A few months ago, because of this blog, I got a free heart scan from HeartScan in Walnut Creek. It’s a multi-level X-ray of your heart and is scored to indicate your heart disease risk. In spite of the fermented food I’ve been eating recently, and the flaxseed oil I’ve been drinking for about two years, my score was right in the middle. What’s impressive about these scans is three-fold:
1. The derived scores are strongly correlated with risk of heart disease death. This isn’t surprising because they are actually looking at your circulatory system. Here is an example of the predictive power. About 1000 subjects were followed for about four years. About 40 of them had something go seriously wrong with their circulatory systems (e.g., heart attack):
The mean coronary artery calcium score was 764 ± 935 [mean ± standard deviation] among subjects with events as compared with 135 ± 432 among those without events (p < 0.0001). [Minimum score is 0.]
The standard deviations are more than the means because the distribution is very asymmetric. (Like most researchers, they should have transformed their data.)
2. You can improve the score. Via lifestyle changes.
3. The scans provided by HeartScan are low enough in radiation that they can be repeated every year, which is crucial if you want to measure improvement. In contrast, a higher-tech type of scan (64 slice) is so high in radiation that it can’t be safely repeated. The higher-tech type of scan, offered by other heart-scan centers, is more profitable for the manufacturer of the equipment (General Electric), which may be why it has become increasingly common.
Heart scans, like the sort of self-experimentation I’ve done, is a way to wrest control of your health away from the medical establishment. No matter what your doctor says, no matter what anyone says, you can do whatever you want to try to improve your score. And if what you do works, it works; if it doesn’t work, it doesn’t work — regardless of what anyone says. My self-experimentation started with something similar to a heart scan: I counted the number of pimples I had. The lowest possible tech, sure, but when I did that, and varied the prescribed medicine, I could actually see what worked and what didn’t.
they should have transformed their data
Huh? This paper of yours isn’t open access? So you really think that it is worth $ 31.50 (of which you receive zilch))? I am going to revise the credibility of this blog…
JLD, I’ve changed the link. Try again.
My coronary calcium score was zero. I’m not sure what exactly that means.
peter, what is your diet and lifestyle history? Sound like you are doing some things right…
and seth, how have your blood lipids been over the years if you don’t mind the question?
David, my HDL is low. The other stuff is okay.
thnx
Because of the way it’s calculated (look up the Agatston Scoring method) CAC has a big spike of values at exactly zero – maybe 50% of the population. Transform away, but you’re not going to get symmetry (and, for many statistical purposes, you don’t need it)
The scoring method certainly could be improved (and has been, by some statisticians) but Agatston remains the default. Moreover, there’s reason to think that different biology may dictate people have some vs zero CAC, and lots vs not much.
So what if you don’t get symmetry — you’ll get closer to symmetry. You’ll improve the situation.
Improve what, exactly? If you mean improving predictive ability in standard regression models, nothing says that the predictor has to be symmetric, or that prediction will be better/worse if you transform the predictor to be symmetric.