Category Archives: sleep

Eight Lifestyle Changes All Patients Should Make To Reduce The Recurrence Of Atrial Fibrillation

Previously, the skeptical cardiologist answered the question “Why Did I Go Into Atrial fibrillation?

An equally important question is “how can I reduce the chances that I have more spells of atrial fibrillation (AF)?”

I spend a fair amount of time discussing with my AF patients what lifestyle changes they can make in this regard. I’ve discovered, however, that many AF patients I am seeing for a second opinion seem unaware of the changes they can make to minimize AF recurrence.

Herein I give you the eight most important changes you can make to minimize both the onset and the recurrence of AF.

  1. Eliminate or substantially reduce alcohol.
  2. Lose weight if you are obese.
  3. Stop smoking. Stopping is associated with a 36% lower risk of AF.
  4. Get your blood pressure under good control.
  5. Get regular aerobic exercise. At least 150 minutes of moderate cardio exercise weekly.
  6. Eat A Healthy Diet. Don’t Eat Crap (as Younger Next Year says). In general, because obesity is such a big factor  in AF, I am fine with whatever diet plan has you at a BMI <28. Healthy diets controlling weight avoid ultra-processed foods, sugar-sweetened beverages, and minimize white rice, pasta, pastries, and potatoes. These diets include lots of fresh vegetables, nuts, olive oil, and fish. Full fat yogurt and cheese are fine in moderation. Eat real food, mostly plants, not too much as Michael Pollan has famously said.
  7. Get high-quality sleep. This means treating any sleep apnea properly in addition to standard advice for getting a good night’s sleep. The risk of AF is four times higher in patients with obstructive sleep apnea (OSA) independent of other confounding variables
  8. Reduce stress. Easier said than done I know. Everything from meditation to Yoga to retiring or cutting back at work to psychotherapy can be tried in this category. Go with whatever works for you. Knowing when you are in or out of AF by utilizing personal ECG monitoring devices may help reduce stress, especially if used under physician supervision.

Let’s dig a little deeper into some specific recent evidence on three which have a huge impact: alcohol, exercise, and obesity.

Alcohol and Atrial Fibrillation

In March, I wrote about the alcohol AF trial recently published in NEJM:

The Alcohol-AF Trial. Binge alcohol consumption (holiday heart) can trigger atrial fibrillation (AF) and observational studies show a higher incidence of AF with higher amounts of alcohol consumption.

This trial was the first-ever randomized controlled trial of alcohol abstinence in moderate drinkers with paroxysmal AF (minimum 2 episodes in the last 6 months) or persistent AF requiring cardioversion.

Participants consumed >/= 10 standard drinks per week and were randomized to abstinence or usual consumption.

Participants underwent comprehensive rhythm monitoring with implantable loop recorders or existing pacemakers and twice-daily AliveCor monitoring for 6 months.

Abstinence prolonged AF-free survival by 37% (118 vs 86 days) and lowered the AF burden from 8.2% to 5.6%

AF related hospitalizations occurred in 9% of abstinence patients versus 20% of controls

Participants in the abstinence arm also experienced improved symptom severity, weight loss and BP control.

This trial gives me precise numbers to present to my AF patients to show them how important eliminating alcohol consumption is if they want to have fewer AF episodes. The study further emphasizes lifestyle changes (including weight loss, exercise, and stress-reduction) can dramatically reduce the incidence of atrial fibrillation.

Obesity and Atrial Fibrillation

We have known for some time of a strong association between obesity and atrial fibrillation. We also know we can make sheep go into atrial fibrillation by making them obese and creating a diseased, fat-infiltrated left atrium.

More recently we have solid evidence that sustained weight reduction can significantly reduce the recurrence of AF.

The Australian LEGACY study took 355 AF AF patients with BMI>27 and offered them a weight management program:

Weight loss was categorized as group 1 (≥ 10%), group 2 (3% to 9%), and group 3 (<3%). Weight trend and/or fluctuation was determined by yearly follow-up. Endpoints included impact on the AF severity scale and 7-day ambulatory monitoring.

Weight loss ≥ 10% resulted in a 6-fold  greater probability of no AF recurrences compared with the other 2 groups. High weight fluctuation doubled the risk of AF recurrence.

Of course, all these factors are interrelated. Exercise, diet, stress, alcohol consumption, and sleep quality all impact weight control and obesity. Patients with AF should be working on all 8 levers for optimal benefit.

Given the LEGACY study findings, if you have AF and are obese, you should be using all lifestyle factors at your disposal to get your body weight down >10%. Do this in a slow and steady fashion with lifestyle changes that are sustainable for the rest of your life. You want to lose that weight and keep it off.

Exercise And AF

The most compelling evidence for the independent role of exercise in reducing AF comes from a Norwegian study of 51 patients with AF who were randomized either to aerobic interval training (AIT) or to their regular exercise habits. The patients randomized to AIT engaged in four 4-minute bouts of high-intensity (85 to 95% peak heart rate) aerobic exercise interspersed with 3 minutes of recovery.

There was a significant reduction in AF burden (measured by implanted loop recorders) in the exercise group, with the mean time in AF dropping from 8.1% to 4.8%, with no significant change in the control group. Patients in the exercise group experienced fewer and less severe symptoms whereas the non-exercising, control group had no change. In comparison with controls, patients randomly assigned to exercise also increased their peak oxygen consumption (Vo2peak), cardiac function, and quality of life, while improving body mass index and blood lipids

Screen Shot 2020-02-02 at 12.19.44 PM
Atrial fibrillation (AF) burden in patients with AF during the study. Mean time in AF was measured by an implanted loop recorder (n=36) before, during, and after 12 weeks of aerobic interval training (exercise) or usual care (control). Patients without AF during the study period are excluded. Mean changes from baseline to follow up were −6.2±8.9 percentage points (pp), P=0.02 for exercise; 4.8±12.5 pp, P=0.09 for control; and 11.0±3.9 pp, P=0.007 between groups. Error bars show the 95% confidence interval.

An accompanying editorial provides this graphic on the benefits of exercise training in AF


For all you readers without AF you can minimize your chances of developing AF by following these lifestyle recommendations.

Afibrillatorily Yours,


N.B. A PDF summary of the 8 factors is available here (Lifestyle changes Afib)

N.B.2 For those wishing to mimic the Norwegian AIT protocol here is the complete description:

Endurance training was performed as walking or running on a treadmill 3 times a week for 12 weeks. Each session started with a 10-minute warmup at 60% to 70% of maximal heart rate obtained at exercise testing (HRpeak), followed by four 4-minute intervals at 85% to 95% of HRpeak with 3 minutes of active recovery at 60% to 70% of HRpeakbetween intervals, ending with a 5-minute cooldown period. During AF, patients exercised at the same treadmill speed and inclination as in the previous sessions in sinus rhythm, with the Borg scale of 6 to 20 as an aid to control intensity. When familiar with the training regimen, patients were allowed to perform 1 exercise per week at home, where exercise intensity was documented with a heart rate monitor (RS300X, Polar Electro, Kempele, Finland).





The Oura Ring For Personal Sleep Analysis: Lots of Hype and Data, Little Science, Utility or Accuracy

The Oura ring is a novel, multisensory device that claims to be able to distinguish sleep stages, including REM sleep,. I purchased one recently and after several months of evaluation and an extensive look at the data supporting it I have to say I am much more impressed with OURA’s  hype, marketing and style than any useful or actionable information about sleep that comes from it.

The Oura website is full of pictures of cool people doing cool things wearing their Oura rings-like this guy

It’s also chock full of marketing blather which implies that somehow the ring will dramatically improve your sleep and your waking life.

We see every individual as unique: your state of health and wellness today, tomorrow, and days to follow. Getting enough restorative sleep has a profound impact on mental and physical health and performance. Your daily choices and rhythms define how well you sleep. With Oura, you learn your optimal times to move, eat and take a break to get that restorative sleep.
Giving you actionable steps to improve your life opens a totally new universe of possibilities – be it for mental, cognitive or physical performance, or for beauty, health, and longevity.

A quick look at the OURA web site certainly conveys the sense that this is the slickest, most cutting edge personal wearable sleep and activity tracker one could purchase.

However, despite Oura’s tantalizing claims there is only one legitimate scientific comparison of the ring to the gold-standard of sleep evaluation, polysmnography (PSG). This was published in 2017 in Behavior Sleep Medicine and its full contents can be read here.

In addition, there is no published evidence whatsoever that changing one’s behaviour based on the various parameters that the ring produces will have any favorable effect on your sleep quality or health in general.

I’ll be quoting from that 2017 published paper which I think is a good, unbiased analysis and I’ll throw in some of my own observations throughout this piece.

How The Ring Works And What It Claims To Do

A good night’s sleep, everyone should know by now is incredibly important to optimal performance the next day. In addition poor sleep quality is linked to a whole host of pathologies (with causality yet to be proven for most.) Thus, I quickly purchased an OURAring after hearing Peter Attia rave about his ring.

OURA likes to promote the idea that it has some sort of special way of measuring sleep based on a combination of sensors.

The Oura ring and its proprietary algorithms are a combination of extensive scientific understanding, years of careful research and development work, and top-notch engineering. All insights and guidance you get are based on proven algorithms and verified knowledge. For example, Oura’s sleep staging algorithms were the first in the market that have been independently validated. The validation study was made by SRI International.

The OURA website notes that the ring is fitted with the following sensors to collect physiologic signals from your body.

The Oura ring registers your body temperature reading every minute while you sleep. By comparing that value to values from earlier nights, it indicates your body temperature baseline and any variations from it.

Measuring blood volume pulse directly from the palmar arteries of the finger.

Detects the amplitude and intensity of your body movement, automatically recognizes that you’re active and tracks the time you were inactive during the day.

Ōuraring (Oulu, Finland) claims to use these physiological signals (a combination of motion, heart rate, heart rate variability, and pulse wave variability amplitude) in combination with sophisticated machine learning based methods to calculate deep (PSG N3), light (PSG N1+N2) and rapid-eye-movement (REM) sleep in addition to sleep/wake states.

After obtaining a sizing kit from OURA I selected my ring and within a few weeks it was delivered. I downloaded the free OURA iPhone app, charged the ring with the supplied USB charger, slipped it on my left ring finger and eagerly awaited my first night’s analysis.

Upon arising in the morning I opened the OURA app and visualized an entrancing display like the one below.

It’s a nice graphic summary of the night’s sleep with my minutes of REM, light, and deep sleep nicely quantified.

More graphs and more data are available by connecting to Oura’s online application which automatically syncs to your smartphone app.

Unfortunately, the app was telling me that I was awake for 109 minutes of the time I was in bed. Which was not correct. I was truly awake only for 10 minutes around 130 AM. This overestimation of my awake time has been a consistent error of the ring for my recordings. If the app can’t accurately track awake time all of its metrics are going to be inaccurate.

In fact, over several months of using the ring/app I have found little relationship between how I feel after sleeping versus how Oura has rated my sleep. There is even less correlation between the “readiness” score that Oura produces and how I feel during the day. Overall, I have found absolutely no actionable information from my months of using the ring.

One morning Oura gave me a “readiness” score of 68 and told me:

“Don’t push it. Your resting heart rate was above average, so you might not be fully recovered”

I felt great throughout the day. These recommendations in my experience are almost unversally inaccurate and useless.

Oura also makes recommendations on when it thinks you should go to bed. One time it told me I should go to bed at 7 PM. I have been ignoring its advice in this area.

Now I am just one individual and it is entirely possible there is something unique about my sleep that invalidates the ring’s accuracy. The ex-eternal fiancee’ tells me I’m a restless sleeper.

In fact, devices that rely on actigraphy tend to be fairly accurate at identifying when you are sleeping but not when you are awake which is the opposite of what OURA is doing in my case.

The SRI paper puts it this way

 Compared to PSG, actigraphy has high sensitivity (ability to detect sleep) although specificity (ability to detect wakefulness) is lower(Marino et al., 2013Sadeh, 2011), with a wide range of accuracy,depending on the amount of night-time wakefulness(Paquet, Kawinska, & Carrier, 2007),the algorithms used and the particular population studied(Van de Water, Holmes, & Hurley, 2011). Most importantly, actigraphy relies on a single sensor, an accelerometer, and thus it provides a measure of motion from which it predicts sleep and wake states. However, information about sleep stage composition, fundamental in studying sleep and sleep disorders,is not provided.

The Science Behind Oura’s Sleep Analytics: Detecting Sleep Stages

So what does the SRI paper OURA likes to quote as proving its accuracy say.

The paper is entitled “The Sleep of the Ring: Comparison of the ŌURASleep TrackerAgainst Polysomnography” and it was written by researchers at SRI international, a research consortium in Menlo Park, California with no ties to OURA.

Another paper which used to be touted on the Oura Ring website (but is no longer referenced on the site) utilized home PSG recordings and was done by an in-house OURA employee.

The SRI researchers studied 41 healthy adolescents and young adults with an average of 17 years and sleep data were recorded using the ŌURA ring and standard PSG on a single laboratory overnight. Metrics were compared using Bland-Altman plots and epoch-by-epoch (EBE) analysis.

EBE analysis showed that ŌURA accurately detected “light” and “deep” sleep in 65% and 51% of the epochs, respectively. It also accurately detected REM sleep epochs 61% of the time, with an overall overestimationof PSG REM sleep (by about 17 min). When the ŌURA ring misclassified PSG REM sleep, the algorithm classified the epoch as “light sleep” (76%) for the majority of the time.

These data suggest that the Oura Ring is virtually useless in telling you if you are in REM sleep versus deep or light sleep.

As the authors noted

Distinguishing sleep stages such as REM and N3 with non-EEG based systems has been challenging and is a goal of several commercial sleep-trackers, with mixed success. 

Clearly, further work is needed to determine what combination of sensors might be used to optimally develop an algorithm that differentiates sleep stages sufficiently well to detect real differences or changes in healthy and clinical populations.

A look at the Bland-Altman plots really tells you how much variation there was in the PSG estimates of various parameters versus the OURA

The Bland-Altman plots show us how much the PSG time in REM differed from the Oura REM time for each individual subject. You can see that some individuals had considerable over-estimation of REM time whereas other had considerable overestimation of REM time.

Although OURA REM time was on average only 17 minutes higher than the PSG REM time this was because the marked overestimation of REM time in some (7 subjects over 30 minutes) was balanced by marked underestimation in others (9 subjects with over 40 minutes and one with 160 minutes).

Given that the average REM time was 92 minutes for most subjects there was a significant discrepancy between PSG. and OURA assessments.

OURA: Coin Flip For Detecting Awake

Oura ring was also pretty useless at identifying when you are awake

Overall, ŌURA had 96% sensitivity (ability to detect sleep), 48% specificity (ability to detect wake), 65% agreementin detecting “light sleep”, 51% agreementin detecting “deep sleep”, and 61% agreementin detecting REM sleep, relative to PSG

Like other sleep sensors utilizing actigraphy, Oura in most individuals can’t accurately differentiate between times when you are lying still but awake and when you are lying still and asleep.

The limitations of wrist actigraphy (see here) for differentiating sleep from wake are worse in those with insomnia:

With actigraphy, because sleep is inferred from lack of movement, subjects who are awake but lie motionless can be classified incorrectly as being asleep, and thus the technique is biased toward overestimating time to sleep, which may lead to incorrectly minimizing the severity of sleep disturbances. This may present a specific challenge for patients with insomnia, and may partially explain the limited validity of wrist actigraphy for estimating sleep onset latency.. 

There are multiple other issues and questions with the usefulness of the data that Oura provides that need clarifying before the ring can be considered useful.

For example the SRI paper found significant differences in results depending on which finger the ring was placed on.

Interestingly, we found that PSG-ŌURA discrepancies for “light sleep” and REM were greater on the ring finger compared to the other fingers, a result that was independent from the amount of PSG sleep fragmentation.Assuming that the main parameters that ŌURA uses to determine sleep stages are motion and optical sensor outputs, it is possible that the different blood supply among fingers maypartially explain these results. For example, it has been shown that SpO2 values differ between fingers as well as hands suggesting a finger-dependent difference in accuracy of the pulse oximetry signal (Basaranoglu et al., 2015).Further studies should confirm and better characterize the dependency of the PSG-ŌURA discrepancies on the ring position by having the same participants simultaneously wear different rings on different fingers.

The in-house Oura study also noted that results were more accurate on the non-dominant hand finger compared to the dominant hand but the Oura website makes no recommendation on which finger to use.

The other data that Oura compiles (heart rate, heart rate variability, temperature change, respirations) are clearly related to sleep cycles but Oura provides no evidence that these data or their proprietary algorithms to give you “readiness” or sleep quality scores are accurate or of any value.

Shold You Buy An Oura Ring?

If you are hoping to get improved analysis of your sleep quality I don’t think Oura adds anything to what is elsewhere available using cheaper wrist actigraphy devices.

The ring is expensive at 299$ and cannot accurately detect sleep stages.

Although most reviews you will encounter on the internet are wildly enthusiastic about Oura, they are likely biased and they provide no evidence that the unique aspects of the ring sensors provide useful information.

Would I buy it again?

I’ve misplaced my ring several times and I have to say that this distressed me immensely. Given that I think the sleep analysis is worthless this is hard to explain.

I think my attachment to the ring is due to a number of factors

  1. It’s stylish and it mimics a wedding ring (which I otherwise would not have.)
  2. I’m intrigued by some of the cardiovascular data it produces (night time heart rate and heart rate variability). Although currently I don’t think the data can guide me to healthier behavior, it’s possible that there is useful information in there somewhere. I hope to write a post on heart rate variability down the line. I’ve done research in this area and have some strong opinions on its value.
  3. I’m curious to see if the respiratory rate data and the temperature data is of any value whatsoever.

So, the ring is best I would say for well-heeled,, self-hacking and self-experimenting techno geeks.

Auroraborously Yours,