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Medscape
5 days ago
- Health
- Medscape
Tying Alcohol to Poor Sleep to Discourage Drinking
This transcript has been edited for clarity. Welcome to Impact Factor , your weekly dose of commentary on a new medical study. I'm Dr F. Perry Wilson from the Yale School of Medicine. You may not have realized it yet, but we are full-on in the era of biofeedback. I remember a few years ago when my smartwatch started reporting on my heart rate variability during sleep. To be honest, I didn't even know what this metric really meant. But I did notice something fairly early on. On nights when I drank alcohol, my heart rate variability went down. Human brains are really good at linking pieces of data like that, and I kept an eye on it, with additional nights of drinking or not drinking and more reports of heart rate variability only strengthening the association. This is not unique to me, of course — multiple studies have demonstrated the link between alcohol and decreased parasympathetic tone, which is the thing that causes the decrease in heart rate variability. But for me, it was the first time I really saw a physiologic consequence of alcohol intake right before my eyes. Sure, everyone has had a hangover, but this phenomenon was there even if I had only had a glass of wine and felt fine waking up. And it had an effect on me. There was something about seeing that number — maybe it's my competitive nature — that made me want to improve it. I guess the behavioral scientists might call this gamification, but whatever you want to call it, the net-net was that I started drinking less. This is the power of biofeedback: You get information about your physiologic state to make the effects of your actions more real. And, with wearable devices now ubiquitous, it seems like the perfect time to test whether anecdotes like mine hold up in the real world. We got a randomized trial to answer that question just last week. I'm thinking about my wearable device this week because of this study, appearing in JAMA Network Open, examining the complex relationship between alcohol use and sleep in a population of 120 young adults aged 18-25. Full disclosure: This was a study out of Yale, but I was not involved in any way. The researchers, led by Lisa Fucito, wanted to test whether biofeedback — in this case, making explicit the link between alcohol intake and sleep quality — could modify alcohol use behavior. Let's digress for a minute to talk about alcohol and sleep. There is something of a two-way street here. In general, alcohol use decreases the quality of sleep; you wake up more, sleep less, and have less restful sleep overall. But bad sleep can also influence alcohol intake. After a poor night's sleep you have less self-control, less discernment — you might make worse decisions — and none of that is conducive to saying 'no thanks I've had enough' when someone is offering you a shot at the local watering hole. To track alcohol intake and sleep quality, the researchers strapped two wearable devices on to each participant. The first was a sleep actigraphy monitor — basically a device that can tell how much you sleep, how deeply, the quality, and so on. The second device was an alcohol monitor. You may have heard of this 'SCRAM' technology that police sometimes use to ensure someone isn't drinking. It samples the alcohol we excrete in our sweat. While every participant wore these devices for 2 weeks, only half of them were given the information the devices provided. The rest were divided into two control groups. One group was given some web-based information about the importance of sleep, and the other group received the same web-based information but were also asked to keep a diary of their drinking behavior and subjective sleep quality. The intervention group is the interesting one here, of course. At the end of week 1 and 2, a trained coach reviewed each participant's data with them. They showed them their blood alcohol content, their sleep data, and crunched this all into clear numbers like the ones you see here. This participant can see that on their non-drinking nights, their sleep quality is better than on their drinking nights. So, with my personal anecdotal data as a guide, this intervention must clearly have led to decreased drinking, right? Well, sort of. But not really. This is the number of drinks per week at each of four time points. Remember, the intervention only lasted for the first 2 weeks. The primary outcome was the number of drinks at week 12. You can see quite clearly an interesting effect; all three groups drank less over time. The intervention with the cool biofeedback, the people who just kept a drinking diary, even the people who got the web-based sleep information program. Everyone. This is actually a classic finding in studies like this known as the Hawthorne effect. It occurs when individuals change their behavior because they are aware they are being studied. You see it in all kinds of behavioral intervention studies. If they know you're watching, people are more likely to wash their hands, leave a tip, hold a door for a stranger. It's powerful. But it's also short lived. When the study is over, people tend to go back to their old behavior. Unfortunately, this makes it tough to assess the intervention itself. Perhaps it really would work in the real world, when big brother isn't watching, but we can't tell in the world of a clinical trial because all the guinea pigs know they are guinea pigs. That said, some of the secondary outcomes were positive. The intervention group had lower rates of sleep impairment and sleep disturbance. That's an odd finding since we know this improvement couldn't have been mediated by less alcohol drinking. Maybe feedback about your sleep quality makes you change other things independent of alcohol? Maybe you're just a bit more mindful about the whole thing? We should also remember that these were all 18 to 25-year-olds. I don't want to sound like an old fogey here, but I will say that I think I was well into my 30s before I took a hard look at some of my less than healthy behaviors and started to make real changes. There are a lot of other pressures on these young adults. Cutting back on drinking may just not be the most important thing to them at this point in their life. So, no, I'm not ready to give up on biofeedback as an agent of behavior change. I still think this area is promising, but we may need to come up with some more clever ways to study it. For now, I'm keeping an eye on my heart rate variability at night; I am a data guy after all. It may not work for everyone, but it works for me, and if it works for you, then that's good enough.
Medscape
14-05-2025
- Health
- Medscape
Yes, You Can Die From a Broken Heart
This transcript has been edited for clarity. Welcome to Impact Factor , your weekly dose of commentary on a new medical study. I'm Dr F. Perry Wilson from the Yale School of Medicine. A patient comes crashing into the emergency room with severe chest pain. The EKG looks like this: As a doctor, if you see this, you're calling the cardiac cath lab. This is an ST-elevation myocardial infarction — the big one — indicative of a blood clot blocking blood flow to a large section of the heart. The sooner you get that blood clot out, the better chance the patient has to survive. So the patient is rushed to the cath lab, and they find… nothing. Clear coronaries. No blood clot. Further questioning reveals that the patient, an older woman, lost her husband recently. This is stress-induced cardiomyopathy, medically known as Takotsubo cardiomyopathy (TC). It's the pathophysiologic manifestation of a broken heart. First described in 1991, Takotsubo syndrome occurs in the setting of deep psychological, emotional, or physical stress. Despite being aware of it for decades, we still don't really understand what the underlying processes are, though they probably have something to do with an excess of catecholamines. But a new study cobbles together data from across the United States to give us new insight into the epidemiology and outcomes of the syndrome. Interestingly, women are much more likely to get a broken heart. But men are more likely to die from it. We got a nice Takotsubo analysis this week, thanks to this article in the Journal of the American Heart Association , from Mohammad Movahed of the University of Arizona and colleagues. They used a database called the National Inpatient Sample. It is what it sounds like: a sample of data from patients hospitalized around the nation. It's a weighted dataset; it doesn't have data from every hospitalization, but individual patients in the dataset can stand in for those who aren't there. This allows you to estimate stuff like the total number of admissions for a certain diagnosis across the whole country. The researchers flagged admissions with a diagnosis code for TC. All told, they identified 39,984 individuals with the syndrome, which scales up to an estimated 199,890 US admissions in total from 2016-2020 — about 40,000 admissions per year in this country. It's not a huge number; there are around 600,000 admissions per year for acute myocardial infarction, but it's not exactly rare. Women were much more likely to have TC; 83% of all the cases were female. You can see here a slight increase in prevalence over time, but nothing dramatic, especially considering that the last year of data would encompass the start of the COVID pandemic. If we break down the incidence by age group, you can see an interesting increase in risk as people got older, with a near doubling of risk after age 45. People have hypothesized that estrogen may play a protective role in this condition, so we might be seeing an increased risk associated with menopause here, but I would have liked to see this stratified by sex to be certain. The authors compare outcomes among those hospitalized with TC to outcomes of hospitalized patients without TC. That feels like an overly broad control group, to be honest, so it isn't surprising that there is, for example, a 12-fold risk for cardiogenic shock compared with the general inpatient population. Individuals admitted to the hospital with other types of heart disease, or a heart attack, would have told us a bit more about the unique risks of TC. Maybe next time. Of course, the worst possible outcome is death, and 6.58% of the patients with TC died during their admission. That's against a background rate of 2.4% of all other patients in the hospital — about a threefold increase in mortality risk. But men with TC were much more likely to die than women, with an 11.2% mortality rate compared with 5.5% among women. This has also been increasing over time. There's no clear explanation for the discrepancy. Men were more likely to develop the condition from physical, as opposed to emotional, stress, and that might change the risk profile. Alternatively, it's possible that this is a 'stubborn man' phenomenon; men might be less likely to go to the hospital when symptoms are mild, so if they do make it to the hospital, they are in worse shape. Take care of yourselves, guys. This paper may have raised more questions than answers, but I appreciate the opportunity to highlight something we often forget — that there is a profound connection between our minds, our emotions, and our bodies, and that connection is not purely subjective. Takotsubo cardiomyopathy is a potentially fatal disease, with all the risks of a major heart attack and without a convenient treatment like cardiac catheterization. And though I hope most of us never experience the levels of stress — emotional or otherwise — that would precipitate this disease, the very existence of a syndrome like this shows us that stress can be toxic. None of us can live stress-free lives, of course, and I'm not sure what the dose-response effect is, but in the end, perhaps knowing that how we feel affects how we feel can help us better manage how we feel.
