This is a cool new study from UCSD research group. 11–19% mARD is interesting, although not quite accurate enough to displace CGMs (the FDA-cleared ones have ~8% mARD).
But the sweat angle is could add signal alongside other techniques like Raman or MIR spectroscopy, and maybe a combination of these and an ML system would be accurate enough to use in practice.
Definitely agreed. I'm rooting for Apple, Samsung, Oura, etc to finally crack this problem and some of the techniques in the article (MIR, Raman spectroscopy, wearable foundation models) seem like they're leading in the right direction.
Unfortunately this particular intervention wasn't successful (not much difference between treatment and control groups). But conceivably, afib triggers is something that varies from person to person and perhaps a future design would tease this out.
This is the first oral PCSK9 inhibitor; it cuts LDL cholesterol (or ApoB) levels by 50-60%. It uses a different mechanism than a statin so you can layer them to get an 80% or so reduction overall.
It also reduces Lp(a), the strongest hereditary risk factor for heart disease, by 28%.
Previous PCSK9 inhibitors like Repatha were injectables (similar to GLP-1s). Only about 1% of people eligible for injectable PCSK9 inhibitors use them, so having a convenient daily pill is a potentially huge win for prevention.
The speed of the pressure wave is one signal that correlates with blood pressure. It's a bit like a string being pulled taut -- waves travel faster with higher pressure. The shape of the wave also gives clues. For example, the rise time of the wave tells you something about the resistance encountered, which is a function of blood pressure.
Rather than hand-engineering these features, most modern systems are built on a wearable foundation model that's been trained reconstruct the signal (similar to how an LLM is trained to predict the next word). Those foundation models are picking up on these signals and likely others.
You're right that calibration with a cuff is required of all systems currently on the market.
The Signal Ring folks' claim they can do a blood pressure number without calibration, which is quite novel and seems to be their "secret sauce". They did run a clinical study as well, so presumably more details will come out whenever that's published.
Likely uses pulse transit time and the shape of the pulse wave to infer changes in blood pressure. I wrote a bit about how this works (in the context of Apple Watch's hypertension notifications) here: https://www.empirical.health/blog/apple-watch-blood-pressure...
To be eligible, you need either a BMI of >=35, or a BMI of >=27 and a set of specific health conditions (uncontrolled hypertension, chronic kidney disease, pre-diabetes, etc). You also can't be qualified for GLP-1s under Medicare's previous Part D coverage.
In practice these criteria are narrower than they look. Of the 13 million Medicare beneficiaries with overweight or obesity, about 4 million actually qualify, because most are excluded for already having a diagnosis, like type 2 diabetes or sleep apnea, that covers a GLP-1 another way.
Right now lots of good health companies hiring, including my own (Empirical). https://www.workatastartup.com/ lets you filter YC companies to see health startups, by stage and location (or remote).
IMO, there's an interesting opportunity for AI to make healthcare deflationary.
For example, Medicare is launching a new program in July that pays a fixed rate for achieving defined outcomes, like lowering blood pressure or cholesterol. Medicare's explicit goal here is to create incentives to automate the repetitive parts of care delivery with software. (Much of preventive cardiology is surprisingly algorithmic and guideline-driven, so this is more plausible than it seems.)
This reverses the incentives of the current system, where CPT codes incentivize doing more "stuff" (but not necesarily delivering the most effective care efficiently).
If you're a software engineer who cares about health, and have been sitting on the sidelines till now, I think the next few years are a really interesting time to make a contribution.
It's pretty well-established science now that vitamin D is a hormone, not a true vitamin. Vitamin D binds a nuclear receptor that regulates roughly 1,000 to 2,000 genes (5-10% of the human genome).
The "Vitamin D" moniker has just stuck around since it was named in 1922.
That trial used a dynamically-adjusted dosage of a vitamin D3 supplement, where dosing was set as to keep blood levels within a target range of 40–80 ng/mL. IMO part of the reason this trial is showing better results than the previous clinical trials of vitamin D supplementation quoted in the above article is that vitamin D has bad effects if too low and too high. Adjusting the dose dynamically to achieve an optimal range gets you the benefits without some of the negative effects.
Biggest changes in the new guidelines from the American Heart Association / American College of Cardiology:
- Universal Lp(a) testing recommended for everyone - Lp(a) is the strongest hereditary risk factor for heart disease.
- Risk Equations switched to PREVENT, which predicts both 10-year and 30-year risk.
- Treatment is now recommended for younger adults, based on these 30-year risk scores.
- CAC scans recommended in more cases (for intermediate risk).
- Specific LDL targets are back, after being removed in the 2013 guideline
The actual guidelines are long and make 52 distinct recommendations, but these are the ones that jumped out as the biggest new changes.
(OP) The science behind eggs being healthy, or at least not harmful for heart health, has been pretty settled for decades.
Unfortunately, official medical guidelines take a while to catch up. It's only in 2026 that the American Heart Association put out updated dietary guidance which makes it official that most people shouldn't limit dietary cholesterol. Fiber and saturated fat are more important drivers of blood cholesterol, which is still recommended as a major risk factor (alongside blood pressure, inflammation, HbA1c, and so on).
The post also tries to explain why there was a limitation on eggs and cholesterol in the first place, starting from the 1968 guidelines.
Co-Founder at Empirical Health (https://empirical.health). Don't die of heart disease.
Before: Co-Founder @ Cardiogram (ML for heart health)
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