Does having high LDL-cholesterol increase your risk of having a heart attack? If you are worried about having high LDL-C due to eating a Keto or Carnivore diet then this video will help you. Research continues to come out showing that high LDL-C is not the danger it was once believed to be, and that there is No association between high LDL-C and the progression of plaque in the heart arteries…
Dave Feldman is a senior software engineer and entrepreneur who became obsessed with understanding Lipidology after seeing his cholesterol climb substantially on a low carb diet. He has since performed a series of experiments around this phenomenon, published several papers on its mechanisms and phenotype, and is currently conducting a clinical study out of UCLA through his newly formed public charity, the Citizen Science Foundation.
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KETO-CTA Study — Findings Presented by Dave Feldman (Interview with Dr. Ken Berry)
Core Questions Raised
- Does high LDL cholesterol or high ApoB, especially on ketogenic/carnivore diets, accelerate coronary plaque formation?
- What happens to plaque burden when people maintain very high LDL for years on low-carb diets?
Study Overview (as described)
- Design: Coronary CT angiography (CCTA) scans analyzed for plaque burden; scans compared across time.
- Cohort size: ~100 participants discussed.
- Diet: Low-carb / ketogenic (includes lean-mass hyper-responders).
- Exposure duration mentioned: Multi-year follow-up; “nearly half a decade” (~4.5 years) cited in discussion for average exposure at very high LDL levels.
- Baseline CAC: Majority reported as CAC=0 at baseline.
- Age: Average age stated as ~55 years.
LDL/ApoB & Who Elevates Most on Keto
- LDL/ApoB rises are most prominent in leaner individuals; a “1–5%” subgroup can see marked increases (lean-mass hyper-responders).
- Overweight individuals starting keto more often see LDL fall or change minimally as metabolic health improves.
Imaging & Analysis Pipelines Used
- Multiple, independent quantification routes were used on the same CCTA datasets:
- Cleerly (AI plaque quantification).
- HeartFlow.
- QAngio.
- A semi-quantitative visual method.
- Quality control / usability rates differed by tool on identical scans:
- Example figures mentioned: HeartFlow ~6.3%, QAngio ~39.8% (context: differing pass/fail or exclusion proportions across analyses).
- Key metric emphasized: Percent Atheroma Volume (PAV); also total plaque volume and non-calcified vs calcified plaque were discussed.
- A specific change example cited: Cleerly ~+23.3 mm³ (small absolute change) in a reported plaque volume metric.
Main Findings Reported
- Progression signals were low overall across the cohort despite very high LDL/ApoB levels on long-term low-carb/keto.
- Some participants showed regression (less plaque at follow-up than baseline).
- Results were directionally consistent across analysis methods, despite different exclusion/quality rates.
- Emphasis that non-calcified plaque (considered more concerning) did not show worrisome acceleration cohort-wide.
Clinical Events Mentioned
- Among ~100 people followed/discussed, no heart attacks were reported within the study’s observation window.
Radiation & Practical Notes on CCTA
- Modern CCTA was described as low-dose radiation, with a figure around ~0.6 mSv mentioned.
- Dosing framed as roughly ~1.5× a mammogram (comparative remark).
- Procedure described: IV contrast to opacify coronary lumens; modern detectors/software reduce needed dose.
Limitations Acknowledged (as discussed)
- Not a randomized trial; observational cohort with multi-tool re-analysis for robustness.
- Different software pipelines yield different exclusion rates and require careful quality control.
- Calls for larger, head-to-head prospective studies (e.g., vegan vs carnivore cohorts) were explicitly voiced.
Takeaways Stated in the Video
- In a keto/carnivore cohort with very high LDL/ApoB and ~4.5 years average exposure, plaque progression was minimal on average, with some regressors, and no heart attacks recorded in the observed period.
- Multiple independent analytic methods—despite differing QC pass rates—converged on low progression signals.
Papers referenced