639 Speaker 3: because there is evidence that that reduces the rate of 364 00:19:02,680 --> 00:19:05,959 Speaker 3: intentional overdose and even icy overdoses that cause liver failure. 365 00:19:06,280 --> 00:19:07,600 Speaker 3: So yeah, take away freedoms. 366 00:19:07,720 --> 00:19:11,160 Speaker 2: Yeah right, this is the medical freedom crowd. It's amazing. 367 00:19:11,680 --> 00:19:14,640 Speaker 1: Yeah, we should take an advertising break and then come back. 368 00:19:14,680 --> 00:19:16,520 Speaker 2: So we'll do that. Oh god, that would be fantastic 369 00:19:16,520 --> 00:19:18,199 Speaker 2: if I could take an advertise. I could use an 370 00:19:18,240 --> 00:19:18,920 Speaker 2: ad right now. 371 00:19:19,040 --> 00:19:24,440 Speaker 1: So badyup. It's going to be for fucking lemon pepper water, 372 00:19:24,520 --> 00:19:26,960 Speaker 1: which is the only pain treatment you should be taking. 373 00:19:28,200 --> 00:19:29,919 Speaker 2: Bark to put between your teeth. 374 00:19:31,320 --> 00:19:34,480 Speaker 1: Sure, yea, go get some leaves and fucking eat them. 375 00:19:34,520 --> 00:19:47,480 Speaker 1: What can get wrong? All right, we're back. Thank you 376 00:19:47,560 --> 00:19:49,960 Speaker 1: for that message from Leaf Pain Relief. 377 00:19:50,480 --> 00:19:51,800 Speaker 2: Get the spot, it's good. 378 00:19:52,240 --> 00:19:55,520 Speaker 1: Don't eat leaves. I saw someone posing with a they 379 00:19:55,520 --> 00:19:57,960 Speaker 1: were taking their graduation pitch. Is very nice setting. I'm 380 00:19:57,960 --> 00:19:59,960 Speaker 1: not going to say the flour, I guess just in case. 381 00:20:00,119 --> 00:20:02,879 Speaker 1: You know, you can call it quite remarkable hallucinations and 382 00:20:02,920 --> 00:20:04,680 Speaker 1: it is not a good idea to be like. 383 00:20:04,680 --> 00:20:05,480 Speaker 2: Half in it. 384 00:20:05,640 --> 00:20:08,040 Speaker 1: Yeah, it's a nice looking flower. You didn't know you 385 00:20:08,119 --> 00:20:08,320 Speaker 1: might have. 386 00:20:08,600 --> 00:20:09,920 Speaker 2: Well, now I want to know what the hell you're 387 00:20:09,920 --> 00:20:11,879 Speaker 2: talking about. You're gonna tell me later. I'm assuming you 388 00:20:11,880 --> 00:20:13,879 Speaker 2: lived in California your whole life. How do you not 389 00:20:14,000 --> 00:20:14,560 Speaker 2: know this? Yeah? 390 00:20:14,640 --> 00:20:15,600 Speaker 1: It text you afterwards? 391 00:20:15,600 --> 00:20:17,480 Speaker 2: Them dandelions? Is it dandelions? 392 00:20:17,480 --> 00:20:19,040 Speaker 1: I've been told not to roses. 393 00:20:21,240 --> 00:20:23,320 Speaker 3: It reminds me though there was a TikTok video of 394 00:20:23,680 --> 00:20:26,639 Speaker 3: there's been a few of women proudly being pregnant and 395 00:20:26,800 --> 00:20:29,800 Speaker 3: ingesting talanol. And to be clear, that's an insane response 396 00:20:29,840 --> 00:20:32,800 Speaker 3: to this problem, Like, please don't take talanol as a point, 397 00:20:33,160 --> 00:20:36,280 Speaker 3: as k was saying before the break, right, Helenol does 398 00:20:36,680 --> 00:20:39,639 Speaker 3: deplete the glutathion in your body, and it is toxic 399 00:20:39,680 --> 00:20:41,480 Speaker 3: to your liver. If you're a deliver, doesn't have the 400 00:20:41,480 --> 00:20:45,440 Speaker 3: glue to thion necessary, it directly injures the liver. And 401 00:20:45,560 --> 00:20:47,520 Speaker 3: this is what happens when you take an overdose, is 402 00:20:47,560 --> 00:20:50,679 Speaker 3: it overwhelms the amount of gluteothion that your liver has 403 00:20:50,960 --> 00:20:52,240 Speaker 3: and it causes liver damage. 404 00:20:52,440 --> 00:20:56,199 Speaker 2: So in most pregnant women who want to keep the 405 00:20:56,240 --> 00:20:59,879 Speaker 2: baby are very judicious to begin with, not just like 406 00:21:00,119 --> 00:21:03,240 Speaker 2: downing shit. Willy nilly, you know what I mean? Like 407 00:21:03,280 --> 00:21:06,000 Speaker 2: they're like, oh god, this is really bad. I bear 408 00:21:06,080 --> 00:21:09,639 Speaker 2: take something and talent all, by the way, sucks, you know, 409 00:21:09,720 --> 00:21:12,520 Speaker 2: as a pain medicine. You know it's not gonna It's 410 00:21:12,560 --> 00:21:14,320 Speaker 2: like the thing you take when they won't give you 411 00:21:14,359 --> 00:21:18,160 Speaker 2: anything else that's not a great one. So to take 412 00:21:18,200 --> 00:21:22,080 Speaker 2: it from them without a good reason, without a proposed mechanism. 413 00:21:22,200 --> 00:21:25,199 Speaker 2: If you're gonna make extraordinary claims, you have to have, 414 00:21:25,840 --> 00:21:29,960 Speaker 2: if not extraordinary evidence por ponderance of it. So this 415 00:21:30,080 --> 00:21:32,359 Speaker 2: is really bothering me, as you can tell, because it 416 00:21:32,359 --> 00:21:33,040 Speaker 2: does not exist. 417 00:21:33,960 --> 00:21:36,240 Speaker 1: Yeah. I think something you mentioned earlier, like when like 418 00:21:36,280 --> 00:21:37,840 Speaker 1: you said, you're back to to a corner where you're 419 00:21:37,840 --> 00:21:42,440 Speaker 1: defending like a big farmer and tynel specifically, is the 420 00:21:42,480 --> 00:21:45,440 Speaker 1: one thing that they've tried to do is like inhabit 421 00:21:45,640 --> 00:21:49,520 Speaker 1: nuance and then disingenuously use it absolutely. 422 00:21:49,680 --> 00:21:52,480 Speaker 3: Yes, yes, that's the entire anti vaccines. 423 00:21:52,960 --> 00:21:55,520 Speaker 1: Yeah, yeah, right, and then it leads to people responding 424 00:21:55,520 --> 00:21:58,320 Speaker 1: in a way that it raises nuance entirely. I understand 425 00:21:58,359 --> 00:22:01,600 Speaker 1: where we get that response, but like it's not the 426 00:22:01,680 --> 00:22:04,679 Speaker 1: correct response, right, Yeah. People want you to be like 427 00:22:04,760 --> 00:22:07,240 Speaker 1: this is one hundred percent safe, right. They want you 428 00:22:07,359 --> 00:22:09,360 Speaker 1: to say this is actually the perfect medication and it's 429 00:22:09,400 --> 00:22:10,880 Speaker 1: fine and you should have it for breakfast. 430 00:22:11,119 --> 00:22:14,919 Speaker 3: Yeah, And the AHHS tweeted out statement that Talanol did 431 00:22:14,960 --> 00:22:19,199 Speaker 3: in twenty seventeen basically saying, we don't recommend talent all 432 00:22:19,400 --> 00:22:24,080 Speaker 3: and pregnancy. But no drug maker recommends any medication. They 433 00:22:24,160 --> 00:22:26,960 Speaker 3: all say, specifically, talk to your doctor about this medication. 434 00:22:27,040 --> 00:22:30,000 Speaker 3: They're not allowed to recommend the medication. Only doctors can't. 435 00:22:30,240 --> 00:22:33,480 Speaker 3: So when they're using that language and then HHS tweets 436 00:22:33,520 --> 00:22:36,240 Speaker 3: it out, HHS is tweeting it out specifically to give 437 00:22:36,280 --> 00:22:39,919 Speaker 3: the illusion that we don't want pregnant people to be 438 00:22:39,960 --> 00:22:42,760 Speaker 3: taking this medication. They specifically said we don't recommend it, 439 00:22:42,760 --> 00:22:45,120 Speaker 3: and that's a nuance and that's how they use it. 440 00:22:45,160 --> 00:22:45,960 Speaker 3: And it just sucks. 441 00:22:46,080 --> 00:22:48,680 Speaker 2: Right, that's exactly right, and title mall the makers of it. 442 00:22:49,080 --> 00:22:50,800 Speaker 2: By the way, I am curious about the fact that 443 00:22:50,880 --> 00:22:53,879 Speaker 2: Johnson Johnson spun Off can view. I wonder if they 444 00:22:53,960 --> 00:22:55,719 Speaker 2: knew this was coming and that's why they did it 445 00:22:55,760 --> 00:22:57,560 Speaker 2: the same way that DuPont spun Off. 446 00:22:57,640 --> 00:22:59,159 Speaker 3: It was only three years ago that they did that, 447 00:23:00,040 --> 00:23:00,440 Speaker 3: you know, more. 448 00:23:00,359 --> 00:23:02,800 Speaker 2: Like DuPont spun Off, the company in charge of all 449 00:23:02,800 --> 00:23:05,800 Speaker 2: their pfasts they're forever chemicals because they knew shit was 450 00:23:05,800 --> 00:23:07,639 Speaker 2: coming down the pipeline. I wonder if that was the 451 00:23:07,640 --> 00:23:09,000 Speaker 2: same reason here Title Law did this. 452 00:23:09,560 --> 00:23:12,680 Speaker 3: They put band aid and nutrigena in the same group, 453 00:23:12,800 --> 00:23:15,879 Speaker 3: so I think it was more just to consolidate home stuff. 454 00:23:16,320 --> 00:23:17,560 Speaker 2: Interesting. Yeah, got a. 455 00:23:17,480 --> 00:23:20,520 Speaker 1: Press conference coming next week about band aid. 456 00:23:20,800 --> 00:23:26,119 Speaker 2: It's can sick cause anxiety. Anyways, It's very interesting to 457 00:23:26,160 --> 00:23:30,280 Speaker 2: me that this is happening at all. Really. I mean, 458 00:23:30,320 --> 00:23:33,520 Speaker 2: what I thought was interesting about the press conference, and 459 00:23:33,560 --> 00:23:35,600 Speaker 2: I wonder if you guys picked up on this too, 460 00:23:36,480 --> 00:23:39,160 Speaker 2: was you know, I was wondering, why is this pivot happening? 461 00:23:39,200 --> 00:23:41,760 Speaker 2: How can RFK Junior be happy about this? He can't 462 00:23:41,760 --> 00:23:45,240 Speaker 2: be happy about leaving his crusade against vaccine. The Mohawk 463 00:23:45,240 --> 00:23:48,919 Speaker 2: community behind him clearly doesn't love that aspect, and I 464 00:23:48,960 --> 00:23:51,119 Speaker 2: wonder why they were pivoting to that, And I wonder 465 00:23:51,440 --> 00:23:53,919 Speaker 2: what you guys think about that. I did feel that 466 00:23:54,080 --> 00:23:56,800 Speaker 2: during that press conference, Trump really went out of his 467 00:23:56,880 --> 00:24:00,480 Speaker 2: way to sort of give lip service we should we 468 00:24:00,480 --> 00:24:03,640 Speaker 2: should talk about this too, about vaccines. He talked about 469 00:24:03,720 --> 00:24:05,840 Speaker 2: vaccines a lot, even though there's no new evidence about 470 00:24:05,920 --> 00:24:10,080 Speaker 2: vaccines causing problems, and Trump gave this terrible advice about 471 00:24:10,119 --> 00:24:12,760 Speaker 2: breaking up the vaccines, which we know is a terrible 472 00:24:12,800 --> 00:24:15,240 Speaker 2: idea because that's going to lead to decrease uptake overall, 473 00:24:15,280 --> 00:24:17,040 Speaker 2: the more visits you have to go back to, the 474 00:24:17,119 --> 00:24:18,840 Speaker 2: less likely you're going to do it, so the more 475 00:24:18,920 --> 00:24:21,120 Speaker 2: likely you're not going to be vaccinated. But it made 476 00:24:21,200 --> 00:24:24,680 Speaker 2: me wonder why this is happening now, why they decided 477 00:24:24,720 --> 00:24:28,240 Speaker 2: to make this pivot, and I wonder what you both 478 00:24:28,320 --> 00:24:29,120 Speaker 2: think about that. 479 00:24:30,320 --> 00:24:33,320 Speaker 3: My theory is the link with fevers. If I'm being 480 00:24:33,359 --> 00:24:37,680 Speaker 3: really conspiratorial, I would say that they're going to try 481 00:24:37,720 --> 00:24:42,760 Speaker 3: and link vaccine induced fever to autism, and they're going 482 00:24:42,840 --> 00:24:45,320 Speaker 3: to say, oh, we thought it was the tile and all, 483 00:24:45,400 --> 00:24:47,000 Speaker 3: but it turns out to be the vaccines. 484 00:24:47,880 --> 00:24:49,600 Speaker 2: It's the fever, and the fever is caused by the 485 00:24:49,680 --> 00:24:51,280 Speaker 2: vaccine gines. Yeah. 486 00:24:51,359 --> 00:24:55,320 Speaker 1: Yeah, My theory is gender. I think that telling pregnant 487 00:24:55,359 --> 00:24:58,240 Speaker 1: people to suck it up is then you've got you know, 488 00:24:58,280 --> 00:25:00,919 Speaker 1: you're dude still standing on the podium there, right, You're 489 00:25:00,920 --> 00:25:03,640 Speaker 1: pregnant people are going to be women. It's something that 490 00:25:03,720 --> 00:25:06,840 Speaker 1: men have been doing to women for millennia. Like it's 491 00:25:06,840 --> 00:25:09,639 Speaker 1: a safer bet than yeah, your kid might die, but 492 00:25:09,760 --> 00:25:10,440 Speaker 1: you know, you never know. 493 00:25:11,280 --> 00:25:14,280 Speaker 2: Yeah, yeah, which actually is you know. That brings up 494 00:25:14,280 --> 00:25:15,880 Speaker 2: another thing that I think we should talk about, which 495 00:25:15,920 --> 00:25:19,119 Speaker 2: is what Trump kept saying. Trump kept saying, don't take it, 496 00:25:19,119 --> 00:25:21,399 Speaker 2: but he was like, what's the worst that happens? Nothing 497 00:25:21,480 --> 00:25:25,560 Speaker 2: bad will come of it. So it invokes this precautionary principle, 498 00:25:25,640 --> 00:25:29,119 Speaker 2: which is like, you know, why not avoid the talent all, 499 00:25:29,400 --> 00:25:33,040 Speaker 2: what's the worst that can happen? And that doesn't work here. No, 500 00:25:33,280 --> 00:25:35,520 Speaker 2: because we know that people are taking this for a fever. 501 00:25:36,119 --> 00:25:38,320 Speaker 2: Tal Law is not good for inflammation, doesn't work on 502 00:25:38,359 --> 00:25:41,080 Speaker 2: inflammation the way advilbbiprofene does it. But it can work 503 00:25:41,080 --> 00:25:44,360 Speaker 2: on a fever. And we know that fever can have 504 00:25:44,880 --> 00:25:47,919 Speaker 2: some risk at least as much, if not more than 505 00:25:48,000 --> 00:25:54,480 Speaker 2: tilentol in harm to the baby, in harm to the pregnancy. 506 00:25:54,960 --> 00:25:58,879 Speaker 2: So to me, the precautionary principle just doesn't apply here. 507 00:25:59,359 --> 00:26:01,520 Speaker 2: And to hear the president, I never heard a president 508 00:26:01,560 --> 00:26:04,879 Speaker 2: give medical advice before like that. It blew my mind. 509 00:26:04,960 --> 00:26:07,720 Speaker 2: I felt like I was disassociating while I was watching this. 510 00:26:07,760 --> 00:26:10,359 Speaker 2: I'm like, this cannot be realized. He said it so unequivocally, 511 00:26:10,440 --> 00:26:11,400 Speaker 2: don't take talentol. 512 00:26:11,480 --> 00:26:15,120 Speaker 3: Just it up. And I tweeted something that I read 513 00:26:15,160 --> 00:26:19,080 Speaker 3: from doctor Glockenplocken, who's one of my favorite medical comedians. 514 00:26:19,600 --> 00:26:22,720 Speaker 3: But he said this will kill people, and I do agree. 515 00:26:22,840 --> 00:26:25,560 Speaker 3: I think people were very incredulous when I when I 516 00:26:25,600 --> 00:26:27,199 Speaker 3: said this will kill people, and they were like, what 517 00:26:27,200 --> 00:26:29,440 Speaker 3: do you mean people dying of a fever. I'm like, yeah, 518 00:26:29,520 --> 00:26:32,399 Speaker 3: kind of like fevers can be really bad for you. 519 00:26:32,440 --> 00:26:34,320 Speaker 3: And if you're not going to hospital and the only 520 00:26:34,359 --> 00:26:36,800 Speaker 3: thing you have is talentol, it's a really good idea 521 00:26:36,840 --> 00:26:38,280 Speaker 3: to take the talent ol. And there's some people that 522 00:26:38,359 --> 00:26:41,160 Speaker 3: don't go to hospital for lots of reasons, and fevers 523 00:26:41,200 --> 00:26:42,320 Speaker 3: can kill you. They just can. 524 00:26:42,520 --> 00:26:42,960 Speaker 4: Yeah. 525 00:26:43,000 --> 00:26:46,680 Speaker 2: So I disapprove of the Canadian and englishmen referring to 526 00:26:46,720 --> 00:26:50,119 Speaker 2: the hospital as hospital. They need you guys to refer 527 00:26:50,160 --> 00:26:51,400 Speaker 2: to it as of the hospital. 528 00:26:51,400 --> 00:26:53,879 Speaker 1: Forgotten about that? Yeah, always for the definite article. 529 00:26:54,000 --> 00:26:56,480 Speaker 3: Yeah, taking it to a hospital, Thank you guys. 530 00:26:56,880 --> 00:26:58,600 Speaker 1: But yeah, I think you're right like that. There is 531 00:26:58,680 --> 00:27:01,399 Speaker 1: no like no harm option here, right, like that is 532 00:27:01,440 --> 00:27:04,760 Speaker 1: a damage is done when people don't take this, right. 533 00:27:04,960 --> 00:27:08,200 Speaker 3: I just imagine this this poor mom you know at home, 534 00:27:08,359 --> 00:27:10,720 Speaker 3: you know doesn't have great healthcare, but does have a 535 00:27:10,720 --> 00:27:14,760 Speaker 3: bottle of talentol and is battling a sorry, I'll americanize 536 00:27:14,760 --> 00:27:16,600 Speaker 3: this like one hundred and four degree fever. 537 00:27:17,080 --> 00:27:18,520 Speaker 2: Thank you don't make me do mad? 538 00:27:18,680 --> 00:27:21,480 Speaker 3: Yeah, you're to make me do mad, you know. And 539 00:27:21,480 --> 00:27:23,200 Speaker 3: and you know, it's it's around that one hundred and 540 00:27:23,200 --> 00:27:25,120 Speaker 3: three hundred and four mark where we actually get really 541 00:27:25,160 --> 00:27:28,040 Speaker 3: worried about the person's brain. We get really worried about 542 00:27:28,040 --> 00:27:30,880 Speaker 3: their health and what's going to happen, and what would 543 00:27:30,920 --> 00:27:33,720 Speaker 3: happen to that person in hospital? They would absolutely get 544 00:27:33,760 --> 00:27:36,520 Speaker 3: talent al right away, prescribed by a doctor right that moment. 545 00:27:37,160 --> 00:27:39,879 Speaker 3: And so I worry about this. I worry about this 546 00:27:39,960 --> 00:27:43,359 Speaker 3: mom presenting a hospital with her fever. She's pregnant, and 547 00:27:43,359 --> 00:27:45,160 Speaker 3: the doctors say, okay, we're going to give you talinol, 548 00:27:45,160 --> 00:27:47,000 Speaker 3: and she says, no, you're right, what because I don't 549 00:27:47,000 --> 00:27:49,000 Speaker 3: want I don't want my child to have autism? Because 550 00:27:49,000 --> 00:27:51,520 Speaker 3: people are listening to this guy. First of all, again 551 00:27:51,760 --> 00:27:54,560 Speaker 3: the hospital. Second, they're going to listen to this guy. 552 00:27:54,800 --> 00:27:55,600 Speaker 2: It's insane. 553 00:27:56,000 --> 00:27:59,000 Speaker 3: People are really going to take this advice. And I 554 00:27:59,040 --> 00:28:03,200 Speaker 3: could see, you know, especially the more Trump following people 555 00:28:03,720 --> 00:28:07,000 Speaker 3: saying you will never give me talentol, not in this hospital, right, 556 00:28:07,160 --> 00:28:10,800 Speaker 3: And so it does sound silly that not taking talentol 557 00:28:10,840 --> 00:28:13,200 Speaker 3: could kill you. But if you're so scared of talentol 558 00:28:13,200 --> 00:28:15,640 Speaker 3: because it causes autism that you don't take it when 559 00:28:15,640 --> 00:28:18,240 Speaker 3: it's recommended to you by a doctor, where it's prescribed 560 00:28:18,280 --> 00:28:21,760 Speaker 3: to you by doctor, you could die. And I won't 561 00:28:21,760 --> 00:28:24,959 Speaker 3: be surprised when there are more fever induced deaths in 562 00:28:25,040 --> 00:28:27,320 Speaker 3: twenty twenty five and twenty twenty six in the United States. 563 00:28:27,359 --> 00:28:30,280 Speaker 3: I already have the CDC Wonder Data search ready to 564 00:28:30,320 --> 00:28:33,080 Speaker 3: go because I study mortality all the time, and I 565 00:28:33,119 --> 00:28:36,040 Speaker 3: am absolutely sure we're going to see a few more 566 00:28:36,200 --> 00:28:38,160 Speaker 3: fever induced deaths than we would have previously. 567 00:28:38,680 --> 00:28:53,600 Speaker 1: Geez, yeah, maybe like we can finish up by explaining 568 00:28:53,640 --> 00:28:56,200 Speaker 1: to people like, you know, if you're talking to someone 569 00:28:56,200 --> 00:28:59,479 Speaker 1: in your family, right, someone who maybe isn't a listener 570 00:29:00,720 --> 00:29:03,360 Speaker 1: to either of our podcasts. I know this isn't directly 571 00:29:03,400 --> 00:29:06,960 Speaker 1: the area either of you specializing, but from what I understand, 572 00:29:07,120 --> 00:29:10,560 Speaker 1: pregnant people like the way that drugs are categorized, as 573 00:29:10,560 --> 00:29:12,880 Speaker 1: we spoke about earlier on. There's not like, yeah, go 574 00:29:12,880 --> 00:29:16,120 Speaker 1: ahead and take all of these, right, there's like probably 575 00:29:16,160 --> 00:29:19,560 Speaker 1: fine if you have to, probably a bad idea unless 576 00:29:19,560 --> 00:29:24,000 Speaker 1: you really need to, and like maybe some straight up don't. Yeah, 577 00:29:24,080 --> 00:29:25,520 Speaker 1: can you explain that for people? 578 00:29:25,760 --> 00:29:28,920 Speaker 3: Sure, So there's a classification system and it's technical, but 579 00:29:28,960 --> 00:29:31,960 Speaker 3: it's exactly like that. There are very few medications that 580 00:29:32,040 --> 00:29:36,520 Speaker 3: are like totally fine. These are medications that are given 581 00:29:36,800 --> 00:29:40,440 Speaker 3: during pregnancy that have been well studied in pregnancy. But 582 00:29:40,760 --> 00:29:42,760 Speaker 3: for the most part, pretty much everything else in my 583 00:29:42,800 --> 00:29:47,760 Speaker 3: world of psychiatry, you know, SSRIs and antipsychotics and benzodiazepines 584 00:29:47,800 --> 00:29:50,960 Speaker 3: and whatnot, they all have the same classification, which is 585 00:29:51,000 --> 00:29:55,120 Speaker 3: basically contraindicated, don't take it unless your doctor persudes it 586 00:29:55,200 --> 00:29:59,000 Speaker 3: for you. Now, we still get pregnant people with depression 587 00:29:59,040 --> 00:30:02,479 Speaker 3: and psychosis and who need all these medications, and so 588 00:30:02,560 --> 00:30:05,280 Speaker 3: we do have to interpret it based off of the 589 00:30:05,400 --> 00:30:07,760 Speaker 3: data that we have, and the data that we have 590 00:30:07,840 --> 00:30:10,240 Speaker 3: always comes late, so if we find a problem, it's 591 00:30:10,280 --> 00:30:15,040 Speaker 3: found too late, and generally it's precautionary. So typically I 592 00:30:15,080 --> 00:30:18,320 Speaker 3: don't know cave if there's a similar thing in GI work, 593 00:30:18,400 --> 00:30:20,960 Speaker 3: But like for me, I'll get a call all the time. Well, 594 00:30:21,000 --> 00:30:23,880 Speaker 3: we have this woman, she's thirty two, she's really worried. 595 00:30:24,280 --> 00:30:27,320 Speaker 3: She normally takes antidepressants, but she's thinking about stopping them 596 00:30:27,360 --> 00:30:29,760 Speaker 3: because she's really worried about passing into her baby or whatever. 597 00:30:30,240 --> 00:30:33,400 Speaker 3: And I'm like, how bad is the depression. Well, it 598 00:30:33,440 --> 00:30:35,600 Speaker 3: was really bad. She was hospitalized three times and nearly died. 599 00:30:35,640 --> 00:30:38,720 Speaker 3: I was like, probably want to keep antidepressant treatment going 600 00:30:38,800 --> 00:30:40,719 Speaker 3: and just let her know that there could be some 601 00:30:40,760 --> 00:30:43,800 Speaker 3: harm to the fetus. But depression is way worse. And 602 00:30:44,320 --> 00:30:46,640 Speaker 3: if we just go with God, you know, do your best. 603 00:30:47,480 --> 00:30:50,000 Speaker 2: There are certain medications where we are going to say 604 00:30:50,080 --> 00:30:53,480 Speaker 2: you absolute should take these during pregnancy. Yeah, and you 605 00:30:53,480 --> 00:30:58,040 Speaker 2: should discuss that with your obstrician, to talk that over 606 00:30:58,080 --> 00:31:01,720 Speaker 2: with yourcologist and your your primary care doctor. You should 607 00:31:01,720 --> 00:31:03,880 Speaker 2: talk it over with your medical team. That's great, But 608 00:31:04,520 --> 00:31:09,320 Speaker 2: every medication has some small amount of risk, some larger 609 00:31:09,360 --> 00:31:12,840 Speaker 2: than others. But it's really about the risk versus the benefit. 610 00:31:13,680 --> 00:31:17,160 Speaker 2: And this has been well studied by the experts, and 611 00:31:17,840 --> 00:31:21,280 Speaker 2: what you've heard, what those people have heard from Trump 612 00:31:21,720 --> 00:31:26,680 Speaker 2: and RFK Junior is well outside of the normal recommendations 613 00:31:27,080 --> 00:31:31,440 Speaker 2: from the experts like the ACOG, the American College of Obstetricians, 614 00:31:31,440 --> 00:31:36,120 Speaker 2: and kindecologists, the people who have been keeping our pregnant 615 00:31:36,120 --> 00:31:40,440 Speaker 2: patients alive and relatively well for many many years. This 616 00:31:40,640 --> 00:31:43,840 Speaker 2: is well outside of those recommendations. And while it's an 617 00:31:43,880 --> 00:31:47,600 Speaker 2: interesting topic and I think, maybe, you know, sure, i'd 618 00:31:47,680 --> 00:31:49,520 Speaker 2: like to see more studies on it, I'm never going 619 00:31:49,600 --> 00:31:52,520 Speaker 2: to say don't study this more. I would say that 620 00:31:52,560 --> 00:31:56,240 Speaker 2: the preponderance of evidence and scientific belief and medical belief 621 00:31:56,280 --> 00:31:59,280 Speaker 2: in this one goes against what they're saying. And I 622 00:31:59,320 --> 00:32:02,360 Speaker 2: would say, least talk it over with your doctor. If 623 00:32:02,400 --> 00:32:04,320 Speaker 2: you have a question, talk it over with your doctor. 624 00:32:04,840 --> 00:32:07,280 Speaker 2: And that's you mentioned it before. Town law has sort 625 00:32:07,280 --> 00:32:11,120 Speaker 2: of like, you know, try to hedge its bets by saying, 626 00:32:11,160 --> 00:32:12,960 Speaker 2: talk it over with your doctor. But the reason they 627 00:32:13,000 --> 00:32:15,200 Speaker 2: do that is they know most doctors are going to 628 00:32:15,200 --> 00:32:18,760 Speaker 2: be reasonable about this and follow the scientific evidence that's there. 629 00:32:19,200 --> 00:32:21,680 Speaker 2: So I would say if they really have a question, 630 00:32:21,720 --> 00:32:24,360 Speaker 2: they should talk about with their doctor. Because Trump, whether 631 00:32:24,440 --> 00:32:26,600 Speaker 2: or not they love him or not, this is well 632 00:32:26,640 --> 00:32:30,560 Speaker 2: out of his range of understanding, and he is getting 633 00:32:31,040 --> 00:32:34,440 Speaker 2: It's like a game of telephone. He's getting a version 634 00:32:34,760 --> 00:32:38,440 Speaker 2: of the medical information transmit to him by RFK Junior, 635 00:32:38,720 --> 00:32:42,280 Speaker 2: who is getting a weird version of it from his 636 00:32:42,440 --> 00:32:45,320 Speaker 2: belief system, and it's being supported by people who are 637 00:32:45,320 --> 00:32:50,320 Speaker 2: there solely just just there to do the beck and 638 00:32:50,400 --> 00:32:53,920 Speaker 2: call of Trump at this point, and that's super dangerous. 639 00:32:54,160 --> 00:32:56,600 Speaker 2: And so if they can keep an open mind about it, 640 00:32:56,720 --> 00:32:59,120 Speaker 2: talk it over with their doctor, continues to do what 641 00:32:59,160 --> 00:33:02,120 Speaker 2: their parents did, I think they're going to be okay. 642 00:33:02,480 --> 00:33:06,000 Speaker 1: Yeah, real quick, because like for reasons that are life 643 00:33:06,000 --> 00:33:07,640 Speaker 1: you related to the way that we do healthcare in 644 00:33:07,680 --> 00:33:10,120 Speaker 1: the United States, people sometimes are retident to talk to 645 00:33:10,160 --> 00:33:13,360 Speaker 1: their doctor, unable to talk to a doctor. Reliable sources 646 00:33:13,400 --> 00:33:16,720 Speaker 1: of medical information versus the shit that you find on Google. 647 00:33:16,800 --> 00:33:18,400 Speaker 1: Give us like a five minute primer. 648 00:33:18,800 --> 00:33:19,000 Speaker 2: Yeah. 649 00:33:19,280 --> 00:33:22,719 Speaker 3: So you know, in almost every jurisdiction there is an 650 00:33:22,720 --> 00:33:25,760 Speaker 3: official health agency that you can go to their website 651 00:33:25,800 --> 00:33:28,960 Speaker 3: and get good health data. So in BC, we have 652 00:33:29,000 --> 00:33:32,280 Speaker 3: Health Length BC and there's a number that you can 653 00:33:32,320 --> 00:33:34,920 Speaker 3: call to speak to a nurse. In America, you have 654 00:33:35,040 --> 00:33:36,800 Speaker 3: great I would say it used to be great. Like 655 00:33:36,840 --> 00:33:38,479 Speaker 3: Cleveland Clinic used to be really great, but they got 656 00:33:38,480 --> 00:33:41,080 Speaker 3: a little hokey. I would still say, you know, there 657 00:33:41,080 --> 00:33:43,680 Speaker 3: are some really good American places that you can go. 658 00:33:44,200 --> 00:33:47,080 Speaker 3: Male Clinic has a lot of public facing information that 659 00:33:47,160 --> 00:33:51,360 Speaker 3: has pretty good general descriptions, but just make sure it's 660 00:33:51,400 --> 00:33:55,320 Speaker 3: from a place that is official because there is a 661 00:33:55,360 --> 00:33:58,240 Speaker 3: whole space now that's going to be opened up because 662 00:33:58,280 --> 00:34:01,360 Speaker 3: the second part of this present that RFK gave was 663 00:34:01,960 --> 00:34:05,560 Speaker 3: about a generic medication that might help some people with 664 00:34:05,600 --> 00:34:08,560 Speaker 3: a very specific form of autism. And I promise you 665 00:34:08,640 --> 00:34:11,560 Speaker 3: the amount of huckstering that's going to happen based on that. 666 00:34:12,239 --> 00:34:14,400 Speaker 3: The alternatives. You know, we made a joke about lemon 667 00:34:14,440 --> 00:34:17,319 Speaker 3: water before the ad break, but there are going to 668 00:34:17,360 --> 00:34:19,880 Speaker 3: be people who are going to be selling the alternative 669 00:34:19,920 --> 00:34:24,720 Speaker 3: titalinol that is autism free, and that's really worrisome. 670 00:34:24,960 --> 00:34:31,080 Speaker 2: Yeah, be wary of anyone that has something in their Instagram, 671 00:34:31,640 --> 00:34:36,520 Speaker 2: their talk, their wellness post that uses the words detox. 672 00:34:37,239 --> 00:34:41,880 Speaker 2: Be wary about ancient remedies. Be wary about anyone that 673 00:34:42,040 --> 00:34:44,640 Speaker 2: is selling something like doctor Oz, who, by the way, 674 00:34:45,040 --> 00:34:47,799 Speaker 2: sells a version of the full linic acid or the 675 00:34:47,880 --> 00:34:52,640 Speaker 2: leucovorin that they're talking about here, So be wary about that. 676 00:34:52,680 --> 00:34:56,319 Speaker 2: We don't sell shit. Be wary about people like doctor Baccarelli, 677 00:34:56,400 --> 00:34:59,440 Speaker 2: the dean of Harvard Epidemiology, who, by the way, I've 678 00:34:59,440 --> 00:35:02,920 Speaker 2: heard is a doctor from the friends I have in Harvard, 679 00:35:02,960 --> 00:35:05,280 Speaker 2: they say he's not a bad guy. But be worry 680 00:35:05,320 --> 00:35:07,600 Speaker 2: about the fact anytime you see someone's making one hundred 681 00:35:07,640 --> 00:35:10,200 Speaker 2: and fifty thousand dollars off of court trial to sue 682 00:35:10,520 --> 00:35:14,000 Speaker 2: tail and all and has a vested interest in these things, 683 00:35:14,600 --> 00:35:18,360 Speaker 2: so you should be worry about those things. That's definitely 684 00:35:18,360 --> 00:35:21,360 Speaker 2: something to look for in if you're looking for trusted source. 685 00:35:21,680 --> 00:35:24,360 Speaker 2: Speaking of hucksters, you could listen to my podcast The 686 00:35:24,360 --> 00:35:27,400 Speaker 2: House of Pod anywhere you find podcasts where we're going 687 00:35:27,440 --> 00:35:30,279 Speaker 2: to talk about medical stuff just like this, and I 688 00:35:30,280 --> 00:35:31,720 Speaker 2: will bring you trusted sources. 689 00:35:32,320 --> 00:35:34,719 Speaker 1: Beautiful. That's that was all a long play to get 690 00:35:34,760 --> 00:35:36,320 Speaker 1: to listen to Kave's podcast. 691 00:35:36,560 --> 00:35:37,960 Speaker 2: I'm in it for the long con. I'm in it 692 00:35:38,000 --> 00:35:38,960 Speaker 2: for the long con, buddy. 693 00:35:39,040 --> 00:35:41,279 Speaker 1: Yeah, thank you for helping us clear that up a bit. 694 00:35:41,400 --> 00:35:44,960 Speaker 1: I think it's it's a real rough time for healthcare 695 00:35:45,000 --> 00:35:48,680 Speaker 1: in general, and especially people with autism, like like well 696 00:35:48,760 --> 00:35:52,319 Speaker 1: nero divergent people. It really fucking sucks to see the 697 00:35:52,440 --> 00:35:56,440 Speaker 1: entire federal government bad mouthing people. So, yeah, we are 698 00:35:56,480 --> 00:35:57,080 Speaker 1: thinking of. 699 00:35:57,000 --> 00:36:00,840 Speaker 3: You, very similar to the issue with trans kids. Like 700 00:36:01,280 --> 00:36:03,239 Speaker 3: I'm a Canadian, you know, and we have right next 701 00:36:03,239 --> 00:36:07,560 Speaker 3: door to my province, Alberta, which is very much taking 702 00:36:07,600 --> 00:36:09,600 Speaker 3: the route of Florida and other things with respect to 703 00:36:09,640 --> 00:36:12,120 Speaker 3: trans policies, and it's just got to suck to be 704 00:36:12,160 --> 00:36:14,880 Speaker 3: a trans kid in Florida right now. It's got to 705 00:36:14,920 --> 00:36:17,600 Speaker 3: suck to be a trans kid anywhere in America right now, 706 00:36:18,000 --> 00:36:20,239 Speaker 3: knowing what's coming down the pipeline. And it'll be the 707 00:36:20,239 --> 00:36:23,319 Speaker 3: same for people with autism and families with autistic kids. 708 00:36:24,040 --> 00:36:28,000 Speaker 2: Yeah, yep. I could conservatively complain about this for another 709 00:36:28,040 --> 00:36:28,680 Speaker 2: three hours. 710 00:36:29,320 --> 00:36:30,319 Speaker 1: Yeah, yeah, yeah. 711 00:36:30,400 --> 00:36:32,600 Speaker 2: We didn't even talk about hepatitis B. By the way, 712 00:36:32,719 --> 00:36:34,880 Speaker 2: we even talk about hepatities. People can talk about this 713 00:36:34,880 --> 00:36:37,480 Speaker 2: on the point. There's just so much. There's so much, 714 00:36:37,760 --> 00:36:41,359 Speaker 2: and it's so terrible, and you're absolutely right, it's really 715 00:36:41,480 --> 00:36:43,080 Speaker 2: like for that community right now. 716 00:36:43,239 --> 00:36:46,480 Speaker 3: By the way, I wanted to debunk something because it's 717 00:36:46,480 --> 00:36:47,640 Speaker 3: been said multiple times. 718 00:36:47,760 --> 00:36:48,560 Speaker 1: Yeah, yeah, I get it. 719 00:36:48,680 --> 00:36:50,880 Speaker 3: RFK and a whole bunch of people have said, I 720 00:36:50,920 --> 00:36:54,759 Speaker 3: didn't know anybody autistic when I was you know, when 721 00:36:54,800 --> 00:36:56,560 Speaker 3: I was a kid or whatever. I've never met someone 722 00:36:56,560 --> 00:37:00,680 Speaker 3: autistic my age. Donald Triplett was the very first person 723 00:37:00,760 --> 00:37:04,880 Speaker 3: diagnosed with autism in nineteen forty three, I believe nineteen 724 00:37:04,920 --> 00:37:08,239 Speaker 3: forty three. He just died last year. I think he 725 00:37:08,440 --> 00:37:13,640 Speaker 3: was something like eighty ninety years old. Okay, autistic people 726 00:37:13,719 --> 00:37:17,440 Speaker 3: are old too. This idea that there aren't old autistic 727 00:37:17,480 --> 00:37:22,520 Speaker 3: people is so asked backwards. It was just not diagnosed. Yes, 728 00:37:22,800 --> 00:37:28,640 Speaker 3: And it's such a shame because when Donald Triplett passed, 729 00:37:28,680 --> 00:37:30,839 Speaker 3: you know, like people in psychiatry notes, that's not the 730 00:37:30,880 --> 00:37:32,680 Speaker 3: type of thing that people in the world noticed. But 731 00:37:32,719 --> 00:37:35,400 Speaker 3: he was the very first autistic person. He lived a 732 00:37:35,440 --> 00:37:38,600 Speaker 3: full life, he was an engineer. He had autism, it 733 00:37:38,640 --> 00:37:41,440 Speaker 3: was diagnosed. He was the first ever case diagnosed, and 734 00:37:41,480 --> 00:37:45,440 Speaker 3: he also lived a life. And so for rfk to 735 00:37:45,600 --> 00:37:48,640 Speaker 3: just erase him completely and say I've never known an 736 00:37:48,640 --> 00:37:51,279 Speaker 3: old person to have autism is just ridiculous. 737 00:37:51,640 --> 00:37:54,640 Speaker 1: Yeah, and if you conduct yourself as Rskade does, but 738 00:37:54,800 --> 00:37:57,399 Speaker 1: being a piece of shit to neurodivergent people, then even 739 00:37:57,440 --> 00:37:59,839 Speaker 1: people who have been diagnosed, I'm just going to be like, hey, 740 00:38:00,000 --> 00:38:01,440 Speaker 1: and yeah, I wanted to talk to you about more 741 00:38:01,600 --> 00:38:04,680 Speaker 1: about life because you're being a turn to them and 742 00:38:04,719 --> 00:38:07,680 Speaker 1: like you're being unkind, Yeah, like what do you expect? 743 00:38:07,880 --> 00:38:12,719 Speaker 2: Yeah, I mean, yeah, Tyler Brandon is like how old 744 00:38:12,920 --> 00:38:15,680 Speaker 2: is she now? Like in her seventies. I mean, it's 745 00:38:15,719 --> 00:38:19,359 Speaker 2: it's absurd to think that this is a totally new thing. 746 00:38:19,520 --> 00:38:22,840 Speaker 2: I mean, it also tells me that he was probably 747 00:38:22,880 --> 00:38:26,160 Speaker 2: a bit sheltered and it probably didn't mean enough people. 748 00:38:26,160 --> 00:38:27,480 Speaker 3: Wow Kennedy sheltered? 749 00:38:27,520 --> 00:38:30,759 Speaker 1: Well yeah, yeah, he's had a different experience of life 750 00:38:30,800 --> 00:38:33,279 Speaker 1: than any of us. It's fair to say. 751 00:38:33,200 --> 00:38:35,320 Speaker 3: I got through the whole podcast without making a toddler 752 00:38:35,360 --> 00:38:37,760 Speaker 3: and all pun. I'm very proud of that. I usually 753 00:38:37,800 --> 00:38:39,920 Speaker 3: do pretty much every time, and it kisses my wife 754 00:38:39,920 --> 00:38:40,560 Speaker 3: off so much. 755 00:38:41,960 --> 00:38:42,799 Speaker 2: I'm really proud of you. 756 00:38:42,840 --> 00:38:43,000 Speaker 1: Man. 757 00:38:43,080 --> 00:38:44,160 Speaker 2: You showed a lot of growth. 758 00:38:44,280 --> 00:38:47,000 Speaker 1: Yeah, yeah, that's great. I was gonna make one, but 759 00:38:47,360 --> 00:38:52,640 Speaker 1: I didn't want to want to offend. Yeah, thank you 760 00:38:52,719 --> 00:38:55,279 Speaker 1: very much. Where can people find both of you on 761 00:38:55,560 --> 00:38:57,960 Speaker 1: the internet if they'd like to, oh, you know, in person? 762 00:38:58,960 --> 00:39:02,160 Speaker 2: Don't find me? Yeah, I give that as You can 763 00:39:02,200 --> 00:39:04,920 Speaker 2: listen to my podcast, The House of Pod. Anywhere you 764 00:39:04,960 --> 00:39:07,400 Speaker 2: listen to podcasts, you'll hear people like James, you'll hear 765 00:39:07,440 --> 00:39:09,960 Speaker 2: people like Tyler. Last time Tyler was on was actually 766 00:39:10,000 --> 00:39:13,680 Speaker 2: for episode two eighty four. We did an episode on 767 00:39:13,800 --> 00:39:18,640 Speaker 2: Adult ADHD with author Rex King. She's rad So that's 768 00:39:18,680 --> 00:39:21,160 Speaker 2: a good episode to listen to. And you can find 769 00:39:21,160 --> 00:39:24,040 Speaker 2: me on Blue Sky at CAVEMD. I still have a 770 00:39:24,239 --> 00:39:26,560 Speaker 2: Twitter account and Instagram account, but I don't really use 771 00:39:26,560 --> 00:39:28,680 Speaker 2: those that much. So find me on Blue Sky Blue Sky, 772 00:39:28,719 --> 00:39:31,240 Speaker 2: by the way as a shout out, as a plug. 773 00:39:31,480 --> 00:39:33,799 Speaker 2: I think it's good for science if you're interested in 774 00:39:33,880 --> 00:39:37,480 Speaker 2: science based stuff. It may not be that much fun 775 00:39:37,520 --> 00:39:39,640 Speaker 2: for everything else, but at least in terms of like 776 00:39:39,760 --> 00:39:42,640 Speaker 2: if you want to follow doctors scientists, that's a good 777 00:39:42,640 --> 00:39:44,440 Speaker 2: place to go. That's that's where a lot of us 778 00:39:44,440 --> 00:39:47,880 Speaker 2: have gone. So I'll be there at Blue Sky. 779 00:39:48,000 --> 00:39:50,919 Speaker 3: Yeah, and I'm I am still on Twitter Tyler Black 780 00:39:50,960 --> 00:39:53,640 Speaker 3: thirty two. I'm slugging it out. It is a lot 781 00:39:53,680 --> 00:39:56,040 Speaker 3: of hate and a lot of death threats now, especially 782 00:39:56,120 --> 00:39:59,160 Speaker 3: as I've I've been on a few trans podcasts, I've 783 00:39:59,160 --> 00:40:03,040 Speaker 3: been on quite a few medical anti vacs and vaccine podcasts, 784 00:40:03,080 --> 00:40:06,239 Speaker 3: So you know, I'll pop up from time to time 785 00:40:06,280 --> 00:40:08,400 Speaker 3: on a podcast or something, but I'm not really have 786 00:40:08,480 --> 00:40:13,200 Speaker 3: anything to plug anymore. I'm just really hoping that we 787 00:40:13,239 --> 00:40:17,040 Speaker 3: can continue to fight this sort of It's a really 788 00:40:17,120 --> 00:40:20,840 Speaker 3: disgusting reality in this decade that misinformation has won the 789 00:40:20,880 --> 00:40:24,560 Speaker 3: day and literally misinformers are the political leaders now, and 790 00:40:24,719 --> 00:40:28,719 Speaker 3: misinformation has just eroded science to the point where I 791 00:40:28,719 --> 00:40:30,439 Speaker 3: don't know if America is ever going to get it back. 792 00:40:31,160 --> 00:40:34,040 Speaker 2: Yeah, if we do, this has set us back many years. 793 00:40:34,480 --> 00:40:36,839 Speaker 2: This has set us back many many years. Yeah, it's 794 00:40:36,880 --> 00:40:37,480 Speaker 2: pretty bleak. 795 00:40:38,239 --> 00:40:39,360 Speaker 3: Well that was fun. 796 00:40:39,800 --> 00:40:47,839 Speaker 1: De's send on that hopeful note. Yeah, all right, it. 797 00:40:47,800 --> 00:40:50,160 Speaker 5: Could happen Here is a production or Cool Zone Media. 798 00:40:50,360 --> 00:40:53,440 Speaker 5: For more podcasts from Cool Zone Media, visit our website 799 00:40:53,480 --> 00:40:57,080 Speaker 5: Coolzonemedia dot com, or check us out on the iHeartRadio app, 800 00:40:57,160 --> 00:41:00,680 Speaker 5: Apple Podcasts, or wherever you listen to podcasts. You can 801 00:41:00,760 --> 00:41:03,080 Speaker 5: now find sources for It Could Happen here, listed directly 802 00:41:03,120 --> 00:41:05,400 Speaker 5: in episode descriptions. Thanks for listening.