WEBVTT 00:00.031 --> 00:17.854 [SPEAKER_00]: I think almost everyone, picking up the newspaper, looking online, especially online, is likely to be very confused about how diet affects health or anything else, because you'll find for almost every food that if you look on internet, it's either a kill you or make you want some more, but everything in between. 00:18.880 --> 00:26.517 [SPEAKER_05]: Yes, the headlines, the social media reels feel like they're all over the place and the topic of a nutrition research feels quite pressing. 00:26.958 --> 00:34.695 [SPEAKER_05]: And so we've got a great episode lined up featuring the Crave trial on coffee and arrhythmia's published in The New Lundryl of Medicine in March 2023. 00:35.114 --> 00:41.684 [SPEAKER_02]: And with that, we'd like to welcome you to another episode of Beyond Journal Club, a collaboration between Corei M and any jam group. 00:42.606 --> 00:51.880 [SPEAKER_01]: The goal of Beyond Journal Club is to take landmark clinical trials, and to put them into context, telling the story of how we got to where we are, and what it means for how we take care of our patients. 00:51.900 --> 00:54.344 [SPEAKER_05]: I'm Dr. Schwarz, a Travati, an internist of BIDMC. 00:55.105 --> 01:00.573 [SPEAKER_01]: I'm Dr. Klumlee, a met-beez hospitalist within the masterial program system, and a WD editor of any jam clinician. 01:01.415 --> 01:03.518 [SPEAKER_01]: I'm Dr. Greg Katz, cardiologist at NYU. 01:04.105 --> 01:06.368 [SPEAKER_06]: And I'm Dr. Katarina Lynn, N.E.J.M. 01:06.388 --> 01:07.249 [SPEAKER_06]: editorial fellow. 01:08.370 --> 01:15.499 [SPEAKER_02]: So I'm so excited that we get to delve into nutritional research today because this is what patients ask us about all the time. 01:15.539 --> 01:19.984 [SPEAKER_02]: I mean, I cannot tell you how many people come to see me, who are confused about what to eat or drink. 01:20.565 --> 01:21.626 [SPEAKER_02]: Is red wine good or bad? 01:21.666 --> 01:22.167 [SPEAKER_02]: What about meat? 01:22.267 --> 01:22.808 [SPEAKER_02]: What about eggs? 01:22.908 --> 01:23.629 [SPEAKER_02]: What about coffee? 01:24.530 --> 01:30.417 [SPEAKER_06]: And we're so fortunate to have Dr. Walter will adhere with us to 01:31.291 --> 01:36.696 [SPEAKER_00]: that was told when I was a doctoral student that probably diets important, but it's just too complicated. 01:37.196 --> 01:39.018 [SPEAKER_00]: But I sort of like complicated things. 01:40.179 --> 01:46.064 [SPEAKER_06]: Dr. Walter Will is professor of epidemiology and nutrition at the Harvard TH Chan School of Public Health. 01:47.065 --> 01:53.531 [SPEAKER_02]: And he's been doing nutrition research for decades, and he's one of the most cited people in literally just all of science, not just nutrition. 01:54.372 --> 01:55.893 [SPEAKER_05]: Yeah, I'm pretty big deal. 01:55.913 --> 02:00.437 [SPEAKER_05]: So today we're going to start by getting into why it's so hard to ask the big questions with nutrition. 02:00.772 --> 02:07.530 [SPEAKER_01]: and then we'll discuss what we can clean and what we have to look out for in both large RCTs versus observational trials. 02:08.131 --> 02:12.542 [SPEAKER_02]: And finally, we'll get into the crave trial to help answer the question that our patients really care about. 02:12.823 --> 02:16.232 [SPEAKER_02]: Can I have a cup of coffee in the morning or is it gonna give me a regular heartbeats? 02:22.658 --> 02:27.723 [SPEAKER_05]: All right, yeah, I don't know about you guys, but like I was saying earlier, with all these health influencers, right? 02:27.763 --> 02:36.171 [SPEAKER_05]: They say things with such certainty, sometimes that even with my own education and the degrees that I have, I can sometimes even get persuaded. 02:36.191 --> 02:43.778 [SPEAKER_05]: And this is all saying that I also know at the same time nutrition research cannot be simplified into these 60 second clips. 02:43.859 --> 02:46.161 [SPEAKER_05]: And so let's get to nutritional research. 02:46.361 --> 02:48.043 [SPEAKER_05]: And why it's so hard to study? 02:48.083 --> 02:50.505 [SPEAKER_05]: And you know, often times, 02:50.485 --> 02:53.745 [SPEAKER_05]: way to complicated draw quick zinger conclusions from. 02:54.957 --> 03:05.270 [SPEAKER_00]: Well, in the perfect ideal world, we would just do randomized trials, but if we're practicality, they're very often, in fact, usually go to be not possible to do. 03:06.031 --> 03:16.945 [SPEAKER_00]: For example, for red meat consumption, it probably really need to be on a bad diet for three or four decades before you actually have a mild cardinal infection. 03:17.005 --> 03:22.872 [SPEAKER_00]: And we know that because you don't have those diseases before age 30 or 40 years 03:23.206 --> 03:30.057 [SPEAKER_00]: So again, if you're doing a randomized trial, that's not going to be feasible to randomize many thousands of people that birthed in favor of them. 03:31.139 --> 03:38.552 [SPEAKER_05]: So the effects of diet on outcomes that we care about, whether it be cardiovascular disease, cancer, mortality, takes decades to show up, right? 03:38.592 --> 03:44.742 [SPEAKER_05]: And most people, you know, lead and barely make a change in our diet consistently for a week, a little, you know, 30 years. 03:45.380 --> 03:53.191 [SPEAKER_02]: and even a randomized control trial that has perfect adherence to nutrition has its own set of problems because it's really hard to just test one thing. 03:53.811 --> 03:59.679 [SPEAKER_02]: If you tell somebody to eat more of one thing, that means they're eating less of something else or they're eating more calories overall. 04:00.200 --> 04:05.768 [SPEAKER_02]: And so ideally, we would love to change one variable at a time and see the effect, but that's impossible in nutrition. 04:06.048 --> 04:10.594 [SPEAKER_02]: And so you can't do the typical placebo versus drug that you would do in other types of studies. 04:11.384 --> 04:17.276 [SPEAKER_06]: And then when these trials are run, we need to consider whether people are actually following their signed interventions. 04:18.018 --> 04:19.120 [SPEAKER_06]: Take for example the Mr. 04:19.140 --> 04:20.323 [SPEAKER_06]: Fit trial from the 1980s. 04:21.305 --> 04:26.676 [SPEAKER_06]: It was a RCT that included replacing saturated fat with polyunsaturated fat. 04:27.787 --> 04:29.469 [SPEAKER_00]: And in the end, there was no effect. 04:30.030 --> 04:36.239 [SPEAKER_00]: The people who joined mostly had already changed their diet, because they'd read the news and made the changes already. 04:36.680 --> 04:45.592 [SPEAKER_00]: And then as a trial went on, they're the intervention group did reduce their saturated fat intake, but the control group did it right in parallel. 04:45.993 --> 04:51.761 [SPEAKER_00]: So in the end, there was really never any meaningful difference between the intervention and the control group. 04:52.082 --> 04:54.385 [SPEAKER_00]: This is hard business. 04:55.377 --> 05:09.042 [SPEAKER_00]: So the best alternative will usually be long-term epidemiologic studies like we're doing plus combining that information with results from shorter-term studies with intermediate endpoints. 05:10.184 --> 05:14.652 [SPEAKER_01]: Yeah, it's good to hear from Dr. Willow why we often must resort to observational studies. 05:14.632 --> 05:18.778 [SPEAKER_01]: and we will review the Bradford Hill criteria on a previous episode on microplastics. 05:19.198 --> 05:29.352 [SPEAKER_01]: These are criteria to help identify strong associations and observational studies that can point towards causation that we can never really say that the Bradford Hill criteria proved causation. 05:29.412 --> 05:40.707 [SPEAKER_05]: Yeah, and with all that in mind, let's get into when we look at an nutritional study, how we can look at it with a critical eye and really build up that chain of causality with some level of confidence. 05:41.767 --> 05:47.596 [SPEAKER_00]: For the average person or physician, looking at that, I think there's several things to consider. 05:47.657 --> 05:52.424 [SPEAKER_00]: First of all, use of the first study is the most unreliable study. 05:53.045 --> 05:59.295 [SPEAKER_00]: It's the replicated finding that is going to be what you, I think, trust more in terms of making any decisions. 05:59.916 --> 06:07.048 [SPEAKER_00]: It's been reproduced by two or three other groups, or sometimes the same investigators using additional approaches. 06:07.028 --> 06:12.039 [SPEAKER_00]: So reproducibility is really important, not just the most recent finding. 06:12.860 --> 06:15.105 [SPEAKER_00]: And then also, how does it fit with other evidence? 06:15.506 --> 06:24.565 [SPEAKER_00]: Do we have some studies that show, for example, in controlled feeding studies that an intermediate endpoint points in the same direction? 06:24.545 --> 06:50.788 [SPEAKER_00]: Sometimes animal models, consistent animal models can help, but usually that's so far from human biology that those are not going to be so reliable, so mostly I think consider first to study itself as a bit prospective as a large long term, and if you can have the methods for assessment been validated, although that may not be in the story, but then how to 06:51.781 --> 06:52.122 [SPEAKER_05]: night. 06:52.142 --> 06:53.887 [SPEAKER_05]: So I appreciate hearing that that process, right? 06:53.907 --> 06:58.179 [SPEAKER_05]: Like when you see a new headline in the world of nutrition or a new research study. 06:58.199 --> 07:06.583 [SPEAKER_05]: And you know, he's mentioned a bunch of times he's like short term intermediate endpoint studies and I just want to clarify what exactly he meant by these. 07:07.188 --> 07:11.558 [SPEAKER_00]: I can use an example of trans fatty acid and take and heart disease. 07:12.059 --> 07:17.250 [SPEAKER_00]: People were doing some short-term studies looking at changes in blood lipids as the outcome. 07:17.751 --> 07:26.631 [SPEAKER_00]: These were studies controlled feeding studies of about 50 people and putting my diets for about three weeks and then looking at short-term changes in. 07:26.611 --> 07:35.140 [SPEAKER_00]: Those short term studies did show that Transfet elevated LDL cholesterol, reduced HDL cholesterol, and then elevated blood triglycerides. 07:35.180 --> 07:40.786 [SPEAKER_00]: And we know that that pattern of lipid changes is associated with increased risk of heart disease. 07:40.826 --> 07:52.618 [SPEAKER_00]: So putting those two kinds of studies together, and each of those were replicated over time, that gave us a really strong foundation to conclude that trans fats were an important risk factor for heart disease. 07:53.375 --> 07:58.804 [SPEAKER_06]: So we're using short term intermediate end points in addition to the larger epidemiological studies. 07:59.565 --> 08:06.277 [SPEAKER_06]: And for many of these studies, we're recording diet with methods like the 24-hour dietary recall or food frequency questionnaires. 08:07.178 --> 08:11.225 [SPEAKER_01]: Yeah, and a lot of these food frequency questionnaires, there's a lot of bias that comes with them. 08:11.746 --> 08:15.432 [SPEAKER_01]: So let's listen to how Dr. Willet tries to minimize the bias for these recal methods. 08:15.973 --> 08:19.078 [SPEAKER_01]: And then perhaps we're going to apply 08:19.936 --> 08:30.333 [SPEAKER_00]: In our studies, what's really important is that we are minimizing bias, because their prospective studies were collecting the information before people are diagnosed with disease. 08:30.373 --> 08:36.362 [SPEAKER_00]: Once they've got a disease, then we're very likely to get biased information there, thinking about their diet differently. 08:36.402 --> 08:42.332 [SPEAKER_00]: So, the important point is that we're getting the information in a way that's unbiased with respect to disease. 08:42.903 --> 08:43.906 [SPEAKER_05]: Yeah. 08:43.927 --> 08:54.162 [SPEAKER_05]: So, prospectively, before someone has a disease in question, can help, but there are also other steps that Dr. Willet takes specifically when it comes to these self-reported questionnaires and recalls. 08:55.357 --> 09:15.475 [SPEAKER_00]: And then we've done, from the very beginning, a series of what we call validation or calibration studies, where we take actually now, our most recent one, about 1,300 people who were already in our study and then we've gone back to them and collected very detailed data, are using way diet records, recording everything that they eat over. 09:15.455 --> 09:22.310 [SPEAKER_00]: Two, one week periods over a year, we have lots of biomarkers from blood measure, but fewer in measurements, double the level of water. 09:22.871 --> 09:36.079 [SPEAKER_00]: Measurements which gets it energy, intake, and so we can compare our simple questionnaire provided by several hundred thousand people with this very detailed measurement, and then we can actually do statistical corrections. 09:36.059 --> 09:38.182 [SPEAKER_00]: to adjust for a measurement error. 09:38.623 --> 09:43.049 [SPEAKER_00]: But what's really very important is that we have repeated these measurements every four years. 09:43.670 --> 09:55.468 [SPEAKER_00]: A very few, in fact, I don't think any other studies have actually done that before, and that does turn out to be really important because people's preferences change over time, manufacturing changes over time. 09:56.326 --> 10:07.844 [SPEAKER_05]: Oh man, so the next time I look at industrial study, I know after hearing the steps that he takes, I'll also try to see, did these investigators take other measures to actually bear high the software-ported data collection? 10:07.864 --> 10:11.270 [SPEAKER_01]: Okay, it's time for me to be in this area in the room again. 10:11.290 --> 10:24.190 [SPEAKER_01]: I hate doing this, but I just have to bring up, even though we now have some extra tools from Dr. Willett to help us make the data more trustworthy, I think there are still a lot of 10:24.170 --> 10:36.590 [SPEAKER_02]: So for most of these observational studies, the data is collected from a food frequency questionnaire, and we need to keep in mind that even really well validated data collected over a short period of time, and then it's extrapolated to all of these years. 10:37.131 --> 10:46.707 [SPEAKER_02]: And we just need to be honest, that even if you're measuring people for two weeks and you're tracking every morsel that goes into their mouth, you don't know what's happening for all of the other years in their lives. 10:46.727 --> 10:50.413 [SPEAKER_02]: I mean, most people's diets change from day to day or week to week or month to month, and 10:50.393 --> 10:54.481 [SPEAKER_02]: We're not following people around for decades figuring out what they're putting in their mouths. 10:55.543 --> 11:05.263 [SPEAKER_06]: Right, Greg, and another thing to keep in mind is that people signing up for these nutritional studies might be more likely to do other healthy behaviors, meaning the healthy user effect. 11:05.868 --> 11:14.058 [SPEAKER_01]: Yeah, and we also need to think about some very common confounders and to make sure that they were controlled for these confounders might include health care use in social economics status. 11:15.020 --> 11:24.852 [SPEAKER_02]: And all of that rigor is really helpful, but we're still left building a chain of evidence from imperfect data sources and even if we're talking about the same food, we might be talking about different things. 11:24.932 --> 11:27.876 [SPEAKER_02]: And so if you tell me you eat ground beef once a week. 11:27.856 --> 11:32.141 [SPEAKER_02]: 80 20 ground beef is a very different product than 93 seven ground beef. 11:32.241 --> 11:35.826 [SPEAKER_02]: And so the level of complexity with all of this stuff is just profound. 11:36.046 --> 11:39.690 [SPEAKER_02]: And sometimes it makes it hard to know if we're even assessing the same thing. 11:40.611 --> 11:47.580 [SPEAKER_01]: And something else to bring up is that we have evidence linking entire diets to lipids, blood pressure, and cardiovascular events. 11:48.040 --> 11:52.986 [SPEAKER_01]: But that still leaves a lot of uncertainty when patients ask about specific foods, not diets. 11:53.307 --> 11:57.812 [SPEAKER_01]: So like we could study the 11:57.792 --> 12:01.397 [SPEAKER_02]: But even if you're talking about eggs, sometimes that raises more questions than it answers. 12:01.517 --> 12:03.901 [SPEAKER_02]: And so with eggs, what's the bioactive compound? 12:03.941 --> 12:05.583 [SPEAKER_02]: Is it the entirety of the food matrix? 12:05.684 --> 12:07.045 [SPEAKER_02]: Is it a specific preparation? 12:07.446 --> 12:08.007 [SPEAKER_02]: Is it the dose? 12:08.027 --> 12:08.688 [SPEAKER_02]: Is it the timing? 12:08.888 --> 12:10.551 [SPEAKER_02]: And coffee's another great example. 12:10.871 --> 12:14.957 [SPEAKER_02]: It's so commonly consumed, but coffee has a million things in it and it's really hard to study. 12:15.815 --> 12:18.323 [SPEAKER_05]: Yeah, exactly, coffee isn't just caffeine, right? 12:18.363 --> 12:21.795 [SPEAKER_05]: It's the antioxidants, the polyphenols, the other biocdo compounds. 12:21.815 --> 12:23.782 [SPEAKER_05]: So yeah, it is a complex question. 12:24.404 --> 12:25.989 [SPEAKER_05]: When we ask, is coffee good or bad? 12:26.009 --> 12:28.457 [SPEAKER_05]: That is a total oversimplification. 12:35.035 --> 12:42.993 [SPEAKER_05]: Alright, so after all the discussion about nutrition research and the complexities of it, let's make it a bit more concrete and do some application. 12:43.474 --> 12:48.505 [SPEAKER_05]: Let's talk about coffee and that oversimplified question, is it good or bad? 12:48.940 --> 12:55.248 [SPEAKER_02]: If I had a dollar for every time a patient asked me if coffee was good or bad, I think that swim lessons for my kids would feel so much more affordable. 12:55.629 --> 13:02.819 [SPEAKER_02]: Like, I literally have patients asking me every single day of my life whether coffee is bad or good for them if they're allowed to have a cup every single day. 13:02.939 --> 13:05.442 [SPEAKER_02]: And the concern really makes intuitive sense. 13:05.462 --> 13:06.784 [SPEAKER_02]: I mean caffeine is a stimulant. 13:06.804 --> 13:15.876 [SPEAKER_02]: It affects autonomic tone, calcium handling, catacolamines, and so for decades, so many of my patients their whole lives they've been told that coffee might provoke irregular heartbeats. 13:15.856 --> 13:22.052 [SPEAKER_01]: Okay, but I also have them there whenever I drink coffee, Greg, I also get palpitations, so I really do sympathize with your patience. 13:22.910 --> 13:26.895 [SPEAKER_06]: And a lot of people will still drink coffee, even if it gets all the symptoms. 13:27.395 --> 13:27.976 [SPEAKER_01]: Yeah, like me. 13:29.437 --> 13:30.619 [SPEAKER_06]: Well, let's look at the evidence. 13:30.839 --> 13:33.562 [SPEAKER_06]: So it's been really popular along study topic. 13:33.722 --> 13:46.757 [SPEAKER_06]: Many observational studies haven't shown increased risk between coffee and a fib, including large cohorts and metanalysis and surprisingly some events just lower a fib risk among certain coffee drinkers. 13:46.737 --> 14:00.223 [SPEAKER_05]: Yeah, and speaking of the overall benefit of coffee, I just want to put out there like this one big observation site that was actually published and then new adrenaline of medicine back in 2012 and show that those who drink more coffee actually tended to have a lower risk of death. 14:00.828 --> 14:09.115 [SPEAKER_02]: You know, you can read a lot about coffee and all of coffee's effects on health and, you know, I sometimes I feel that you can take any of the individual components and find a mechanism. 14:09.155 --> 14:14.520 [SPEAKER_02]: And then you pick catacombs, you say increases sympathetic stress, you pick antioxidants, you say it helps with inflammation. 14:15.441 --> 14:15.641 [SPEAKER_01]: Right. 14:15.922 --> 14:20.606 [SPEAKER_01]: As a fair mention before, there are so many ingredients, polyphenols, antioxidants, vital chemicals. 14:21.146 --> 14:24.830 [SPEAKER_01]: And so, some of these might have anti-inflammatory or cardiovascular effects. 14:25.390 --> 14:30.835 [SPEAKER_01]: So, even mechanistically, I don't think it's obvious which ingredient 14:30.815 --> 14:41.598 [SPEAKER_02]: And so if you want to be an influencer, basically pick a random molecule in coffee, find a plausible biological mechanism, and then the epidemiology you like, and then post about it on social media, and then boom, goes viral. 14:41.639 --> 14:45.988 [SPEAKER_02]: You have 5,000 comments on Instagram, including people fighting with each other in the comment thread. 14:45.968 --> 15:14.541 [SPEAKER_05]: people painful all of it yeah so I think we all agree that observational studies especially the diverse group of chemicals that actually make up coffee those observation studies aren't perfect but the creature out of the one that Catarina picked out was you know really asking a more targeted question this question was does short term coffee consumption lead to our friend years this is a much easier question to answer because we have more control over short term coffee consumption right even if we can't control all the specific ingredients in said coffee 15:14.622 --> 15:18.781 [SPEAKER_06]: Right, and so investigators of this RCT had a more focused goal in mind. 15:19.344 --> 15:24.025 [SPEAKER_06]: What actually happens to heart rhythms on days when people drink coffee versus when they don't? 15:24.730 --> 15:44.933 [SPEAKER_01]: Now some of you like me might be wondering what the acronym CREV stands for, and so I'm here to tell you that it stands for coffee and real-time atrial and ventricular activity, which I think described the trials as simply, so I give this 10 out of 10. premature atrial contractions with the primary outcome, but ventricular activity was also measured as a secondary outcome. 15:44.913 --> 15:48.540 [SPEAKER_02]: climb the investigators to thank you for your compliments on their acronym. 15:48.740 --> 15:54.471 [SPEAKER_02]: And so after the trial was done, the media headline basically simplified this to caffeinated coffee is safe. 15:54.592 --> 15:56.836 [SPEAKER_02]: There's no increase in premature age real contractions. 15:57.297 --> 15:59.902 [SPEAKER_02]: But that headline, it's true, but it hides a lot of nuance. 16:00.723 --> 16:01.645 [SPEAKER_01]: Yeah, so let's get into it. 16:02.206 --> 16:04.170 [SPEAKER_01]: Who were the participants in this trial, Keterina? 16:04.825 --> 16:09.035 [SPEAKER_06]: So there were a hundred healthy people and they were on average 39 years old. 16:09.597 --> 16:21.265 [SPEAKER_06]: Most were non-Hispanic white and the medium BMI was 24 and very few had chronic health conditions like diabetes or hypertension and at baseline about half-drink 1-3 cups of coffee daily. 16:21.835 --> 16:22.235 [SPEAKER_01]: Okay. 16:22.376 --> 16:24.238 [SPEAKER_01]: So far, nothing crazy there. 16:24.278 --> 16:30.765 [SPEAKER_01]: I also found this to be really interesting that the participants didn't know there are assignments until the night before. 16:31.346 --> 16:36.672 [SPEAKER_01]: So the night before they were going to text messages telling them that they were to drink coffee or not drink coffee for the next day. 16:36.732 --> 16:40.396 [SPEAKER_01]: There was also a second text message at 8 a.m. the next morning. 16:41.037 --> 16:49.446 [SPEAKER_01]: And so for the 14-day trial, each day was randomized and researchers made sure that no person got the same assignment of coffee 16:49.747 --> 16:53.472 [SPEAKER_05]: Um, can you just imagine getting a text message or be like, you can't drink coffee tomorrow. 16:54.494 --> 16:55.295 [SPEAKER_05]: Um, I think it's a good point. 16:55.435 --> 17:06.069 [SPEAKER_05]: How do the investigators make sure that the participants who got the text message to drink coffee will actually were drinking coffee and the ones I were randomized to have standing from coffee did not drink their coffee. 17:06.630 --> 17:12.278 [SPEAKER_02]: If I'd been this trial, I would have certainly been excluded because I would have withdrawn consent and might not be able to. 17:12.258 --> 17:23.115 [SPEAKER_02]: So it's super clever how they track these folks and so participants were given fit pit watches, zio patches, continuous glucose monitors, and a smartphone app called Eureka that track their geolocation. 17:23.135 --> 17:29.785 [SPEAKER_01]: Yeah, so the researchers basically track their participants using this app to see if they went into a coffee shop or stayed away from a coffee shop. 17:30.346 --> 17:34.993 [SPEAKER_01]: And this is specifically for people who were reported in the beginning of the study that they went to coffee shops to get coffee. 17:35.334 --> 17:38.198 [SPEAKER_01]: This didn't really apply to people who may their own coffee set home. 17:38.380 --> 17:43.966 [SPEAKER_01]: They also gave participant surveys to fill out and then had them press a button on their ZO patch when they drink the coffee. 17:44.386 --> 17:50.052 [SPEAKER_01]: And both of these, we know, as a weaker form of validation since people can forget to press a button or lie on a survey. 17:50.093 --> 17:58.361 [SPEAKER_06]: Interestingly, they were offered reimbursement for coffee, even if they didn't follow their assigned coffee days as long as they provided receipts. 17:59.262 --> 18:06.430 [SPEAKER_06]: It's a smart way to try to make coffee reporting more accurate since people reimbursed regardless of whether they followed their randomization. 18:07.372 --> 18:08.493 [SPEAKER_05]: Yeah, that is smart. 18:08.673 --> 18:14.880 [SPEAKER_05]: I definitely would fess up that I accidentally turn coffee even if I was supposed to knowing that hey, I got some reimbursement out of it. 18:15.361 --> 18:17.423 [SPEAKER_05]: All right, now let's get into the end points though. 18:18.104 --> 18:22.589 [SPEAKER_05]: Start with our primary outcome, PAC's premature atrial contractions. 18:23.130 --> 18:25.092 [SPEAKER_05]: I got to say, why? 18:25.112 --> 18:28.556 [SPEAKER_05]: Like, I don't know. 18:28.576 --> 18:30.578 [SPEAKER_05]: And maybe this is embarrassing to say, but 18:30.558 --> 18:33.762 [SPEAKER_05]: I don't like, I kind of like ignore PACs when I see them on EKGs. 18:34.723 --> 18:54.388 [SPEAKER_02]: So, I basically ignore PACs also unless they're really symptomatic, so I don't think that you're wrong there, but the thing that really everybody is worried about with caffeine is the risk of AFIM, and, you know, if you look at the burden of PACs across a population or a foreign individual, the burden of PACs is a pretty decent predictor of future AFIM. 18:54.368 --> 19:01.762 [SPEAKER_02]: So from a clinical perspective, PACs are a pretty reasonable target if you want to think about the risk of a fib down the road. 19:02.203 --> 19:09.897 [SPEAKER_02]: It's not perfect and, you know, ideally you'd power the trial and follow people for long enough to actually see a fib, but looking at PACs isn't so bad. 19:10.383 --> 19:12.505 [SPEAKER_05]: Okay, thank you for explaining that a bit more. 19:12.526 --> 19:14.528 [SPEAKER_05]: And I guess Catarina, I'll turn it over to you. 19:14.648 --> 19:20.054 [SPEAKER_05]: Would you do the honors of telling us what do they find regarding coffee drinking and PECs on those cyopatches? 19:21.076 --> 19:24.660 [SPEAKER_06]: So for the daily number of PACs, they found no difference. 19:25.240 --> 19:31.227 [SPEAKER_06]: So for coffee versus no coffee days, there were 58 versus 53 PACs over 24 hours. 19:31.988 --> 19:36.053 [SPEAKER_02]: That's like two PACs an hour, so basically a minimal burden. 19:36.758 --> 19:37.859 [SPEAKER_01]: interesting. 19:38.140 --> 19:39.902 [SPEAKER_01]: And there were multiple secondary outcomes. 19:40.342 --> 19:50.094 [SPEAKER_01]: So they looked at PVCs, so premature of intricular contractions, step counts, sleep, and glucose levels, and these were all using the gadgets they had put on the participants. 19:50.815 --> 19:51.015 [SPEAKER_02]: Yeah. 19:51.035 --> 19:55.300 [SPEAKER_02]: So there's no difference in their glucose levels, but the other secondary outcomes are really interesting. 19:55.340 --> 20:00.066 [SPEAKER_02]: There were more PVCs on days drinking coffee, 154 versus 102 on average. 20:00.046 --> 20:11.879 [SPEAKER_02]: The people in the study also took more steps during their coffee days about 1,000 more steps each day on average, but they 36 fewer minutes of sleep per night, both of those measured be of their fit pit. 20:11.899 --> 20:21.350 [SPEAKER_01]: And when they analyze a data per coffee drink, for each cup of coffee someone drank, they had 587 more steps, but 14 minutes less sleep daily per cup of coffee. 20:22.071 --> 20:22.832 [SPEAKER_05]: Uh, interesting. 20:22.852 --> 20:27.657 [SPEAKER_05]: I can't have a winter like for people just walking more to coffee shops and that's why they had more steps. 20:28.143 --> 20:31.109 [SPEAKER_01]: Yeah, I think that is certainly one theory that has been brought up. 20:31.469 --> 20:34.956 [SPEAKER_01]: The other is that maybe coffee gives you more energy and helps you exercise more. 20:34.996 --> 20:39.906 [SPEAKER_01]: And to put that in your perspective, the average American walks about 5,000 steps a day. 20:39.946 --> 20:45.797 [SPEAKER_01]: So if coffee makes you walk 1,000 steps more, that's like a 20% increase in exercise. 20:46.216 --> 21:04.765 [SPEAKER_06]: that is awesome right like I feel like Duncan starbucks like they got a new model like did your trainers increase your stepcap by twenty percent like that yeah before we get carried away it's worth mentioning again that this was a small time limited study there were only a hundred people and the trial was only two weeks 21:05.150 --> 21:07.916 [SPEAKER_01]: Yeah, but I think we got to give the researchers credit where it's due. 21:08.317 --> 21:11.585 [SPEAKER_01]: We talked a lot about how nutritional studies are really hard to perform. 21:12.628 --> 21:17.298 [SPEAKER_02]: And to that, there's multiple reasons from a research perspective why this study is rigorous. 21:17.679 --> 21:20.526 [SPEAKER_02]: The first is to very clear intervention. 21:20.506 --> 21:22.530 [SPEAKER_02]: Second, the adherence was really well tracked. 21:22.991 --> 21:29.724 [SPEAKER_02]: Third, these outcomes, PAC's, PBC's, stepcats, they're objective, and so it's not based on symptoms, there's no placebo effect. 21:29.864 --> 21:30.906 [SPEAKER_02]: It's not palpitations. 21:31.467 --> 21:36.056 [SPEAKER_02]: And, for everybody served as their own control, coffee on some days, no coffee on others. 21:36.116 --> 21:39.122 [SPEAKER_02]: And so, we don't really need to worry about balancing the groups. 21:39.102 --> 21:39.683 [SPEAKER_02]: This is nice. 21:39.703 --> 21:42.186 [SPEAKER_02]: It's a type of nutrition question that is truly testable. 21:42.386 --> 21:49.194 [SPEAKER_02]: This is not just coffee cause cancer, but does coffee over a short-term period cause this concrete thing that we can truly measure. 21:49.254 --> 21:52.358 [SPEAKER_02]: So I'm personally really happy that we have this strap. 21:52.378 --> 21:55.282 [SPEAKER_04]: And that is a big deal coming from Greg Katz if anyone knows. 21:58.085 --> 22:04.013 [SPEAKER_05]: All right. 22:04.033 --> 22:08.518 [SPEAKER_06]: So where does this leave us with coffee and then the messaging to our patients? 22:08.701 --> 22:10.163 [SPEAKER_06]: It's a complicated question. 22:10.544 --> 22:15.592 [SPEAKER_06]: Crave was done on healthy people, so we can't extrapolate it to people with cardiovascular disease. 22:16.274 --> 22:27.452 [SPEAKER_06]: And so it's really more complicated than blanket statements, like coffee is positive, no increase in PACs, people are more active, or on the flip side, coffee is negative, more ventricular, ecto-p, less sleep. 22:28.495 --> 22:32.322 [SPEAKER_01]: Yeah, Catarina and both of those interpretations could technically be correct. 22:32.702 --> 22:38.292 [SPEAKER_01]: If I'm counseling like a young, healthy person who values energy and activity, I think this data feels reassuring. 22:38.853 --> 22:45.525 [SPEAKER_01]: But if I'm talking to someone with symptomatic PVCs or a lot of sleep issues, I think this data leads to a very different conversation. 22:45.944 --> 22:54.219 [SPEAKER_05]: Yeah, like, like, you have symptomatic PVCs or we're presuming every time you drink coffee to rounds, but does that mean for your long-term cardiovascular health? 22:54.399 --> 22:56.663 [SPEAKER_05]: Again, like, I'm still stuck on those endpoints, right? 22:56.884 --> 22:59.869 [SPEAKER_05]: I don't know the relevance of those PACs and PVCs per se. 23:00.372 --> 23:04.798 [SPEAKER_02]: My honest assessment is that we can't really tell anything about long-term cardiovascular risk. 23:04.818 --> 23:13.369 [SPEAKER_02]: And more than that, there's a difference between saying that PACs are associated with aphid versus something is associated with more PACs, so it's also associated with aphid. 23:13.550 --> 23:14.791 [SPEAKER_02]: Those aren't really the same thing. 23:15.312 --> 23:30.312 [SPEAKER_02]: And going back to the study, 50 PACs over a 24-hour period, that is a normal number of PACs for a healthy, like, totally well patient to have. 23:30.882 --> 23:44.481 [SPEAKER_02]: Yeah, it's really interesting because PVC is our often thought of as a harbinger of bad cardiovascular outcomes, but even a hundred PVC's in 24 hours is it's kind of a nothing burger for a sick patient who has heart failure, let alone a young healthy patient who doesn't. 23:44.982 --> 23:56.738 [SPEAKER_02]: There's a hundred thousand heart beats in a 24-hour period, so I'm not going to even spend five seconds thinking about whether a hundred PVC's are a hundred and fifty PVC's is really anything much at all in the grand scheme of things. 23:57.494 --> 24:04.064 [SPEAKER_05]: So I guess what we're saying is Clem is not going to go into heart failure, you know, with the 150 PVC's having every day drinking coffee. 24:04.344 --> 24:04.765 [SPEAKER_02]: Yay. 24:06.587 --> 24:17.843 [SPEAKER_02]: But also, if you told me that I could get my patients to walk a thousand more steps a day by just giving them coffee, then there's a decent chance I would sneak into their houses and just force them to drink coffee every morning. 24:18.404 --> 24:21.409 [SPEAKER_01]: Okay, that's creepy and I'm going to be locking my doors for now on. 24:22.009 --> 24:23.772 [SPEAKER_01]: You're not my patient, Clem. 24:23.752 --> 24:29.020 [SPEAKER_01]: Yeah, exactly. 24:29.080 --> 24:30.342 [SPEAKER_01]: I do want to bring up one more study. 24:30.723 --> 24:33.267 [SPEAKER_01]: It's coffee in patients who already had a fib. 24:33.807 --> 24:38.935 [SPEAKER_01]: This was completely called decaf by the authors, which stands for does eliminating coffee of void fibrillation. 24:39.516 --> 24:41.980 [SPEAKER_01]: It was published in JAMA and November 2025. 24:41.960 --> 24:47.353 [SPEAKER_02]: So the DKF study took 200 coughing drinking patients who had a faeb and were going for cardiovascular version. 24:47.794 --> 24:53.267 [SPEAKER_02]: They had a half-drain caffeinated coffee for six months and another group not drink coffee for six months. 24:53.287 --> 24:58.399 [SPEAKER_02]: Fortunately, they saw that the coffee group actually had a lower rate of recurrence of a faeb or atrial flutter. 24:59.341 --> 25:03.206 [SPEAKER_06]: One thing was that the A-Fib and A-Futter were only clinically defined. 25:03.346 --> 25:07.051 [SPEAKER_06]: There wasn't a more structured or continuous way of measuring heart rhythms. 25:07.732 --> 25:13.980 [SPEAKER_05]: Ah, so it was going to have known if like a patient had, you know, a short bout of A-Fib while they were sleeping or if it happened subclinically. 25:14.000 --> 25:15.302 [SPEAKER_06]: Exactly. 25:15.402 --> 25:21.670 [SPEAKER_06]: And since most patients reported few A-Fib symptoms, even if A-Fib recurred, they may not have noticed it. 25:22.443 --> 25:31.006 [SPEAKER_01]: Yeah, and also maybe it's just me, but I feel like if you want to study if coffee triggers aphib, then you should probably include more people who said that coffee triggered their aphib. 25:31.547 --> 25:37.363 [SPEAKER_01]: And sadly, in the DKF trial, only 40% of the patients reported that coffee triggered their aphib in the first place. 25:37.715 --> 25:44.669 [SPEAKER_02]: But even with all of those caveats, these two studies are probably some of the best data that we're gonna have on the question of coffee and arrhythmias. 25:44.769 --> 25:59.858 [SPEAKER_02]: And so my take is that even if you take the most pessimistic read of the data for this group of patients who are pretty young and pretty healthy, that coffee is probably fine for you with respect to a regular heartbeats, but it might cause you to have a few more PVCs and mess up your sleep a little bit. 26:00.800 --> 26:09.137 [SPEAKER_06]: So what are you going to tell your patients the next time they ask, which for you, Greg, maybe tomorrow, if drinking coffee is good or bad for e-rhythmias? 26:09.277 --> 26:10.459 [SPEAKER_02]: I bet you it will be tomorrow. 26:10.579 --> 26:17.914 [SPEAKER_02]: And so when my patients even those who have a fib asked me if they can drink coffee, I tell them that if you like coffee, you can drink coffee. 26:17.894 --> 26:21.599 [SPEAKER_02]: But you shouldn't start coffee because it's a therapy for a fit because it's not. 26:22.180 --> 26:26.767 [SPEAKER_02]: And if it causes palpitations for you, like it does for clamp, then you don't have to drink it. 26:27.007 --> 26:35.059 [SPEAKER_02]: But if you like coffee, I don't think that there's any compelling evidence, even including these trials to say that it's harmful for you, even if you have irregular heartbeats. 26:41.637 --> 26:42.999 [SPEAKER_01]: Alright, so let's zoom out a little bit. 26:43.239 --> 26:49.168 [SPEAKER_01]: I think it's step one to be able to look at the data and see what they actually say and to interpret that correctly. 26:49.669 --> 26:54.937 [SPEAKER_01]: And hopefully we've given you enough tools up until now to interpret data with all of its caveats. 26:55.478 --> 27:00.405 [SPEAKER_01]: But then the next step which arguably is harder is actually talking to patients about nutrition. 27:01.145 --> 27:12.345 [SPEAKER_00]: So there's a lot of what might be called implementation research that needs to be done where we do know a good direction, but how to make it easy for people to move in that direction. 27:12.906 --> 27:20.559 [SPEAKER_00]: Certainly, good advice is important as a starting point, but almost in all cases just advising people alone is not sufficient. 27:20.579 --> 27:22.022 [SPEAKER_00]: It has to be. 27:22.002 --> 27:28.233 [SPEAKER_00]: There are barriers in terms of cost to be able to be for many people, and we want to try to remove those barriers as much as possible. 27:28.754 --> 27:31.279 [SPEAKER_00]: The role of physicians here, of course, is a key issue. 27:31.840 --> 27:46.626 [SPEAKER_00]: And one of the things I've realized for quite a while is we actually haven't given physicians the tools that they need to incorporate nutrition counseling into their practice or even life had some really good physicians during life. 27:46.606 --> 27:52.569 [SPEAKER_00]: If none of them has asked me about what I ate, then that's a starting point and only a starting point for moving on. 27:52.589 --> 27:56.565 [SPEAKER_00]: Where's how can you go stuff the discussion without knowing what a person's eating? 27:57.322 --> 28:02.210 [SPEAKER_05]: Yeah, I think we've all been guilty of this and not asking our patients what they're eating or drinking for that matter. 28:02.250 --> 28:07.820 [SPEAKER_05]: And think on top of it, the other common scenarios when our patients are bringing up a very specific nutrition question. 28:07.920 --> 28:09.703 [SPEAKER_05]: And A, I won't be able to help us with this, right? 28:09.723 --> 28:22.485 [SPEAKER_05]: Like, how do we communicate in a way that really resonates with the patient about what the nutrition's research is lacking and what it might be telling us and how do we say in some level of confidence knowing that there's all these gaps? 28:22.718 --> 28:33.152 [SPEAKER_02]: So I think a good rule of thumb is that when the data are mixed or even when there are confusing messages or contradictory messages about a topic, that probably means that the effect size is weak. 28:33.513 --> 28:38.679 [SPEAKER_02]: And so the stakes of any decision that you're making about that individual item is probably pretty low. 28:39.260 --> 28:52.438 [SPEAKER_02]: And so that's why when in general, I know this is not going to sound satisfying, but when I'm talking with patients about nutrition and we're focused on details that I don't think are all that important, I try to redirect them to things that 28:53.262 --> 29:00.285 [SPEAKER_05]: Yeah, well how do you like respond when a patient's like, oh, my wife is putting garlic all over my food, Dr. Cat, it's that good for me. 29:00.940 --> 29:05.966 [SPEAKER_02]: I've seen that too, and what I tell them is if you like garlic, then you should eat garlic. 29:06.346 --> 29:08.829 [SPEAKER_02]: But garlic is in a superfood because there's no such thing. 29:09.150 --> 29:23.607 [SPEAKER_02]: And so when people are asking me questions about very specific foods or phytochemicals or nutrients, you know, I try to redirect them to the bigger picture and nutritional advice that's consistent across a whole bunch of data sources. 29:23.647 --> 29:28.973 [SPEAKER_02]: But if you don't like something, you shouldn't be choking it down because again, there's no such thing as a magical food. 29:28.953 --> 29:45.455 [SPEAKER_02]: And so sometimes I'll have patients do a food log for a week or 24-hour diet recall, and I usually find that a fair number of my patients have very, very straightforward things that could be improved in their diet, whether they're drinking too many calories, they're eating baked goods, cookies, pastries, candies. 29:46.015 --> 29:55.568 [SPEAKER_02]: And so if you look at the sort of consensus across all of the different diet tribes, there's a whole bunch of things that seem to be pretty consistent. 29:55.548 --> 29:56.690 [SPEAKER_02]: not too many calories. 29:57.150 --> 29:59.013 [SPEAKER_02]: Drinking your calories is bad for you. 29:59.213 --> 30:00.315 [SPEAKER_02]: Soda is junk food. 30:00.595 --> 30:02.678 [SPEAKER_02]: Legumes, vegetables, fruits, whole grains. 30:02.758 --> 30:04.300 [SPEAKER_02]: Nobody disagrees that those are good. 30:04.660 --> 30:10.548 [SPEAKER_02]: And so think about the things that none of the diet gurus recommend and try to avoid those things. 30:10.849 --> 30:16.797 [SPEAKER_02]: And so when I'm talking about my patients, I really try to focus on the low hanging fruit of their diet improvements. 30:16.777 --> 30:29.790 [SPEAKER_02]: I think that one message is like, it's really easy to confuse yourself and a lot of questions about healthy eating are come from people who know what junk food is and who are trying to find loopholes in that concept. 30:30.310 --> 30:35.318 [SPEAKER_05]: Yeah, this is so hard and I am so glad we're talking about this because I think this is tricky on many friends. 30:35.418 --> 30:38.383 [SPEAKER_05]: The science is hard and on top of that the conversations can be hard. 30:38.883 --> 30:44.051 [SPEAKER_05]: I'm always amazed by the way like what we tell our patients and then like what our patients actually like hold on to. 30:44.112 --> 30:55.930 [SPEAKER_05]: So I'm really curious from like our listeners even like what other approaches do you have in terms of handling these conversations knowing the limits of the research and how hard some of these outcomes can be to really study. 30:56.956 --> 31:02.624 [SPEAKER_01]: Yeah, and this is my personal opinion, but I believe that we as clinicians don't think critically enough about nutrition. 31:02.664 --> 31:06.310 [SPEAKER_01]: So I really hope that we've given you all some food for a thought and a pun intended. 31:06.850 --> 31:15.703 [SPEAKER_01]: And the next time you pick up your morning cup of coffee or when you hear about the latest diet in the news or on social media, we hope that you now have more tools to help you think more critically about your food and diet. 31:16.264 --> 31:17.706 [SPEAKER_02]: And that is a wrap for today. 31:17.766 --> 31:20.871 [SPEAKER_02]: Please feel free to share today's episode with your friends and colleagues. 31:21.307 --> 31:26.314 [SPEAKER_06]: and special thanks to Dr. Walter Willett for kindly dedicating his time and sharing his wisdom with us. 31:26.915 --> 31:31.321 [SPEAKER_05]: Yeah, thank you to our peer years, Dr. Jane Leopold and Dr. Jim and Wong for the accompanying graphic. 31:32.182 --> 31:37.370 [SPEAKER_01]: If you have any feedback or suggestions, please email us at helloacorionpodcast.com. 31:37.390 --> 31:41.155 [SPEAKER_02]: A pin is expressed our own and do not represent affiliated institutions. 31:43.008 --> 31:47.859 [SPEAKER_05]: Ah, I think we've all been able to give this a not asking our patients with their eating or for their drink. 31:47.879 --> 31:48.660 [SPEAKER_05]: Look. 31:48.680 --> 31:48.921 [SPEAKER_05]: Yeah. 31:49.322 --> 31:51.166 [SPEAKER_05]: I think we've all started over. 31:51.386 --> 31:59.143 [SPEAKER_05]: Yeah, I think we've all been... You know, some days I put my hoodie on to like be the focus mode, but it's not helping. 31:59.123 --> 32:00.846 [SPEAKER_01]: It looks like you're about to like start wrapping. 32:03.491 --> 32:04.272 [SPEAKER_05]: I was just a T.I. 32:04.313 --> 32:06.396 [SPEAKER_05]: before it was just a T.I. 32:06.757 --> 32:07.458 [SPEAKER_01]: Yeah, of course. 32:08.821 --> 32:10.304 [SPEAKER_05]: Yeah, channel owner T.I. 32:10.384 --> 32:11.325 [SPEAKER_01]: Yeah, you're an Eminem. 32:12.067 --> 32:13.730 [SPEAKER_05]: Yeah, all right, nails are flying. 32:14.131 --> 32:14.331 [SPEAKER_05]: All right.