Vollständiges Transkript von 135: Continuous Glucose Monitors: Can Tracking Blood Sugars Improve Your Health?

ended up in like a billion appointments, specialist appointments. 00:04:38.720 --> 00:04:40.720 And I was like, Do you have a blood pressure log? 00:04:40.800 --> 00:04:41.600 And he's like, Yeah. 00:04:41.759 --> 00:04:46.879 And he like whipped it out of a manila folder, and he's like, This is what it is on the days that I don't take it at home. 00:04:46.959 --> 00:04:49.360 And the guy was like, Rocking 120s over 70s. 00:04:49.680 --> 00:04:52.160 And I'm like, Oh my friend, you have white coat hypertension. 00:04:52.480 --> 00:04:56.079 But he came prepared so we could like move the ball quite a bit. 00:04:56.480 --> 00:04:57.120 So that was cool. 00:04:57.360 --> 00:04:58.800 Maybe he listened to your podcast. 00:04:59.040 --> 00:05:00.000 Hey, well now. 00:05:00.160 --> 00:05:05.279 Um, so there's a couple details that both I want to explain about CGMs as a reminder. 00:05:05.360 --> 00:05:13.120 Um, you'll notice that the explanation about the three different types of blood sugars was a little bit more brief because we do have that whole other episode. 00:05:13.360 --> 00:05:22.000 But the common wearable sensors measure glucose in the fluid around your cells rather than taking repeated samples directly from your bloodstream. 00:05:22.160 --> 00:05:29.839 So that means the sensor reading can lag behind a finger stick, particularly when glucose is changing quickly. 00:05:29.920 --> 00:05:31.839 So that's something that's important to know. 00:05:32.000 --> 00:05:42.480 Um, sometimes what that means is that people, when they're experiencing symptoms or it's a critical time, you should have the skill of checking your fingertick glucose anyway, which we also explained in that episode. 00:05:42.720 --> 00:05:49.759 And also, a CGM continuous glucose monitor by itself does not deliver treatment. 00:05:50.399 --> 00:05:53.519 Some systems connect to insulin pumps. 00:05:53.680 --> 00:05:55.680 It's actually quite amazing. 00:05:56.000 --> 00:06:03.680 But the standard CGM that we are talking about here and that was like used in the study does not have that feature. 00:06:04.240 --> 00:06:09.600 So wearing a sensor alone does not automatically change your medication. 00:06:10.879 --> 00:06:13.519 So tell us what changed in this new study. 00:06:13.839 --> 00:06:26.560 So historically, CGMs have been especially important for people who use insulin because insulin dosing requires information about glucose and can cause low blood sugar. 00:06:26.639 --> 00:06:28.800 So that's one thing that we're really afraid of. 00:06:29.040 --> 00:06:32.240 But what if you had type 2 diabetes and you don't take insulin? 00:06:32.399 --> 00:06:36.160 Could seeing those patterns still improve your treatment? 00:06:36.319 --> 00:06:38.800 And that's what the Kinect trial studied. 00:06:39.199 --> 00:06:53.759 So, to help you guys become uh more savvy in thinking about these trials, like we do here from time to time, researchers enrolled 283 adults across 22 primary care practices in the United States. 00:06:54.000 --> 00:06:56.000 So it was, it happened in real life. 00:06:56.079 --> 00:06:58.480 It wasn't in some like weird box that they put people in. 00:06:58.560 --> 00:07:00.000 This was real world stuff. 00:07:00.319 --> 00:07:08.480 And these were people with type 2 diabetes whose glucose was above target and who were not using insulin when they entered the study. 00:07:08.720 --> 00:07:27.120 So one group received a CGM and the other continued routine glucose monitoring, guided by their specific care team, which in older guidelines and maybe more recent, there wasn't a huge push for people who are not on insulin to check their blood sugar all the time. 00:07:27.360 --> 00:07:30.879 So they might not have been checking a whole lot. 00:07:31.600 --> 00:07:40.720 So importantly, both groups received education about diet and exercise, and both had the same scheduled follow-up contacts. 00:07:40.879 --> 00:07:49.920 I will say, when I was reading through the trial, they they were seeing people a lot, like way more than you would normally see in primary care. 00:07:50.160 --> 00:07:52.480 So um, that is a little caveat to this. 00:07:52.639 --> 00:07:56.480 That if I'm not sure if we're gonna talk about it later, so I wanted to bring up now. 00:07:57.199 --> 00:08:06.079 What they found after about six months is that the CGM group's average A1C fell from 8.8% to 7.2%. 00:08:07.040 --> 00:08:14.240 And in the comparison group, who didn't use a CGM, it fell from 8.7% to 8%. 00:08:15.120 --> 00:08:26.879 And after accounting for differences at the start, the benefit associated with a CGM was about nine-tenths of an A1C percentage point, like the whole point, like what you would say there. 00:08:27.120 --> 00:08:29.199 So there's another piece that I wanted to explain. 00:08:29.360 --> 00:08:34.399 Um, this introduces a thought about something called time and range. 00:08:34.559 --> 00:08:40.879 So it is another way that we are able to measure how well someone is able to control their diabetes. 00:08:41.039 --> 00:08:48.639 So when someone's using a continuous glucose monitor, you're able to try to see if your blood sugar stays between 70 and 180. 00:08:48.799 --> 00:08:56.639 And 70 being the lower threshold of anything that you would want, and 180 being a upper threshold that someone can set. 00:08:56.960 --> 00:09:05.200 And so what they found is that the group using the CGMs spent about five additional hours each day with glucose in range. 00:09:05.279 --> 00:09:07.919 So between 70 and 180. 00:09:09.039 --> 00:09:12.320 And so that's what the trial used. 00:09:12.480 --> 00:09:15.840 Your own goals may be individualized by your care team. 00:09:16.080 --> 00:09:19.360 So there's a couple important distinctions that I wanted to make here. 00:09:19.519 --> 00:09:27.200 If this was a little bit confusing, trying to explain the study, is that people were taking medications for diabetes. 00:09:27.279 -->

00:09:34.799 Like they were taking, like up to around 40% of them were taking a GLP1, or I'm just going off now. 00:09:35.039 --> 00:09:42.799 Like 40% of them were taking a GLP1, and a very large percentage of them were taking an SGLT2 inhibitor like Jardiance. 00:09:42.960 --> 00:09:51.759 And these are so commonly used now for diabetes, and they we can get really great control of people's diabetes without using insulin. 00:09:52.320 --> 00:09:56.960 And both groups were just not using insulin whatsoever. 00:09:57.279 --> 00:10:07.679 And nothing they tried at least to create this environment that nothing else changed except for one group got a CGM and the other didn't. 00:10:08.000 --> 00:10:10.879 But of course, we already talked about that. 00:10:11.039 --> 00:10:20.799 It seems like the group that got the continuous glucose monitor had a greater A1C reduction than the group that did not get the continuous glucose monitor. 00:10:21.039 --> 00:10:26.000 But there is an element to this that I think is like useful for us to explore. 00:10:26.240 --> 00:10:33.200 Okay, so there are a couple interesting pieces that I wanted to share about the results. 00:10:33.519 --> 00:10:41.600 We see that the group with the continuous glucose monitors had a lower A1C reduction than the group that didn't. 00:10:42.080 --> 00:10:47.519 And that's a lot of what the anchor of the conclusions of the article will say. 00:10:48.399 --> 00:11:03.600 But I think it is also interesting that the group that did use the CGMs had medication added 31% of the time, and the group that did not use CGMs had medication added 17% of the time. 00:11:04.480 --> 00:11:21.120 And I think we have a little bit of the chicken or the egg situation that did the continuous glucose monitors lead to more awareness of someone's blood sugar and then therefore more of a dynamic response to treatment? 00:11:22.240 --> 00:11:32.879 Or did the simply the continuous glucose monitor itself increase someone's awareness of what they're eating in the day and how active they're being and the blood sugar spikes? 00:11:33.200 --> 00:11:39.600 And did that lead to the change in the A1C compared to the control group? 00:11:40.639 --> 00:11:46.159 And this interestingly, the study does not figure that out for us. 00:11:46.639 --> 00:11:50.799 It actually leaves an open-ended question in the discussion section. 00:11:51.200 --> 00:12:02.240 They say that they don't think it was from the medication differences, but this is a nice time to explain that this trial was sponsored by the continuous glucose monitor company. 00:12:04.000 --> 00:12:04.480 Which one? 00:12:04.879 --> 00:12:05.519 Dexcom. 00:12:05.919 --> 00:12:06.799 Oh yeah. 00:12:07.200 --> 00:12:19.039 So I mean they paid for the supplies and they helped support like getting people what they needed to make it happen, but they explicitly state that they didn't like help with any of the data analysis or anything like that. 00:12:19.840 --> 00:12:21.279

But it makes you wonder. 00:12:21.519 --> 00:12:21.840 Yeah. 00:12:22.559 --> 00:12:31.039 And I guess at this point, um what I really wanted to kind of get into is that I think I'm pro-CGM. 00:12:33.039 --> 00:12:34.639 Yeah, I think they're really useful tools. 00:12:34.960 --> 00:12:35.600 Me too. 00:12:36.159 --> 00:12:36.639 I do. 00:12:36.799 --> 00:12:50.159 I can't of course I can come up with like a a lot of one-off scenarios where it can not help someone, but I think it would be so useful. 00:12:50.320 --> 00:12:57.360 I mean, can you even think of a couple off the dome of like how it might be useful for someone who like hasn't maybe thought of a couple use cases? 00:12:59.440 --> 00:13:20.559 Well, I think if, you know, like with someone with diabetes and your whole life is kind of wrapped around what your blood sugars are doing, I think that's it's a really good tool because you can just like open your phone, like open the app and see what your blood sugars are doing in real time. 00:13:21.840 --> 00:13:29.679 And you also don't have to prick your finger if you're someone who like regularly checks your blood sugar. 00:13:31.279 --> 00:13:33.039 And that like really hurts. 00:13:34.159 --> 00:13:38.240 Checking your blood sugar, like the finger prick, yeah, you know, right? 00:13:38.399 --> 00:13:38.960 It really does. 00:13:39.200 --> 00:13:40.159 It's annoying. 00:13:41.519 --> 00:13:42.559 Takes that away. 00:13:42.720 --> 00:13:55.679 And then I think it also will make it easier for the person to if there's any sort of like lifestyle change that needs to happen. 00:13:56.399 --> 00:13:57.600 You know what I mean? 00:13:58.879 --> 00:14:01.120 Oh, I I'm I totally agree. 00:14:01.279 --> 00:14:13.360 I I think stepping away from the well, yes, I think there are like there are so many use cases in diabetes, and that's what was studied here, and that's what we're talking about. 00:14:13.440 --> 00:14:20.720 And specifically, like I do think that this technology should be accessible to people, even if you just don't have insulin. 00:14:20.879 --> 00:14:24.159 Like I don't like using insulin. 00:14:24.399 --> 00:14:29.600 Yeah, and that's this is not like medical advice, this is just like my personal preference. 00:14:30.000 --> 00:14:57.679 If people want to talk about band-aids in medicine and like trying to treat the root cause of something, which I'm like, we are not root cause people um here, because like root cause is if you are listening right now, is tongue-in-cheek for like a scalper online who's trying to sell you something that has some sort of like fantastical mechanistic explanation that magical herb no one else has told you about because no one knows about it and they're lying to you. 00:14:57.919 --> 00:15:08.960 Um but insulin like truly is just lowering blood sugar, which is important, but now we have all these medicines that are able to help your heart and your kidneys. 00:15:09.279 --> 00:15:19.120 But I've had so many

use cases where people are like, they wake up in the morning and they check their blood sugar first thing in the morning, and like, but doctor, doctor, my blood sugar is 97. 00:15:19.440 --> 00:15:30.240 And then they eat their first meal and they check, like they don't check an hour after, but I tell them to, and they're like, Holy crap, my blood sugar's 230 after I ate breakfast. 00:15:30.399 --> 00:15:30.720 Yeah. 00:15:30.960 --> 00:15:35.519 That's the granular feedback that you can get that like facilitates lifestyle stuff. 00:15:36.159 --> 00:15:41.519 Yeah, like maybe you need to eat breakfast that has more protein and fiber. 00:15:43.360 --> 00:15:46.639 Skip the bagel with like 80 carbs in it. 00:15:47.279 --> 00:15:48.799 I know that I I do. 00:15:48.960 --> 00:15:58.080 I think that this is where uh I will share my breakfast of champions is the fiber one cereal and a couple eggs in that order. 00:15:58.320 --> 00:16:06.480 And I really and I don't work for fiber one, but like it's a really quick, easy, high fiber source. 00:16:06.559 --> 00:16:13.360 And until I find a reason that it's not great for you, like I think that's way better. 00:16:13.519 --> 00:16:15.120 I mean, you even see it on TV. 00:16:15.279 --> 00:16:20.799 Like, we were watching Love is Blind, and the guy was like, Yeah, I go to Duncan, thin guy, but he's like, I go to Duncan every day. 00:16:21.039 --> 00:16:27.200 He's like, I get a bagel with X Schmear on it every day, and that is like a weekend treat. 00:16:27.279 --> 00:16:30.799 Yeah, maybe a like seldom weekend treat. 00:16:31.120 --> 00:16:51.200 Yeah, I think it's because if you kind of like what you were saying, you check your blood sugar once right when you wake up, it's fine, you go about your day, and then it's kind of like out of sight, out of mind, and you don't think about it, and your sugar's actually really high. 00:16:51.360 --> 00:16:55.600 Maybe your A1C is getting higher, and then next thing you know, your toes are falling off. 00:16:56.080 --> 00:16:56.480 Exactly. 00:16:56.799 --> 00:16:58.320 We want to keep our toes. 00:16:59.279 --> 00:17:27.759 So, in the face of I mean, and now we were talking about people with diabetes, but like, and I'm not sure how many people who don't have diabetes are gonna listen to this episode, but this could bump out to people with pre-diabetes because there is, I mean, I'm literally looking at a website right now of I think it's called Lingo, and it is a commercially available, and there are more of them now, but a commercially available continuous glucose monitor. 00:17:27.839 --> 00:17:29.599 And you and I have even talked about doing this. 00:17:29.759 --> 00:17:42.160 And when I went to the obesity medicine conference, they were talking about it, yeah, having people do this where you slap one on, even if you're an average person in average health, and also like two-thirds of people have pre-diabetes, I'm pretty sure. 00:17:42.319 --> 00:17:43.519 So maybe

one third. 00:17:43.599 --> 00:17:44.640 Sorry, guys. 00:17:44.960 --> 00:17:54.960 And see what happens, and like be aware that like you're gonna see if you do a high-intensity exercise, like you're gonna see your blood sugar go up. 00:17:55.680 --> 00:17:56.960 And that's okay. 00:17:57.200 --> 00:18:05.359 But you're also gonna see, like, I would love to see what would happen if I house a bag of tortilla chips and I see the repercussions of that. 00:18:05.519 --> 00:18:08.240 Oh my god, that would probably change my behavior. 00:18:08.480 --> 00:18:09.839 Yeah, seeing that spike. 00:18:10.160 --> 00:18:10.400 Yeah. 00:18:10.640 --> 00:18:14.559 I think it would also be interesting to see like how long it takes to go back down to normal. 00:18:14.799 --> 00:18:15.200 Totally. 00:18:15.359 --> 00:18:17.839 As like a person who does not have diabetes. 00:18:18.160 --> 00:18:19.759 Yeah, I think it's fascinating. 00:18:20.000 --> 00:18:24.079 And now that I mean, I don't even think you need a prescription for some of these people. 00:18:24.160 --> 00:18:25.920 Like you can No, you can order them online. 00:18:26.160 --> 00:18:30.960 Literally order them online, and I think they're only gonna get more accessible. 00:18:31.119 --> 00:18:37.759 And it's not something that I think you need to do all the time if you don't have diabetes and your doctor didn't prescribe it to you. 00:18:37.920 --> 00:18:41.440 I think you could just do it for a time-limited experience. 00:18:42.079 --> 00:18:44.400 We should do it and talk about what we learned. 00:18:44.720 --> 00:18:45.759 Do our own little experiment. 00:18:45.920 --> 00:18:46.640 Yeah, I would do it. 00:18:46.880 --> 00:18:47.599 I think it would be cool. 00:18:47.680 --> 00:18:48.640 I would too. 00:18:49.119 --> 00:18:54.799 Or if you're like a low sugar girly, maybe you got too much insulin going on. 00:18:55.599 --> 00:18:57.200 Yeah, that would be interesting. 00:18:57.680 --> 00:19:02.720 There are people who have reactive hypoglycemia or relative hypoglycemia. 00:19:02.880 --> 00:19:18.079 Like, I I mean, I I think anything in medicine and science and health is like we have population level data for people from studies and stuff, and like normals that are set from averages in the population. 00:19:18.160 --> 00:19:23.920 But like what is true for one person might not always be true for another person. 00:19:24.720 --> 00:19:28.880 This goes for anything, like side effects, blood pressures, blood sugars. 00:19:29.039 --> 00:19:38.319 Like there's there's so much to be personalized, and we just have that's how we collect information to make decisions about one individual person. 00:19:38.720 --> 00:19:40.480 Really preachy right now. 00:19:40.960 --> 00:19:47.440 So I think that they are I'm I'm looking like looking at the website right now, they are for lingo, they are not sponsored. 00:19:47.680 --> 00:19:55.279 Um, one in three adults have pre-diabetes, of course, but 80% of adults with pre-diabetes don't know they have it. 00:19:55.440 --> 00:19:57.680 This is something we've talked about on the show. 00:19:58.319 --> 00:20:03.920 And it looks like they say start today for just$54 for a two-week plan. 00:20:05.759 --> 00:20:09.839 And maybe not for everyone, um, you would consider it an investment for your health. 00:20:09.920 --> 00:20:13.519 And I'm they say start for that cost. 00:20:13.680 --> 00:20:19.200 I'm not sure you know what else is tucked in there that causes that. 00:20:19.359 --> 00:20:30.079 But you know, you also might ask your own doctor if you have diabetes, if I if you have coverage for a continuous glucose monitor, they very well may refer you to your insurance company. 00:20:30.319 --> 00:20:34.319 Maybe their health record has a feature where they can look it up real quick. 00:20:34.400 --> 00:20:51.680 Um, sometimes I'm able to see, but it usually is reserved for people who have insulin, which is why in the beginning of the the study, like this episode, when we were talking about the study, why I was so keen that this new information came out for people who don't use insulin because we didn't have this information for people. 00:20:52.240 --> 00:20:53.839 And so that was new. 00:20:54.000 --> 00:21:06.000 Um, while we're wrapping up on the study and overall here, a couple other things for you to know about that were specific for this is that the trial only lasted six months, so that's not a long time. 00:21:06.240 --> 00:21:17.440 You kind of need to officially know it long term, but like we can make a conjecture that like behaviors may fade over time, like we've talked about for so many things. 00:21:17.920 --> 00:21:23.359 Um, cost, access, and demands of daily life could really affect results outside of a study. 00:21:23.599 --> 00:21:28.640 And we already talked about how DEXCOM funded the trial and supplied the sensors. 00:21:29.119 --> 00:21:38.079 So that doesn't mean we throw out the results like with the bathwater, but you know, something to keep in mind when you're doing studies like this. 00:21:38.720 --> 00:21:39.279 All right. 00:21:40.000 --> 00:21:44.160 Any other thoughts or things that I think we should get them. 00:21:44.880 --> 00:21:48.240 That'd be I think it would be cool to be. 00:21:50.880 --> 00:21:57.839 I would be like, 'cause I just went and got like labs done, and I went like within an hour after eating lunch. 00:21:58.400 --> 00:21:59.359 I forget what I eat. 00:21:59.440 --> 00:21:59.680 I don't. 00:22:00.319 --> 00:22:06.400 Know how like carb heavy it was, but my sugar was like 72 or something. 00:22:06.640 --> 00:22:10.720 Yeah, you're just I was like, uh I am just a vision of health. 00:22:11.200 --> 00:22:12.000 Metabolic queen. 00:22:14.480 --> 00:22:21.119 Yeah, I I probably one, I probably need labs from the how it's been like a year. 00:22:21.440 --> 00:22:23.920 A year from flying close to the southern bolly. 00:22:24.559 --> 00:22:31.440 And based off of those

results, HIPAA guys, um, I should probably if it's yourself. 00:22:31.759 --> 00:22:32.960 HIPAA myself. 00:22:33.119 --> 00:22:35.519 Um, I should probably do one of these. 00:22:35.759 --> 00:22:37.599 Um, so maybe we will. 00:22:37.680 --> 00:22:41.839 And of course, for the purposes of science, if we do do it, we will share it with you guys. 00:22:42.079 --> 00:22:42.400 Yeah. 00:22:42.480 --> 00:22:43.359 Um for science. 00:22:43.599 --> 00:22:45.279 One way or another for science. 00:22:45.920 --> 00:22:53.119 Gosh, I wish there was like a listener question section where they could like be like, any I could any questions, but there isn't. 00:22:53.599 --> 00:22:57.759 Any other thoughts or feelings about this? 00:22:58.799 --> 00:23:00.799 Do you think that ended up being clear enough? 00:23:01.279 --> 00:23:01.920 I think so. 00:23:02.480 --> 00:23:02.799 Okay. 00:23:03.200 --> 00:23:03.839 I hope so. 00:23:05.039 --> 00:23:12.960 Well, no one's really like ever talked about it with like type 2 diabetes or with people who don't take insulin. 00:23:13.440 --> 00:23:18.559 Because they're typically like people with CGMs have and diabetes are like type 1. 00:23:19.039 --> 00:23:19.440 You know? 00:23:20.720 --> 00:23:22.160 Type 1 or insulin dependent. 00:23:22.400 --> 00:23:22.799 Type 2. 00:23:23.119 --> 00:23:23.680 Yeah. 00:23:24.000 --> 00:23:26.079 So it's very cool, very small. 00:23:26.640 --> 00:23:26.799 Yeah. 00:23:27.119 --> 00:23:29.200 And it was like 230 people. 00:23:29.440 --> 00:23:29.680 Yeah. 00:23:29.759 --> 00:23:32.160 But this made it into the New England Journal of Medicine. 00:23:33.039 --> 00:23:41.440 I mean, it took a year after it was they were done collecting data to publish the data, which is my shtick. 00:23:41.680 --> 00:23:43.039 I bet it was reviewer one. 00:23:43.359 --> 00:23:44.240 Oh my god. 00:23:44.559 --> 00:23:46.160 Well, this is my sh stick with it. 00:23:46.240 --> 00:23:51.119 I understand the whole process has to happen, but like it's the pace. 00:23:51.599 --> 00:23:51.920 Yeah. 00:23:52.240 --> 00:23:54.880 Like this exactly is the example. 00:23:55.039 --> 00:23:57.279 This trial ended November 2025. 00:23:57.519 --> 00:23:58.319 Oh my God. 00:23:58.880 --> 00:24:00.400 And it's October 2025. 00:24:00.799 --> 00:24:02.240 October 2026. 00:24:02.960 --> 00:24:15.440 And I like people are talking, like spewing stuff on TikTok, right and wrong, and right by accident, and wrong on purpose, and wrong by accident all the time. 00:24:15.680 --> 00:24:18.160 And like there's no filtering that. 00:24:18.400 --> 00:24:23.359 And this process, which is so precious, takes so long. 00:24:23.680 --> 00:24:28.799 And like, I appreciate how long it takes, but it also frustrates me. 00:24:28.960 --> 00:24:31.359 Like, this is the frustrating part of research. 00:24:32.240 --> 00:24:32.799 Yeah. 00:24:36.160 --> 00:24:43.680 Well, it's gonna take even longer now for insurance companies to get around to thinking about this, to be like, oh, maybe we should cover this. 00:24:43.839 --> 00:24:46.160 It's a little bit of something called the Hawthorne effect. 00:24:46.319 --> 00:24:49.519 Um and they would it would behoove them too, I think. 00:24:49.920 --> 00:24:56.559 Just like yeah, it would behoove them to do a lot of things, but that's not the place for that. 00:24:57.359 --> 00:24:58.480 Definitely not. 00:24:59.119 --> 00:25:00.319 Um, all right, what do you think? 00:25:00.480 --> 00:25:01.359 Banterizing a little bit? 00:25:01.519 --> 00:25:01.759 Yeah. 00:25:02.079 --> 00:25:02.400 Okay. 00:25:02.880 --> 00:25:07.119 Um, well, the Sixers and Knicks are starting to play right now, so hold on. 00:25:07.599 --> 00:25:07.920 Okay. 00:25:11.680 --> 00:25:14.559 Eddie's going to the Sixers game on Thursday. 00:25:14.880 --> 00:25:15.519 Is it? 00:25:16.640 --> 00:25:17.200 Wait. 00:25:17.920 --> 00:25:20.480 Is this the like no, it's not the home opener. 00:25:21.599 --> 00:25:22.240 Oh, it is? 00:25:23.359 --> 00:25:28.880 Eddie's going to the home opener with Mike. 00:25:30.799 --> 00:25:32.400 Can I say you're going with Mike? 00:25:33.039 --> 00:25:35.519 Mike's coming out of his basement to go to the Sixers game. 00:25:35.599 --> 00:25:37.440 They're gonna kiss LeBron, hopefully. 00:25:37.759 --> 00:25:38.400 If we're lucky. 00:25:38.640 --> 00:25:40.079 It's gonna be very exciting. 00:25:42.400 --> 00:25:43.359 I'm I'm pumped. 00:25:43.519 --> 00:25:46.240 Um, I we have to I have to get a shirt. 00:25:46.400 --> 00:25:52.480 Um so I can so I was always like a LeBron guy. 00:25:52.799 --> 00:25:58.960 And then so of course when he was with the Lakers, I was like, yeah, Lakers, Cavs, Cavs. 00:25:59.359 --> 00:26:02.559 He he first it was the magic in Dwight Howard. 00:26:03.359 --> 00:26:08.160 But now it's just this, it just feels so right. 00:26:08.559 --> 00:26:09.200 It just clicks. 00:26:09.519 --> 00:26:10.240 You feel so right. 00:26:10.559 --> 00:26:14.880 Oh, because I've like ever since living here, I've been like, oh yeah, it makes a lot of sense. 00:26:15.200 --> 00:26:20.640 I like the Sixers, they're fun, and I always like when they're doing well, and I'm sad when they're losing. 00:26:20.799 --> 00:26:22.799 So that's fandom to some degree. 00:26:23.279 --> 00:26:26.799 But now, I'm like, oh my god, this is great. 00:26:27.839 --> 00:26:29.440 And so I can't wait. 00:26:29.599 --> 00:26:31.519 Um, that's gonna be awesome. 00:26:32.480 --> 00:26:35.839 And let's see, what else have we been up to? 00:26:36.079 --> 00:26:38.240 You made a delicious dinner tonight. 00:26:38.880 --> 00:26:39.279 I did. 00:26:40.000 --> 00:26:44.400 Little shrimp fajita smorgish board. 00:26:44.559 --> 00:26:45.359 Yeah, yeah. 00:26:45.440 --> 00:26:46.720 So I'm glad you liked it. 00:26:46.960 --> 00:26:47.839 That was good. 00:26:48.079 --> 00:26:48.799 It was so good. 00:26:49.119 --> 00:26:50.480 I might go back for some more. 00:26:50.960 -->

00:26:57.279 Got a little uh little wrap, little old tortilla, high in fiber, they make them. 00:26:57.599 --> 00:26:58.079 High in fiber. 00:26:58.319 --> 00:26:59.759 You can go find them, they make them. 00:27:00.400 --> 00:27:02.799 We watched the Victoria's Secret Fashion Show last night. 00:27:03.039 --> 00:27:06.640 You I've never seen you so jazzed up over the program over a program. 00:27:07.039 --> 00:27:09.200 The Victoria's Secret Fashion Show. 00:27:09.759 --> 00:27:18.240 And it really was like in its heyday, like mid-2010s, and then they stopped it. 00:27:18.480 --> 00:27:22.480 I think in like it was before COVID. 00:27:22.960 --> 00:27:26.319 So maybe like 2017-ish, 2018. 00:27:27.759 --> 00:27:36.000 I think they like got canceled or something for having like unrealistic beauty standards, blah, blah, blah, or something like that. 00:27:36.160 --> 00:27:42.160 And then they did it again not last year, but 2024, I think, or 2023. 00:27:42.480 --> 00:27:43.680 And it was awful. 00:27:44.160 --> 00:27:45.119 It wasn't good. 00:27:45.279 --> 00:27:54.240 No one had the Victoria's Secret Angel loose curls, they all had slick back buttons because that was the trend, and it didn't go over well. 00:27:54.559 --> 00:28:05.039 And I think that they've really honed in on the prime Victoria's Secret fashion show days to an extent, not fully. 00:28:05.200 --> 00:28:18.880 They're being like real inclusive because they're afraid of the internet, and I get that, but man, what a time to be alive in like 2011, watching the Victoria's Secret fashion show live. 00:28:19.680 --> 00:28:23.279 I have to, or maybe there's one that I like really liked. 00:28:23.920 --> 00:28:26.000 Taylor Swift was there a couple years. 00:28:26.319 --> 00:28:27.359 Was she in the show? 00:28:27.599 --> 00:28:30.000 No, she was like performing, but she like looks like a model. 00:28:30.079 --> 00:28:32.160 She's like tall and pretty and blonde and skinny. 00:28:32.240 --> 00:28:33.440 So yeah. 00:28:34.160 --> 00:28:35.599 She was oh, that makes any sense. 00:28:35.680 --> 00:28:37.759 I mean, there were we saw some performances last night. 00:28:37.920 --> 00:28:39.680 It didn't air last night. 00:28:39.920 --> 00:28:46.160 I've never I just like love it because it's just like I don't know. 00:28:46.240 --> 00:28:52.720 I feel like girls like watching it because it's like these supermodels are like you're not just like a girl. 00:28:52.799 --> 00:28:57.440 And I get that they're trying to be inclusive, but it's like, okay, like I practically look like that girl walking down. 00:28:57.519 --> 00:29:05.119 Like, you're not a supermodel, like supermodels are they're like otherworldly, you know, like they're not real people. 00:29:05.359 --> 00:29:18.960 Not everyone is a supermodel they could be aliens, they could be aliens, and it's just like fun to watch them, and they're you know, just objectively beautiful people on the screen, and they're like, oh my god, like this person looks like this. 00:29:19.440 --> 00:29:22.000 It's like the same reason you like watch football. 00:29:22.480 --> 00:29:23.200 Just gonna say that. 00:29:23.359 --> 00:29:25.680 I was like, this is why they made professional athletes. 00:29:25.839 --> 00:29:27.599 Yeah, it's just like it's a similar concept. 00:29:28.079 --> 00:29:34.400 Hoopla around the Olympics, you know, because these are the best athletes in the world, like they are not real people, they're special. 00:29:35.039 --> 00:29:37.039 Yeah, it's like the same thing. 00:29:37.519 --> 00:29:39.920 From that perspective, I totally agree with you. 00:29:40.160 --> 00:29:42.640 Yes, there's there's nothing else behind that. 00:29:42.799 --> 00:29:43.759 It's just like so fun. 00:29:43.920 --> 00:29:46.319 Yeah, I'm glad you you got so excited. 00:29:46.640 --> 00:29:52.400 I did, I was so excited, and like Adriana Lima was there, and Candace came back, Alessandra came back. 00:29:53.440 --> 00:30:01.519 Everyone's mad that Kylie wore the fantasy bra, which I do understand because I wonder how many boomer men are still listening. 00:30:01.759 --> 00:30:14.480 If you were around for prime VSFS days, the supermodel who got to wear the fantasy bra was like, it was the big thing, and who's gonna wear it? 00:30:14.559 --> 00:30:19.119 And like you all have to wait, and like they put wings on everyone nowadays, too. 00:30:19.200 --> 00:30:21.119 Like, you had to earn your wings back in the day. 00:30:21.279 --> 00:30:26.319 Like, this is what I mean when like they're being too inclusive, everyone gets their wing, everyone gets a wing. 00:30:26.480 --> 00:30:29.920 Like, but yeah, I enjoyed it. 00:30:30.160 --> 00:30:33.519 We should watch some old ones and then because it was also fun. 00:30:33.599 --> 00:30:59.119 I was telling you last night when they would have like sound bits of like the producers and stuff, so you got to hear kind of like what was happening backstage, and it showed all like the chaos backstage, and people are like dressing the girls, like not like undressing them, but like switching out their shoes and like all that stuff, and it was like, and then they're like grabbing them to come out onto the stage, come out and stuff in the street. 00:30:59.279 --> 00:30:59.599 I love it. 00:30:59.680 --> 00:31:02.799 You live up so much, and you have so much detail and history to it. 00:31:02.960 --> 00:31:11.119 I mean, we have a thing in our house love what they love is what we say, and you know, from the You loved it, it was fun, right? 00:31:11.279 --> 00:31:16.480 Well, yeah, from the objectivity of like that these people work so hard at their craft and we're like celebrating them. 00:31:16.640 --> 00:31:18.000 Yeah, absolutely. 00:31:19.440 --> 00:31:22.079 I'm not supposed to say positive things about it. 00:31:22.720 --> 00:31:25.279 No, but like that, but like that's the thing. 00:31:25.440 --> 00:31:34.640 They're supermodels, they're not a threat to me because in

no world are you gonna end up with one of them? 00:31:34.880 --> 00:31:35.680 That's a good point. 00:31:36.319 --> 00:31:37.680 Nobody ever want that. 00:31:37.839 --> 00:31:42.319 They're not my nickies, but even like, okay, this is like a little toxic. 00:31:43.039 --> 00:31:56.240 I don't really care, but like everyone knows like the supermodel diet and supermodels, they all like starve themselves, and that's how like they're so tall and skinny and pretty, and like they all starve themselves before the show, and like blah blah blah. 00:31:56.400 --> 00:32:04.559 And I saw an interview with um Barbara, I always forget if it's Pavlin or Palvin, the one who's married to Cole Sprouse. 00:32:04.960 --> 00:32:06.240 Okay, I think. 00:32:06.559 --> 00:32:22.000 Um, because they've like been together for a while, and she just had a baby like less than two months ago, and like looks amazing, which is an example of like you are otherworldly, because like most women who have just had a baby don't look like that at six weeks. 00:32:22.319 --> 00:32:32.480 They're barely walking around, probably depending, let alone like walking down a runway in stilettos with like wings on, like crazy. 00:32:32.640 --> 00:32:36.960 But I saw an interview and someone was like, What's like the first thing? 00:32:37.039 --> 00:32:39.200 Like, what are you dying to eat after the show? 00:32:39.440 --> 00:32:43.599 And she was like, Oh, well, and you know, in like 20, whatever. 00:32:44.000 --> 00:32:46.000 Oh, wait, is she married to Dylan or Cole? 00:32:46.160 --> 00:32:46.640 I don't know. 00:32:46.799 --> 00:32:48.559 Her husband, she's married to a twin. 00:32:48.799 --> 00:32:49.759 Sound like me over there. 00:32:49.920 --> 00:33:00.400 Um she's like, Oh, in you know, like 2017 or 2018, my husband brought me Shake Shack because I was just like dying to eat that, but not this time. 00:33:00.559 --> 00:33:05.599 And you know, I'm just like listening to my body and eating healthy and like for my baby, and da-da-da. 00:33:05.759 --> 00:33:10.160 I'm like, okay, well, now you're being too relatable, Barbara. 00:33:10.480 --> 00:33:11.119 Yeah. 00:33:14.079 --> 00:33:15.759 Stepped over too much into reality. 00:33:15.920 --> 00:33:16.079 Yeah. 00:33:16.319 --> 00:33:17.759 Get on the world league. 00:33:21.359 --> 00:33:22.640 But yeah, it was really great. 00:33:22.799 --> 00:33:24.079 I think we should watch. 00:33:24.640 --> 00:33:26.240 Yeah, we're gonna watch. 00:33:26.480 --> 00:33:28.880 Look, you own that bottom TV, so whatever you want. 00:33:29.039 --> 00:33:29.599 I do. 00:33:30.160 --> 00:33:31.440 I'm excited. 00:33:33.039 --> 00:33:35.200 All right, what do you think? 00:33:40.799 --> 00:33:41.440 Yeah. 00:33:41.920 --> 00:33:43.359 Got nothing else. 00:33:43.759 --> 00:33:44.480 Excellent. 00:33:44.720 --> 00:33:47.440 So thank you for coming back to another episode of your checkup. 00:33:47.519 --> 00:33:52.000 Hopefully, you were able to learn something for yourself, a loved one, or a neighbor. 00:33:52.240 --> 00:33:56.960 You can find us on Instagram, threads, send us an email, send us a voicemail if you'd like. 00:33:57.200 --> 00:33:59.440 But most importantly, stay healthy, my friends. 00:33:59.599 --> 00:34:01.359 Until next time, I'm Ed Deleski. 00:34:01.519 --> 00:34:02.559 I'm Nicole Rufo. 00:34:02.799 --> 00:34:03.759 Thank you and goodbye. 00:34:04.000 --> 00:34:04.640 Bye. 00:34:10.880 --> 00:34:15.119 This information may provide a brief overview of diagnosis, treatment, and medications. 00:34:15.280 --> 00:34:19.199 It's not exhaustive and is a tool to help you understand potential options about your health. 00:34:19.360 --> 00:34:23.920 It doesn't cover all details about conditions, treatments, or medications for a specific person. 00:34:24.079 --> 00:34:27.440 This is not medical advice or an attempt to substitute medical advice. 00:34:27.679 --> 00:34:32.719 You should contact a healthcare provider for personalized guidance based on your unique circumstances. 00:34:32.960 --> 00:34:37.440 We explicitly disclaim any liability relating to the information given or its use. 00:34:37.599 --> 00:34:41.519 This content doesn't endorse any treatments or medications for a specific patient. 00:34:41.760 --> 00:34:45.679 Always talk to your healthcare provider for a complete information tailored to you. 00:34:45.920 --> 00:34:47.599 In short, I'm not your doctor. 00:34:47.840 --> 00:34:48.639 I am not your nurse. 00:34:48.800 --> 00:34:52.480 And make sure you go get your own checkup with your own personal doctor.