Taking the interest in understanding another's position and where they are coming from is key to having a productive conversation / debate.
But what if someone is persistently misrepresenting your position - even if unintentional?
2/ Of course, the most obvious example of this with clear malice is the Straw Man fallacy (which I won't go into here).
Yet what about where someone restates your position in a way that's not too far off, save some critical flaws that you assume are a simple misunderstanding?
3/ What happens next reveals the problem.
You find you're spending a lot of time attempting to clarify your position in a good faith effort to correct the misunderstanding -- but it isn't working. The other party either isn't getting your original point with repeated attempts...
4/ ... Or it's possible they don't want to.
Regardless, if you're one to (1) start with the assumption each party is acting in good faith and (2) are used to clarifying your position anyway, you're very susceptible to getting caught in this loop. I know I have been...
5/ But there is a simple solution.
... Call out the recasting of your position or statements for exactly that. They may genuinely feel they are summarizing or restating what you're saying in a fair manner - but that's irrelevant to the problem (and you have to recognize this)
6/ So moving forward, I'm going to link this thread when I find I'm that loop.
I'll ask the one I'm chatting with to stick with arguing what I stated as it was stated -- and that I can't spend time constantly correcting their version of it (even if well intentioned).
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After trying (and failing) to get conventional researchers interested, I started the Citizen Science Foundation (@realCSF) – a 501(c)(3) Public Research Charity.
💰We crowdfunded a study budget for #LMHR and near-#LMHR individuals with this triad. It took a lot of work, but the community stepped up to make this happen.
📝 We recruited 100 participants who traveled to Lundquist Institute to undergo a high-resolution heart scan called a CT angiogram (#CTA).
A year later (visit 2), they returned for a second #CTA, allowing Lundquist to compare the scans and track plaque progression.
When Lundquist shared the aggregate data of the first set of scans after they were completed, I was excited, but we needed more data to make comparisons.
3/ 🤼#MiHeart Match Analysis
-- Semi-Quantitative --
Component #1:
🔬The semi-quantitative match with Miami Heart showed nearly identical plaque levels with our Keto-CTA cohort
---
Following the initial baseline scans, Lundquist was then able to conduct a matched analysis with participants from another study, known as Miami Heart (#MiHeart). Eighty of our participants were matched with individuals from this other study based on age, sex, ethnicity, and shared low CVD risk factors.
They were compared with a semi-quantitative analysis. Semi-quantitative readings involve a cardiologist visually evaluating and scoring plaque buildup at key locations in the coronary arteries.
So what were the results?
In short, our participants, with an average LDL cholesterol of 272 mg/dL over 4.7 years, showed no statistically significant difference in plaque levels compared to the Miami Heart cohort (average LDL cholesterol: 123 mg/dL).
🧵 My thoughts on the Baseline Piece of the Puzzle
-- That everyone keeps missing... 1/10
A week ago today the longitudinal paper for our KETO-CTA study dropped (jacc.org/doi/10.1016/j.…) and there's been a lot of positive feedback, but also critiques worth discussing. I'd like to zero in on the topic of NCPV and PAV change.
First and foremost, I’m looking to be respectful of lead author Dr. Adrian Soto-Mota (@AdrianSotoMota) and Principal Investigator Dr. Matthew Budoff (@BudoffMd) regarding the complexity and relevance the heterogeneity of the cohort with regard to our findings. The coming paper expanding on this for both classification and clinical use is already under submission for review.
However, waiting for the publication of the new paper seems very untenable given how long these things take and interest in discussing the overall change in NCPV and PAV for the KETO-CTA study.
This can be challenging on my end as I want to represent this study effectively. And that’s difficult right now when I not as versed to delve deeper into both the heterogeneity relevance statistics like Dr. Soto-Mota or the issues with looking to changes in NCPV or PAV at low baseline levels like Dr. Budoff.
However, here’s what I can speak to…
I can speak to my own personal challenges in looking to the change of NCPV and PAV overall and why this hasn’t made sense to me. Not from a standpoint of discouragement, such as — this makes the study look bad. No, I mean it actually doesn’t fit any model I’m aware of save present plaque being predictive of future plaque change.
Let me unpack what I’m talking about…
Our baseline scans from the study showed this was a low risk population. Again, if looking at this from a population level.
But then, we were able to do a match analysis with Miami Heart. Matching up age, sex, ethnicity and risk factors quite tightly, but with our cohort having an average LDL-C of 272 mg/dL, and the matched Miami Heart cohort having average LDL-C of 123 mg/dL. And what did we find? They were nearly identical. In fact, for the semi-quantitative data ours was trending slightly better. jacc.org/doi/10.1016/j.…
2/10 - Moreover, while unpublished, I was cleared to present a preliminary quantitative match analysis with Miami Heart last year at a conference. These would make use of Cleerly scan data for both our cohort and Miami Heart. So it had both overall plaque volume and non calcified plaque volume (NCPV).
3/10 - But even better, there was a subgroup analysis that excluded those taking cholesterol lowering medication on Miami Heart to match again with ours...
First, let me say that data on this has been a bit limited. But *IF* we do ultimately confirm there are more ApoB-48 (B48) than ApoB-100 (B100) in ASCVD plaque, it would be a very big deal.
Let's unpack...
2/ First, thanks to @TuckerGoodrich for pinging me on these pubs and pressing the discussion.
But also credit to @CaloriesProper on tweeting this a couple years ago (I missed it then)
To understand why this would be so important if true, some review...
3/ B48 and B100s are the major proteins on chylomicrons (CMs) and VLDLs, respectively.
CMs mostly carry lipids from the small intestine to the bloodstream (lipids consumed), VLDL mostly carry lipids from storage; predominantly from adipose stores.
#Me: Why would triglyceride rich LDL particles be more atherogenic than triglyceride poor LDL particles?
#ChatGPT: Triglyceride-rich LDL (low-density lipoprotein) particles are more atherogenic (i.e., more likely to contribute to the… twitter.com/i/web/status/1…
2/
#Me: Couldn’t it also be possible that triglyceride rich LDL are ultimately the result of metabolic dysfunction and that better explains its association with atherosclerosis?
#Me: Is it possible that almost the entire amount of atherogenesis associated with high triglyceride rich LDL is due to dysfunctional lipid metabolism and the diseases that result in these profiles rather than the LDL particles themselves?
1/🧵 I'm definitely a fan of both @DominicDAgosti2 and @DrRagnar (obviously), so I was excited to see them chatting about #lipids, #LMHRs, and Dom's consideration of increasing carbs to lower his #ApoB
3/ When chatting with Dom in SD last year for dinner, he mentioned focusing less on maintaining such a sizable muscle mass as he typically does, and I predicted he'd likely see his LDL/ApoB as considerably higher with this change if still #keto. This podcast appears to confirm...