They’re showing their hand here.
When people who are actually competent in statistics, like mathematicians such as Taleb, look at this kind of data, and see strong causal claims being made from weak or contradictory evidence, they recognize the problem immediately.
Some in medicine have a fundamental misunderstanding of how we actually practice.
We don’t make decisions off a single variable like LDL in isolation.
We have plenty of examples of patients with LDL <70 who still develop plaque because of other, more predictive factors. And others with LDL well above 100 who never develop meaningful disease.
Even in long-term prospective data, some of the longest-living populations often have LDL levels above 100. That alone should tell you isolated LDL is not a strong standalone predictor.
But we don’t have to rely on observational data.
We have decades of predictive modeling showing, over and over again, that isolated LDL has weak predictive accuracy on its own. In some cases, adding it to a well-performing model barely improves discrimination.
We also have CAC and CCTA data showing that when imaging is clean, the short- to intermediate-term risk is low, regardless of LDL.
That’s the point.
We use models to estimate who is more likely to have an event and who is more likely to benefit from treatment.
This is not new. This is the foundation of modern medicine.
Stroke, cardiology, internal medicine. This is where CHADS-VASc, HAS-BLED, ABCD2, ICH score all come from.
We use these every day. Not perfectly. Not all with perfect external validation. But with enough consistency to guide real decisions.
Same concept here.
LDL is one input. Not the model.
If you reduce everything to LDL alone, you’re not practicing medicine the way it’s actually done.
You’re reducing a complex, probabilistic system to a single variable and calling it science.
Tom Dayspring is a fraud & statin shill: he advocates statins for people w/0 calcium score"just in case", equivalent to giving someone lung radiation therapy, although cancer free, "just in case" because his sister in law smokes.
A lot of stat mistakes/base rate fallacies.
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