Tellit Likeitis

Systematic challenger of metabolic & cardiovascular misinformation. Bradford Hill criteria over cherry-picked studies. RCTs over testimonials.

[Tellit Likeitis @Tellit007]

Exactly right on the playbook.

But NATURE-CT answers the "something else" objection directly. No diabetes. No FH. No hypertension. CAC 100 or below. They screened out the usual confounders.

The 0 mm3 outlier at LDL in the 500s is a data point in a distribution where median plaque nearly doubled. It is not the distribution.

The question for the facultative hypercarnivore crowd: if LDL-C is not driving it in the NATURE-CT cohort, what is? Because the confounders they normally invoke are not in the room.

[Tellit Likeitis @Tellit007]

LDL-C of 111. No medications. Five years. Median non-calcified plaque nearly doubled.

That is the NATURE-CT study, just published in the Journal of Cardiovascular Computed Tomography. 205 patients. Low-risk. CAC 100 or below. No statins, no PCSK9 inhibitors, no lipid-lowering therapy of any kind. No diabetes. No familial hypercholesterolemia. People clinicians often tell to watch and wait.

Over a median 4.9 years, non-calcified plaque volume went from 27.5 to 53.5 mm3. Annualized rate: +4.9 mm3 per year. Total plaque grew at +6.7 mm3 per year. Low-attenuation plaque, the substrate SCOT-HEART linked directly to myocardial infarction, went from 9% prevalence to 23%. No symptoms. No events during follow-up. Just loading.

54% had a CAC score of zero at baseline. The plaque loaded anyway.
This is consistent with the Ference magnitude times duration model in peer-reviewed serial imaging. Arterial burden accumulates as a function of particle concentration and time. These participants were not running extreme LDL-C. They were running 111. The clock was still running.

Now here is what the keto community needs to sit with. Budoff and Kinninger, two of the lead authors on the KETO-CTA preprint, also authored NATURE-CT. The keto community concluded plenty. LMHR are safe. ApoB is not the driver. Paradigm shift. The missing control arm only became a methodological concern when someone else brought it up.

NATURE-CT does not close that gap. The studies used different analysis software, different populations, different intervals, and no randomized comparison exists. But it establishes a reference rate from the same author group using the same imaging modality.

Untreated participants at LDL-C 111 showed measurable non-calcified plaque accumulation over five years using Cleerly. The KETO-CTA preprint used QAngio as its primary tool. QAngio produces different absolute volumes from the same scans than Cleerly does. The retraction established exactly that.

The two figures cannot be compared numerically. What can be said: loading occurred at 111. Whether it occurred faster at substantially higher LDL-C over one year remains the unanswered question the missing control arm was supposed to answer.

The keto community cannot cite KETO-CTA as a research landmark while dismissing NATURE-CT as irrelevant. Both came from the same author group. The missing control arm in KETO-CTA was always the gap. NATURE-CT does not fill it. It shows the floor.

A CAC of zero is a meaningful risk stratifier at the population level. It is not a guarantee. Of those rescanned for calcium, 54% started at zero. Five years later, 31% remained there. New calcification appeared in patients the baseline score called zero.

Choose wisely my friends.

[Tellit Likeitis @Tellit007]

They found a small win and are giddily wetting themselves from laughter.

Precious.

Here is how small the "win" is.

A crossover study in the American Journal of Clinical Nutrition showed short-term eucaloric low-carbohydrate eating reduces liver triacylglycerol. Calories matched. No weight loss required. The keto community is sharing it as a landmark.

Three things they are not sharing.
First, the study is short-term. Crossover designs in dietary research carry carryover risk, and short-term carbohydrate restriction reduces liver glycogen and associated water content before meaningful fat oxidation occurs. The mechanism driving the liver TG signal determines how durable the finding is.

Second, the study has no fibrosis endpoint and no cardiovascular outcome. Liver TG is a validated marker of hepatic steatosis. It is not a validated surrogate for MACE. The gap between those two things is where people die.

Third, the diet that reduces liver fat in this study elevates LDL-C and ApoB in a meaningful fraction of people who follow it. DiMattia and Petersen, JAHA 2026, peer-reviewed American Heart Association journal: LDL-C increases of 18 to 70 mg/dL in lean ketogenic diet users. The claim that this elevation is benign has, in their words, no rigorous supporting data.

Fascinating.

Now the other side of the scale. Silverman et al., JACC 2020. Four independent mechanisms of LDL-C lowering: statins, ezetimibe, PCSK9 inhibitors, genetic loss-of-function variants. One dose-response line across all four. The biology does not care which mechanism lowers LDL-C. It responds the same way every time. That convergence is what causality looks like.

Keto runs the opposite direction on that curve in the people it elevates.

The win: liver TG down in a short-term eucaloric crossover.
The loss: LDL-C and ApoB up, with no outcomes data on the other end, against 170,000 patients in the cardiovascular literature pointing one direction.

They are celebrating the footnote. The index does not agree.

Isn't it ironic.

[Tellit Likeitis @Tellit007]

@DrSeanOMara identified the enemy correctly. Then built an $8,000 package around being the only one who can find it.

He asked if that makes him a grifter. The $8,000 package answered.

Precious.

His premise: visceral fat is the silent killer. Correct. His protocol: MRI scan, private consult, coaching package, Naples or Minneapolis only. His blind spot: the intervention with the strongest visceral fat reduction data in history requires none of that.

SURMOUNT-1 DXA substudy. Tirzepatide versus placebo. Fat loss ratio: 75% visceral and ectopic fat, 25% lean mass. Identical to the placebo group composition. His enemy. Eliminated. At scale.

SELECT enrolled 17,604 patients with obesity and cardiovascular disease. Major adverse cardiovascular events reduced by 20%.

Isn't it ironic.

Anyone who wants to understand what GLP-1 receptor agonists actually do to body composition should read @DrNadolsky. The short version: they hit exactly the fat compartment he has built an $8,000 package to identify.

He found the right enemy. He is selling the wrong weapon.

[Sean OMara MD, JD @DrSeanOMara]

Am I a low-carb grifter?

Lots of people lose weight and don't lose visceral fat. You can lose muscle, water, other types of fat. The only way to be sure is with an MRI.

I've seen it over and over. When people cut carbs, they start losing visceral fat.

[Tellit Likeitis @Tellit007]

@rodedc1 @KenDBerryMD @PlantBasedNews The firetruck arrives after the fire. ApoB was already inside the arterial wall before the event. That is not the same analogy.

Did your firetruck arrive before the fire started?

[Tellit Likeitis @Tellit007]

Rubino is solving the wrong problem.

His Nature Comment this week draws a useful distinction between clinical obesity (organ dysfunction present, treat as disease) and preclinical obesity (elevated risk, organ function preserved, treat as risk not disease). The framework is intellectually honest. The clinical/preclinical distinction holds up in the data. But the treatment threshold it implies is wrong.

Rubino's logic: demonstrated disease burden should determine treatment intensity. If your organs are still functioning, you have risk, not disease. Treat accordingly.

The problem: cardiovascular disease does not announce itself before it arrives. Plaque accumulates silently. The organs are "functioning" until the heart attack. Preclinical is not pre-problem. It is the problem, accumulating.

Karungi et al. 2026 analyzed 17 primary prevention randomized controlled trials covering 105,879 patients. Lower-risk populations derived approximately three times the relative risk reduction per unit of LDL-C lowering compared to higher-risk populations.

The five-year number needed to treat was statistically constant across risk strata. Early treatment is not less efficient. It is more efficient per year of exposure prevented.

Ference 2024 in Nature Reviews Cardiology puts the number to it. Five years of lipid-lowering therapy reduces cardiovascular risk by approximately 22%. Forty years reduces it by approximately 54%. The gap between those two figures is the cost of Rubino's threshold.

SELECT enrolled 17,604 patients. Obesity plus established cardiovascular disease. Many would qualify as preclinical obesity under Rubino's framework: organ function largely preserved, presenting for cardiovascular risk management, not active organ failure from adiposity itself. GLP-1 therapy reduced major adverse cardiovascular events by 20%.

Rubino would classify those patients as having elevated risk, not disease. SELECT showed what waiting for that threshold to be crossed costs them.

The clinical/preclinical distinction improves diagnostic precision. It does not improve the outcome of telling someone with a BMI of 32 and a ten-year cardiovascular risk of 8% that they have risk, not disease, and to come back when something breaks.

Fascinating.

[오창명 @changmyung1981]

🚨 Should obesity always be considered a disease?

A provocative new Nature Comment argues that the answer is no.

Francesco Rubino, chair of the 2025 Lancet Commission on Clinical Obesity, challenges the growing movement to classify all obesity as a chronic disease. Instead, he proposes a more nuanced framework distinguishing clinical obesity from preclinical obesity, with major implications for diagnosis, treatment, health policy, and research.

The central argument

For years, obesity was viewed primarily as a risk factor for diabetes, cardiovascular disease, cancer, and premature mortality.

More recently, advocacy groups and professional societies have increasingly promoted obesity as a chronic disease to reduce stigma and improve access to treatment.

However, Rubino argues that this shift may oversimplify a highly heterogeneous condition.

Two individuals with exactly the same BMI can have dramatically different health states:

✅ One may have preserved organ function and remain healthy for decades.

❌ Another may experience heart failure, respiratory impairment, metabolic dysfunction, and severe mobility limitations.

Yet current classifications often place both under a single disease label.

Clinical vs Preclinical Obesity

The 2025 Lancet Commission proposed a distinction:

🔴 Clinical obesity

Excess adiposity directly causes organ dysfunction
Impairs daily activities
Produces measurable physiological abnormalities
Represents a true disease state

🟡 Preclinical obesity

Excess adiposity is present
Organ function remains preserved
Future risk is elevated
Disease has not yet developed

This framework treats risk as risk and disease as disease.

Why BMI alone is insufficient

The article emphasizes that obesity differs from diseases such as diabetes or COVID-19.

Classic diseases are usually defined through:

Consistent symptoms
Predictable clinical trajectories
Shared biological mechanisms

Obesity lacks this uniformity.

BMI predicts population-level risk but often fails to predict:

Individual prognosis
Current health status
Treatment response
Underlying biology

As a result, obesity cannot always be interpreted as a disease at the individual level.

The biological argument

Another key point:

There is no single biological abnormality shared by all people with obesity.

While genetics, environment, aging, sleep disruption, medications, and food environments contribute, obesity represents multiple biological pathways rather than one disease mechanism.

The success of GLP-1 receptor agonists demonstrates that body weight is biologically modifiable—but not necessarily that every case of obesity constitutes disease.

Policy implications

The consequences are enormous.

If every person with obesity were classified as having a chronic disease:

Hundreds of millions could become eligible for lifelong treatment
Health systems could face unsustainable costs
Access criteria might become increasingly arbitrary
Some individuals may receive therapies with limited clinical benefit relative to risk

The author argues that treatment intensity should be proportional to demonstrated disease burden rather than BMI alone.

Take-home message

The debate is not whether obesity can be a disease.

The debate is whether all obesity should be considered disease.

Rubino argues that diagnostic precision matters:

Clinical obesity = disease.

Preclinical obesity = elevated risk, but not disease.

Recognizing this distinction could improve patient-centered care, sharpen research, reduce overtreatment, and create more sustainable health policy.

Reference

Rubino F. Why obesity shouldn’t always be considered a disease. Nature. 2026;654:33–36.

#Obesity #GLP1 #MetabolicHealth #Endocrinology #PublicHealth #PrecisionMedicine #ObesityMedicine #NatureJournal #Metabolism #HealthcarePolicy

[Tellit Likeitis @Tellit007]

@birddog_007 @drterrysimpson Yes, the correction of his title is noted. Funny that's all you had to say. Zero engagement with the hard outcome data as per usual. Fascinating.

This is understandable since your position has zero.

Classic @birddog_007

[Tellit Likeitis @Tellit007]

@drterrysimpson is a cardiac surgeon who has operated on thousands of hearts. He just explained the ApoB and inflammation debate better than most academics do.

His framing: inflammation is the fuse. ApoB is the TNT. Light the fuse with no TNT and nothing happens.

People with PCSK9 loss-of-function mutations carry genetically low ApoB across their lifetimes. They can have all the inflammation they want. They rarely get heart disease. Build up the TNT first and the fuse becomes catastrophic.

Fascinating.

He has familial hypercholesterolemia. His father had a heart attack at 55 and started statins that year. His father lived to 98, sharp to the end. His mother refused statins. She had vascular dementia by 85. He watched both outcomes in the same family, up close, across decades.

Remarkable.

His LDL-C is now in the 40s. His ApoB is 45 to 46. He has a positive CAC score. He said if he could go back 30 years to when his father started statins, he would start them then instead of now.

He also said this about people who challenge him for being on a GLP-1: willpower is not the issue. The issue is a brain that will not turn off food noise. He knew that 12 hours after his first injection.

None of this is theoretical. This is a surgeon who spent decades operating on the consequences of undertreated cardiovascular risk, then found himself carrying the same risk, and made every hard outcome evidence-based decision available to him.

This is what it looks like when the evidence base actually lands.

[Simon Hill MSc, BSc @theproof]

Statins, GLP-1s, seed oils, Ancel Keys, and the influencers shouting the loudest about all four.

Bariatric surgeon Dr Terry Simpson has familial hypercholesterolemia, lost 50 pounds on tirzepatide, and spends his time pushing back against the loudest voices on social media. We sit down to work through what the data actually says, and how to think about uncertainty in nutrition and medicine.

For the full show notes head to: https://t.co/y7x6C5eDc3

[Tellit Likeitis @Tellit007]

@drterrysimpson Thanks for the correction doc. I am outside the one hour edit window, but noted for future posts. Keep up the good fight!

[Tellit Likeitis @Tellit007]

Three fallacies in two screenshots. That dog don't hunt. All bark, no bite.

Fallacy one: the ACM dilution trap. Demanding all-cause mortality as the only valid endpoint for a cardiovascular drug is not rigorous thinking. It is a statistical trap. Non-cardiovascular deaths (cancer, accidents, infections) dilute the cardiovascular signal. Sasieni and Wald called this out explicitly in Circulation in 2017: applying an ACM standard to cardiovascular drugs is bad science. The NNT for cause-specific cardiovascular mortality is a fraction of the all-cause figure. Nobody applies the ACM standard to hip replacement surgery.

Fallacy two: scope restriction laundered as a general finding. The finding that primary prevention populations with near-optimal LDL-C show no ACM benefit is a scoped result in a specific low-risk subgroup. It does not mean statins have no benefit. It means the absolute benefit scales with baseline risk, which is exactly what you would expect from a drug reducing a dose-dependent cumulative process.

The CTT meta-analysis shows this directly: benefit is proportional to cardiovascular risk. Low-risk patients derive smaller absolute benefit. This is not evidence against statins. It is evidence for risk-stratified prescribing.

Fascinating.

Fallacy three: the NIH citation as authority. Posting a PubMed snippet does not make the interpretation correct. The same CTT database that shows 10% ACM reduction also shows 22% reduction in major vascular events, 19% reduction in coronary mortality, and a dose-response relationship with LDL-C reduction that runs across every subgroup analyzed. The data is not in dispute. The framing of it is.

For the confounder-free evidence on LDL-C causality: people born with PCSK9 loss-of-function mutations carry lower LDL-C across a lifetime and have 88% fewer coronary events.

That is not a statin trial. That is a natural experiment. It has been running for generations.

Do better.

[Bird Dog @birddog_007]

@Tellit007 @KenDBerryMD @PlantBasedNews When did I ever say carnivore and once again for those that know how to read

[Tellit Likeitis @Tellit007]

At least you are consistent. Wrong on every post. Remarkable.

"Statins have no mortality benefit" and "carnivore has no hard outcome data" cannot both be true simultaneously as a coherent position.

The CTT meta-analysis shows 10% all-cause mortality reduction per 1.0 mmol/L LDL-C reduction across 170,000 patients. The carnivore cardiovascular outcomes trial does not exist.

One side of this debate has the data. The other is waiting for a YouTube debate to substitute for it.

[Tellit Likeitis @Tellit007]

The metabolic improvement is substantial and worth crediting. HbA1c 7.2 to 5.2 sustained for a decade is a genuine clinical achievement.

The ApoB trajectory is the part worth a conversation. At >113 for 10 years, cumulative particle loading has been running above where you want it, even while insulin resistance was resolving. The two processes run on different timelines.

A CAC score would tell you what the arterial wall has been doing during those 10 years. That number, combined with where your ApoB sits now, is what shapes the next decision.

The metabolic case for low-carb is made. The cardiovascular case depends on what the imaging shows.

[Tellit Likeitis @Tellit007]

Fasting insulin has no standardized reference range, no FDA-cleared assay standard, and no randomized trial showing treatment to target reduces cardiovascular events. It is on this panel because it sounds metabolically sophisticated, not because it has earned a place in outcomes data.

@KenDBerryMD gets the BMI critique exactly right. Population screening tool, not a diagnostic standard. Visceral and ectopic fat as the operative variable. The panel should move beyond weight.

Then he goes off the rails. Classic @KenDBerryMD

The panel he proposes needs one substitution. Swap fasting insulin for ApoB. ApoB counts every atherogenic particle in circulation, integrates the TG-rich remnant burden he is trying to capture with TG/HDL, and outperformed every other lipid fraction in 293,000 UK Biobank participants in Sniderman et al. EHJ 2024. It is the number the panel is trying to approximate.

@DrMarthaGulati has documented exactly what cardiovascular risk stratification looks like when you move beyond LDL-C. ApoB is not an add-on. It is the variable the other markers are proxying for.

The rest of the panel is directionally correct. Add ApoB. Drop fasting insulin.

Choose wisely my friends.

[Ken D Berry MD @KenDBerryMD]

BMI has always been a crude population-screening tool, not a diagnosis. The clinically important issue is not simply “weight,” but excess adiposity, especially visceral/ectopic fat, with impaired metabolic function. The next step should be measuring waist, BP, TG/HDL, glucose, insulin, A1c, liver markers, not just relabeling more people by BMI.

[Tellit Likeitis @Tellit007]

@birddog_007 @KenDBerryMD @PlantBasedNews Two anonymous accounts. One has news clippings and arm flailing about a diet with 0 hard CVD outcomes and statin fear mongering.

The other has decades of hard CVD outcome data showing 88% less heart disease with low LDL-C and ApoB.

Choose wisely my friends.

[Tellit Likeitis @Tellit007]

@rodedc1 @KenDBerryMD @PlantBasedNews Really? You are still sticking with "firetruck tho!" meme from 20 years ag9? Spoiler alert: the firetruck was already in the building before the fire. It's the arsonist. Choose wisely.

[Tellit Likeitis @Tellit007]

@MichaelAlbertMD What happens to side effect profiles?

[Tellit Likeitis @Tellit007]

@birddog_007 @LiveAncestral Every deck chair in fantastic shape, except for that gaping hole in the hull. Classic.

[Tellit Likeitis @Tellit007]

@birddog_007 Anonymous account telling you not to take advice from anonymous account. Noted.

[Tellit Likeitis @Tellit007]

Those are in the guidelines. They are not in what most Americans actually eat.

The Standard American Diet is characterized by ultra-processed food, refined carbohydrates, added sugar, and excess saturated fat. The AHA dietary guidance recommends whole grains, vegetables, legumes, nuts, and unsaturated fats. Those are not the same document.

Blaming the guidelines for outcomes that resulted from non-compliance with the guidelines is not a critique of mainstream cardiology. It is a category error.