Ep. 33 - GLP-1 Side Effects Patients Are Actually Reporting and What Reddit Data Reveals

Dr. Tim Sayed walks through an April 2026 study published in Nature that analyzed over 410,000 Reddit posts from people using semaglutide and tirzepatide, using AI language models to extract and categorize what patients were actually saying about their experiences on these medications. The study identified roughly 67,000 self-reporting users, and among them, 43.5% described at least one side effect, with nausea leading at 37%, followed by fatigue, vomiting, constipation, and diarrhea.

What makes this study notable, and what Sayed spends real time on, is where the real-world data diverges from the clinical trial record. Fatigue appeared far more commonly in Reddit posts than in formal trial reporting. Reproductive symptoms including irregular periods, mid-cycle bleeding, and heavy cycles emerged as a signal in about 4% of users reporting any side effect, something not well captured in current drug labeling. Temperature-related complaints like chills and hot flashes showed up as well, which the study authors connected speculatively to glucagon's known role in thermogenesis. Sayed is careful to carry the study's own caveats: selection bias is real, Reddit skews younger and American, and voluntary self-reporting cannot establish true prevalence.

The broader point he lands on is practical. Prescribers should know what patients are reading and talking about, because those conversations are already shaping what people expect and ask about in the clinic.

Contact Dr. Tim Sayed:
Phone: (858) 247-2933
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Transcript

SPEAKER_00 0:04

Hello, welcome back, listeners to the Scalpel's Edge. I'm your host, Dr. Tim Site, MD, double board certified plastic surgeon in Southern California with a practice that focuses on holistic health and wellness, including breast implant illness management with explant surgery, as well as medically supervised nutrition with GLP1 compounded medications and general wellness services, as well as aesthetic services. On our podcast, Scalpel's Edge, we like to talk about all those aspects of our physical, mental, emotional, and spiritual health that go into optimizing our performance, that helps us to live on the bleeding edge or what I like to call the scalpel's edge of life. And as many of you know, um, we have been talking a lot in our podcasts about the GLP1 medications. Um, I've spoken of my own personal experience both as a prescriber and as a patient on these medications. And we've talked about, you know, outcomes, side effects, new products in the pipeline on the horizon, uh, the ever-shifting and evolving regulatory climate around GLP1s and the compounding pharmacies versus the major drug manufacturers and affordability and accessibility issues and so on and so forth. Uh, today what I thought I would do is walk you through an interesting paper that was just uh, as of the time of the recording of the podcast, that was just published, and it was published in Nature, which is one of the preeminent journals, uh, peer-reviewed medical journals. Um, Nature has a lot of subsidiary publications of different um focuses. Um, so this was in one of the nature journals, and um data publication was April of 2026. Um so um what I wanted to do is just walk you through an interesting kind of um analysis they did, which was to look at social media posting about patient experiences, real-world patient experiences being on GLP1 drugs and sort of analyzing this and how that kind of is similar to, but how it may differ from what's published in the clinical trial data. So, as you may know, for a drug to meet FDA approval and be um uh allowed on the United States market for medical purposes, I'm not talking about uh, you know, just nature's you know, natural supplements and um certain herbals and things that are often not regulated by the FDA uh and are more over-the-counter type of products. Um, I'm talking about medical-grade products that are regulated, regulated very clearly and with a high level of scrutiny by the FDA. Um, and certainly the GLP1 medications like OZEP and uh Munjaro, Zeppbound, Wagovi, um, all of these are regulated that way by the FDA. So, of course, these GLP1 medications are highly regulated by the FDA, including uh the FDA uh working with the manufacturers on trying to set guardrails and parameters around the availability of compounded versions of these medications, which many of us prescribe that have actually increased accessibility for a lot of patients out there. Um, you know, what I think is really interesting about this paper is it's actually taking advantage of the latest in technology, specifically AI language models and tools like Gemini and Claude and ChatGPT to basically analyze what people are posting on Reddit. So you maybe use Reddit yourself, it's a very popular social media platform, kind of conversational threads. Doesn't have a whole lot of bells and whistles, it's just basically people post on a subject and people comment and you get upvoted or downvoted, depending on what people think of your commentary. Um it's a nice supplement, you know, Reddit kind of dovetails uh with some of these closed uh Facebook groups that you can join for different subject matter that you're interested in, including health uh-related uh issues uh and medical problems and so on and so forth. There are patients in different medical communities who all have rare diagnoses or common diagnoses who want to share their experiences. And so what this paper did was to look at 410,000 Reddit posts from May of 2019 to June of 2025 that mentioned the active ingredients in these GLP1 drugs, semaglutide or terzepatide. Um, in the analysis, according to the abstract, there were about a total of 67,000 users who self-reported using these medications, and 43.5% described at least one side effect. Uh the summary of this is that the GI symptoms predominated, which we know from our own anecdotal experience and from the data published in the clinical trials and in what we see from our own patients, which is typically the nausea, bloating, the sense of fullness, feeling like your stomach wants to explode, like you can't quite move gas either up or down your GI tract, um, a sense of constipation, sometimes alternating with diarrhea, just kind of this very blah feeling uh that almost makes you um dread eating. Um, so there's a physical aspect to that that is part of what keeps you from eating. And then there are also uh effects on the brain where the brain chemistry is altered in terms of its satiety or feeling you know satisfied, those centers uh they get triggered by GLP ones to let you feel like you are content and satisfied with fewer calories in your system or without eating sugars and foods that may lead to fat buildup, and instead using up your own stores. So no big surprise here that in this study that the most common side effects were GI nausea was about 37% of patients, fatigue in about 17%, vomiting in about 16%. That's a higher rate than I've seen in my own patient population. Uh, constipation, 15%, diarrhea, 13%. Um, there were some reproductive symptoms, like menstrual irregularities, and then uh temperature-related issues like chills and hot flashes that seem to emerge as what they call in the paper, they call them unrecognized potential effects. So, what they summarize in their abstract is that the findings highlight, I'm quoting now, they highlight patient concerns not well captured in current labeling or trials, and that large-scale social media analysis can complement traditional pharmacovigilance, meaning being vigilant about you know um uh adverse effects with the FDA, making sure adverse uh outcomes are reported, uh that you can make reports if you have an adverse event on a patient using a device or a medication. Um, but that large-scale social media analysis can complement traditional pharmacovigilance by detecting emerging safety signals and expanding understanding of the real-world safety profile of GLP1 receptor agonists. So let's go kind of deeper into the study and see what they really did. Okay, so they go through some background on what these GLP1 uh receptor agonists are, and that they've gained popularity for type 2 diabetes as well as weight control, and that the GI symptoms are well established. Um, social media data is providing the opportunity now to capture a broader range of patient experiences, including symptoms that are not formally recognized in drug labeling. Uh, drug labeling is basically what the FDA makes the manufacturer put on the product insert or on the packaging or as an advisory to patients and providers alike that tell you, you know, what the outcomes were like in the clinical trials, what were the reported side effects and adverse events, um, what are the dosing indications, what are the uh specific use cases that are considered on-label indications, where this is what the FDA approved the medication for. We can prescribe a lot of things, or pretty much anything that the FDA has approved, you can prescribe as a physician off-label. You have to let the patient know that you're prescribing it for an off-label use case. So um let's talk through a little bit of how they gathered this data on Reddit. So they talk about, you know, so Reddit has over 100 million daily active users who um are typically posting anonymously, meaning, unlike, say, Facebook, where you're you know, supposed to give your real name uh when you enroll, um here you can actually uh have a pseudonym and post anonymously. So there's some idea there that this is a little bit more um candid an environment. You know, you don't have to be verified with your identity to be able to post there. And that can be good and bad. For the purposes of reporting side effects of medications or you know, candor about medical issues, it's probably a good thing that you can post anonymously. Um, people can be very um open about their experiences, good, bad, and ugly. So they selected it as the data source due to its large, publicly accessible topic-specific health communities and its long-form, context-rich user discussions, meaning that these uh participants are usually going into a lot of details. Um, and you know, it's all contextualized within whatever thread. So if this is a thread about GLP1 side effects on, you know, 7.5 milligram trzepatite, you know, that might be the whole subject matter. And if you start deviating, talking about you had this experience on Ozempic, or you were trying Rebelsis orally and you didn't find, you know, and here, what dose were you on on Rebelsis? And you start like digressing, people can kind of bring you back, they can downvote your posts, your posts can get better visibility if you stay on topic. And so that's kind of a very keen aspect to Reddit, which is to be on topic with what's going on, uh, uh, that is the uh subject of the actual thread that you're participating in. So um they talk about how uh prior work has established Reddit as a valuable source for studying health-related disclosures, including those things that are sensitive or stigmatized. Um, and it's an important resource for public health and computational social science research. So um they say that unlike other major platforms that provide either restricted, unreliable, or very um costly access through what are called APIs, application programming interfaces for you to be able to access the information. Um, basically, Reddit is you know really an open forum for public uh health research kind of at scale. So um that's why they chose this as the platform for the um uh to to go through the social media posts and analyze what people were saying. So they called this a cross-sectional study of self-reported side effects of semaglutide and trusepatide from May 2019 through June 2025. And the posts and comments were collected from nine large subreddits that discuss either weight management or GLP1 receptor agonist medications. You're listening to The Scalpel's Edge. I'm Tim Syed, MD, double board certified plastic surgeon in Southern California with a focus on holistic health and wellness. And today we're talking about GLP1 medications and specifically side effects and patient experiences that are discussed in Reddit forums that were analyzed in this recently published paper. And we're going to include what they did with AI to kind of analyze the sentiment and the information that patients were providing to paint a broader picture of what it means to be on these medications in terms of things you may expect for side effects and experiences. So, what they did in terms of the systematic process is they then identified posts where users who were taking um the uh GLP1s in any FDA-approved formulation, and they were doing it for either type 2 diabetes or weight management using one of the um classifiers that they used to classify these drugs. Um they were they used this toolkit um in Chat GPT, they used a kind of um filter toolkit to allow them to extract the specific medications that were mentioned by the people who were posting. And then they used another GPT uh language model, or they call it a mini uh-based classifier, which is a way for them to kind of categorize things that people are saying. So basically, a digression here AI language models essentially are uh these tools with using artificial intelligence that get trained on the way people communicate about different subjects and you know, the kinds of uh forms of speech they use, the slang, the formal uh vernacular or formal terminology people might use, um, what people may mean in terms of connotation of something. Um it's like the famous thing where you know you're writing a letter of recommendation for somebody who's looking for a job, and it's like, you know, you would be very fortunate to get Tim to work for you. And that could mean that you'd be very fortunate if you were able to hire this guy because he's so good. So you'd be super lucky to get him to work for you. The other could mean you'd be really lucky if you can get him to do any work. Um, and it's the same, you know, actual denotation or the same actual words, but the connotation with a meaning behind it is polar opposite different. And that's one of the fascinating things about language and the English language in particular, things like the word invaluable, which means you can't value it. It's so valuable that it's invaluable, right? And that there's two words that technically should mean the opposite that mean the same thing. So, anyway, they went through using these models to help analyze what people are talking about. And it gives you a way to kind of categorize things. Then you can apply machine learning, you can apply even database, traditional database sort of data science to search through things, but you have to be able to catalog things. Uh, and one of the cool things about AI is its ability to sort of catalog um, you know, what people mean when they say things uh in the same way that, you know, or in a more sophisticated way, rather, that that like Google kind of won the search war because they did a much better job of figuring out what it is you're actually trying to search for and to kind of figure out are you somebody who's browsing or are you searching? And there's and and in the language of sales, there's a difference between sort of you know, window shopping, going to um Costco and just walking every aisle, and you're kind of like, I'm just kind of browsing. I'm not necessarily sure that I want to buy a George Foreman grill today or a, you know, or this you know, king-size thing of um mayonnaise. But while I'm here, yeah, I guess we're out of mayonnaise, so maybe I'll buy this, you know. So that's kind of more browsing as opposed to I want to go to Costco because we're out of bottled water for the office and we need bottled water because we have a you know clinic for full of patients tomorrow. So we, you know, we need water. Now, if you're listening to this and you're really into holistic health and wellness, you probably know that we probably shouldn't be drinking out of plastic bottles uh because of microplastics and so on and so forth. But the point of me saying that is really just getting to the idea of you know, what is your intention? What is your sentiment and your intention? Are you going to Costco because you have a mission to buy certain things that you need, or are you, while you're there, just browsing to see what else is around because here's your opportunity, and this is a place where you find things. And that's kind of the way the internet is. Sometimes you're there with intention, and sometimes you're doom scrolling on Instagram or Facebook or you know, TikTok, and you're just seeing where this takes you, where the algorithm takes you. So AI is kind of you know similar in many ways. And so, you know, just like your algorithm on your Instagram is learning from your behaviors, well, so too do these AI language models kind of learn from what people are looking for, what are they saying, and how do people respond? And it builds this sort of you know conversational library of human intention and human behavior. Uh, super cool. And I think we're just scratching the surface of the power of these types of models uh as we sit here today, and it's just rapidly expanded in the last couple of years, as you've seen, I'm sure, in your own social media, AI actors, you know, AI um uh music making tools where you can have something sing in the voice of John Lennon by just singing it in your own voice, and then it'll correct the pitch and put it in his voice. It's just amazing stuff. So that's my little digression about AI and how it's pertinent to this. So, getting back to the study, they went and identified these posts where people were taking semaglutide or trisepatite in any FDA-approved formulation, and they applied these classifiers to kind of categorize the information, and they then mapped it. So they used this classifier to extract the self-reported side effects and then map them to preferred terms using med DRA, which is a uh basically a medical ontology or a medical data dictionary, a vocabulary, sort of like, you know, you might say redness, and I would say erythema as a physician. Erithema is the medical Latin term for redness. Um, but most lay people will not use that term. They've never heard that term. So you say, my fingertip, you know, the tip of my finger, my fingernail is red and it hurts, you know, I would describe that as having, you know, rhubor or or erythema, redness, and edema or swelling. And so medical ontologies know that these words are synonymous and know how to categorize them. And that's very important for electronic medical record uh development, um, using AIs to scribe what we do in the encounter with the patient so it can helpfully make our visits more efficient. Doctors can see more people, spend more quality time with the patient instead of spending that time entering data into a computer and so on. So, all that's going to get a lot better in the coming years as AI keeps exploding as well. So they mapped these self-reported side effects into the med DRA preferred terms, and basically they found that 173,000 or so of 411,000, 410,000 posts that mentioned semaglutide or trisepatide indicated personal use, and there were about 67,000 users who were posting these. So they basically called through the things that were on the subject, but not necessarily somebody describing that they are taking the medication. So they could actually winnow this down to the people who are actually on the meds. So among them, 43.5% reported at least one side effect, and there was an average of 2.7 side effects per user. So we talked earlier about the prevalence of the side effects, nausea, most common, about 37%, followed by fatigue, vomiting, constipation, and diarrhea. Um other symptoms were reported by at least 5% of users who did disclose any side effects, included a lowered appetite. Well, you would expect that actually, and I would think almost 100% of patients, right? That's part of how it works. Uh, abdominal pain, uh, heartburn or reflux, uh, headache, abdominal distension, bloating, and dizziness. Uh, the most common things that occurred together or co-occurring um uh side effects were nausea and vomiting, with 2,900 users or about 10% reporting both. So overall, 66% of patients with side effects reported at least one GI symptom, and psychiatric symptoms were um reported by about 13%, anxiety and depression being the most common. So then they did another analysis and they examined the monthly frequencies of the 10 most commonly reported preferred terms or side effect terms. And they said that symptom counts increased in parallel with overall discussion volume, but didn't show any distinct or interpretable temporal shifts. Meaning, okay, as people were talking more and more, they would see more people talking about symptoms, but that didn't necessarily mean that as you talk as you gleaned who was on this for six months, that their rate of symptoms was somehow higher than the people who were just starting on the meds or who had been on it for two years. So they then um examined the side effect frequencies separately for users who exclusively mentioned semaglutide versus trusepatide. And so they looked at the differences, and that's not all that important here, but it what is important is that nausea was in about 39% of the semaglutide group, and in the trusepatide it was 29%, so a lower percentage, which that is consistent with our my own experience as a prescriber and what patients have been saying, as well as the data that I have seen prior to uh launching the GLP1 medically supervised weight loss program in my practice. So they have a table that lists all the different things, and they did say that you know, injection slight reactions, pretty common with any kind of injectable drugs, uh, muscle pains, that but they listed some interesting things like insomnia, chills, feeling cold. Each of these were reported by anywhere between one to four percent of the trusepatite users. So um now they're gonna talk about where these things are consistent with the clinical trials and where they may differ. So consistent GI side effects are most common. Um and um the uh headache, which was common in the trials, showed a mixed placebo comparison, while fatigue, which was the second most reported symptom on Reddit, um, met reporting thresholds in relatively few trials. So fatigue seems to be something that people in the real world really do experience a lot more than what the clinical trials reported. So that's something that you need to know if you're gonna be on the medication, and doctors and prescribers should know if they're going to prescribe these medications to patients. You're listening to The Scalpel's Edge. I'm Tim Site, MD, double board certified plastic surgeon in Southern California. My practice focuses on holistic health and wellness. One of those avenues is uh GLP1 medication prescribing. Today, we are walking through a recently published Nature paper, a very uh prestigious journal, uh, talking about side effects uh determined from Reddit posts of people on semaglutide and trzepatide as analyzed through AI models. Super high-tech, super up to date, uh hot off the presses. So they identified several side effects not previously reported with semaglutide or trisepatide. And that was uh about 4%, 4% of Reddit users with side effects reported reproductive symptoms, typically um bleeding in between periods, heavy cycles, and irregular cycles. Um and of course, these would only these would be higher in female only samples, obviously, by definition. So you know, not you're gonna have 0%. rate in the the the male patients uh and you know um this is gonna exclusively occur in basically cisgender females or you know potentially transgender males um so anyway um they uh also indicated that these GLP1 receptor agonists are thought to impact food intake by engaging receptors in the hypothalamus or the brain and we've talked about this on the podcast um and it also plays a central role in the menstrual cycle so the hypothalamus and the pituitary gland kind of communicate with each other and those communicate with the adrenal glands and with the ovaries and the uterus and in males with the testes um uh and uh basically they impact hormones and cycles um and um fertility and all these uh you know sort of sexuality based issues so um some patients uh describe symptoms that were possibly linked to altered regulation of the temperature like chills and hot flashes and so that uh they think should warrant some further study and placebo controlled trials or or what's called postmarket data which is where a product is already on the market and then they want to gather more data as it continues to be in use, which has been done with breast implants, like we've talked about on the subject of breast implant illness here on the podcast. But basically they think it's important particularly because it is known that glucagon which is the naturally occurring hormone from the pancreas that these medications are mimicking is known to have some associations with heat generation or thermogenesis in the body. So strengths of the study are that it's large, it's contemporary, it's unprompted, it's self-disclosed experiences, they use systematic data dictionaries to kind of catalog this and they used a straightforward language learning model or LLM which is an AI tool of you know basically vocabulary to detect these potentially underreported signals in a timely manner, meaning early enough that you know can kind of learn from this and maybe make this something that either the manufacturers will study as they develop new drugs or to encourage reporting on these issues as part of postmarket surveillance and also for proscribers and patients to know as we embark on treating patients. Some of the limitations of the study are very important to point out. One is that it's possible that the patients who are actually on these subreddits may differ from the overall population prescribed. Maybe the only people going on these subreddits are the people who are having problems, right? I mean there's a selection bias concern. If I'm doing really well, I may not spend a lot of my time going on you know a subreddit so that I can tell everybody look how well I'm doing on Truezepatide. It's sort of sometimes you'll be on some forum call it you know some kind of software uh you know music software for example that I like to use and you'll have some user who's calling out that there was a recent update from Apple and now I'm having this problem. Anyone else experience this problem? And the helpful posts are the people who've experienced the problem especially the ones who've experienced the problem and found a solution. But you'll by like every fourth or fifth will be no problems here working like a charm for me. And it's like this is that is useless you know like we don't need to even hear that. We can assume that people who are not responding that it's working for them. You know but this it's almost like this this like humble bragging or not even humble, just bragging. I I don't have the problem I don't know must be user error I've seen this where people will post and literally say it must be your fault that you're experiencing this. It must be that you don't know what you're doing. I'm a genius I know what I'm doing. One of the big problems with social media is this like armchair warrior behavior where people can hide behind screens uh in the anonymity of their homes and Reddit maybe make it worse. We talked about anonymity maybe being a good thing for candor and exchanging information but also potentially bad because you don't there's no shaming somebody you don't know who it is. So but anyway some of the other limitations is that you know the selection bias people who are on the subreddits may not represent the population at large of patients who are using these medications. Also Reddit users tend to be younger they're more likely to be male and they're disproportionately located in the United States. So we don't know what this tells us about the experience of GLP1s in Brazil or you know the United Kingdom or Egypt or China or Russia. So this composition of Reddit users and self-selection into health related discussions limit the generalizability of our findings and that's basically saying what I said earlier that you know selection bias of people going into this and choosing to self-report limits how broadly you can extrapolate the information to people at large. They also can't quantify the magnitude or direction of the biases. So you know Reddit provides a very active online health community and it's one of the few platforms with this accessible high volume data but hopefully they can extend the same type of analysis to specialized patient forums. For example a lot of the manufacturers when they do clinical trials they may actually have patient forums to gather patient sentiment to understand real world experiences. There are also platforms patients like me and other things where people go on to kind of meet with people who are like them dealing with the same health issues and so on. And again there's selection bias there but potentially the possibility that people there are really actively both seeking and going to contribute high quality information and not just lurking or just trolling or you know trying to be armchair warriors. So they're commenting in the paper that the future work should extend the approach to other sources like specialized patient forums, clinical review platforms or any social media systems that restore stable API access to assess the consistency of patient reported symptom patterns across different environments. So they just say their results should be interpreted as kind of a hypothesis generating signal or something that basically should stimulate further thought about what we should look at with these medications. Another limitation is that because users were not prompted to disclose all their side effects, you can't really estimate the true prevalence so you know participating is voluntary people who experience more severe symptoms are going to be and the ones that are more distressing are going to be more likely to post about it than people with positive or neutral experiences and you know is what I said before the selection biases. But even those who reported side effects may not have disclosed every symptom experienced you know um because the people's belief about what are potentially attributable to the medication and what may be unrelated could have influenced the report. So somebody might have irregular periods and be like but you know I've looked at the insert from Ozempic I know that that's not a side effect because that's not in the clinical trial as a reported side effect with any you know high frequency. So that must not be from the GLP1 so I won't report it when I'm talking about it on Reddit. Who needs to know about my periods you know that's private. I'm not gonna talk about that by the way and and even if I did it's probably not related so why ring it up but that's actually you know somebody excluding data that might actually be pertinent and so there may be the underreporting of certain symptoms. Prior work they say has found that while clinical trials often rely on self-report, GI symptoms are often underreported and inconsistently reported compared compared to validated measures for functional GI disorders. And so this may be again that you know people sort of like yeah I get indigestion when I eat spicy food. So I didn't think maybe that that was really related to the medication. That's a little to me just back of the napkin it's kind of a little less likely that people would not think to report significant GI side effects if they're talking about GLP01s when pretty much everybody knows that those are the most common side effects, right? And they should know that because that should have been disclosed to them when they got put on the medication. So to me I'm I think it's less likely that there's underreporting of GI than that there's underreporting of non-GI side effects. And then they also said that their analysis prioritized just the breadth of symptoms over the temporal granularity is the term they use. So like how you know quickly these things occur, how frequently you know are there pauses what's the correlation to when you get these side effects versus when you had your dose for me I know that like the day after getting my GLP1 shot is and the and the second day after that are usually the days I felt the most bloating, the most queasiness or just this distance this distension in my stomach not wanting to eat um and it would kind of subside by day four or five and then certainly by day seven when it was time to get the next dose it was largely back to baseline or somewhat close to baseline. So they were unable to determine when or how frequently the events occurred over the course of treatment or whether event occurrence depended on any other patient characteristics like the presence of type 2 diabetes. So the third thing is that natural language processing can misclassify or overlook nuanced context, which is what we were saying before about interpreting things and like you could say two words or the same the same expression meaning two different things or say two words that sound like they should mean opposite but actually mean the same thing. So they validated the specific models used in the study against manually annotated samples so where they actually had humans looking through this to take samples and and and read through and see okay I think this person has you know nausea I think this person has irregular periods because I'm using human language skills to interpret what's being written and and categor it. So um you know they had a high performance comparable to prior adverse event extraction systems. So they feel like overall the data extraction was pretty good um and you know they feel that their validation approach ensured that there was reliable extraction for the application. Certain self-reported effects may not fit neatly into these um medical data dictionary concepts or they may have been misclassified based on the user's description. So one example they give is that some things that were classified as reflux, which is heartburn, contents of your stomach going up into your esophagus if that was uh bucketed as as reflux or GERD gastroesophagal reflux disease GERD based on user terminology, it might have instead been recorded in a clinical trial as dyspepsia, which is just a general term meaning upset stomach basically so um they wanted to try to you know parse this better so you could be really specific about the symptoms. So without demographic and clinical data to match or adjust for confounding between medication groups, they can't determine whether observed differences in complaint frequencies are attributable to the specific formulations versus differences in the populations that are using each formulation. So that's a key insight which is that you don't know if the reason there's some side effect profiles are a little bit different on trusepatide and versus semaglutide group is it because that trisepatide is itself less likely to cause these side effects than semiglutide or is it because people who are on trzepatide are somehow different from people who are on semaglutide in some aspect somebody who tells you that they're really prone to nausea is probably going to be enrolled in taking trzepatide rather than sepaglutide at least in my practice because I know that truse causes less nausea. So you know there's again bias both self-selection on the part of the patient and the way we can bias where we put patients who then subsequently potentially participate in talking about their symptoms on these kinds of forums. So despite the limitations they go on to summarize that social media data provide important insight into these symptoms and they may be helpful in identifying those rarer or underreported effects that should be investigated further. And they do comment and this is very pertinent as well to my breast implant illness community which is that quote online health communities are increasingly influential in shaping patient expectations and treatment decisions. And a growing body of research examines these platforms across a range of contexts so social media discussion of things is here to stay it is influencing what people think to ask about things to bring to their doctors to talk about we should be aware of it as providers understand what people are talking about so that we can have informed, nuanced conversations with patients. And while we always talk about how we learn from our patients you also don't want to be caught in a situation where the patient knows so much more about something that you lose credibility because there's still an accountability matrix of as a physician, well you're the doctor you should know this you should have prescribed me this or you should have done this for me but I talked to you you understood this as well as I did but I'm not a doctor you know so you you need to kind of have that authority and that means staying well informed. So I think this kind of study is really useful to understand what people are really talking about in the real world. So um the last thing they say is that you know if you encounter patients on these meds asking you about their periods or temperature things, um you can tell them hey I know there's one study that that indicated that when people talk about their own symptoms on social media, these things have come up more commonly than they did in the clinical trial. So it's plausible that that's an issue for you too. Let's see what we can do to help you with that or maybe send you for some testing and so on and so forth. So I think this is really cool. I think it's gonna be really interesting to see where AI analysis of patient reported data takes us. We already know that AI is being used now for drug discovery to help um you know investigate molecules and come up with chemical formulations. And that's just going to get more and more sophisticated I think as these models learn and as we develop more sophisticated models as scientists. So I hope this has been informative. I found it very interesting as always here on the scalpel's edge we welcome your feedback and your um suggestions on topics on guests um things you'd like us to tackle uh so please if you like what you're hearing please go on to your platforms where you get your so your uh podcast content and listen to rate and review all episodes of the scalpel's edge and until we meet again I've been your host here Tim SiteMD, double board certified plastic surgeon in Southern California and as always stay well and keep on keeping on