99% of heart attacks had a warning. Your doctor called it "normal."

Can you have a heart attack with “normal” labs and no warning signs? Or are we missing the warning signs because our thresholds are too late and our prevention model is too reactive?

Today I react to a fascinating video from Dr Brad Stanfield, BUT STICK AROUND because then we take a deep dive into the actual JACC paper behind the headline that “99% of people who had a heart attack had at least one warning sign beforehand.”

We break down:

* Why “normal” isn’t always optimal
* The difference between diagnosed risk factors vs actual exposure
* Why blood pressure of 128/82 may still matter
* The hidden role of insulin resistance and metabolic syndrome
* ApoB vs LDL-C vs non-HDL cholesterol
* Why prevention needs to start decades earlier
* The problem with reactive medicine
* What Jim Fix’s story actually teaches us about cardiovascular disease

This is not a message of fear. It’s a message of agency.

Because clogged arteries rarely appear out of nowhere. Most of the time, the body whispers long before it screams.

⏰ Chapters ⏰
0:00 The “99% of Heart Attacks” claim
0:57 Did people really have NO risk factors?
2:23 Why “SMURF-less” heart attacks confused cardiology
3:02 Are our thresholds too high?
4:21 Insulin resistance may be the missing link
5:14 The massive 9-million-person study
5:57 Over 99% had at least one non-optimal risk factor
6:50 Diagnosed risk factors vs actual exposure
7:18 The underdiagnosis problem in medicine
8:02 Why billing data can be misleading
10:13 Cardiovascular risk is continuous, not binary
11:42 Prediabetes still damages arteries
13:43 Why granular patient data matters
14:50 The tragic story of Jim Fix
16:47 “The second most common symptom is denial”
17:31 Exercise didn’t cause his heart disease
19:17 Why this data is actually hopeful
20:03 Reactive medicine vs prevention
20:32 “I lost weight… isn’t that enough?”
22:03 How aggressive should prevention targets be?
23:50 ApoB explained simply
25:29 My take on ApoB vs LDL-C
28:05 Deep dive into the JACC paper
35:28 Which risk factor was most common?
37:21 Most patients had MULTIPLE risk factors
39:26 Does this only apply to older people?
41:34 What happens when we use standard clinical cutoffs?
43:43 Why non-HDL cholesterol matters
45:47 The boring prevention advice still wins
46:38 Residual risk after lifestyle transformation
47:00 Why the fundamentals still matter most

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___________________________
🧬 About Dr. Lily Johnston
 
Dr. Johnston is a double board-certified vascular and general surgeon in San Diego, specializing in metabolic and cardiovascular prevention. She’s the founder of CorSight Health and a passionate advocate for reimagining how medicine approaches chronic disease.
 
This video is for educational purposes only and does not constitute personalized medical advice. Please discuss your individual health risks, labs, medications, and treatment decisions with your own physician.

Transcript

SPEAKER_01 0:00

Hey guys, I have a new video that popped up in my feed, and I cannot wait to watch it with you. This is from Dr. Brad Stanfield, a PCP down in New Zealand, who is telling us that 99% of people who have had heart attacks have this warning sign. Let's find out what it is together.

SPEAKER_00 0:21

On July 20th, 1984, Jim Fix, the man whose best-selling book on running had inspired millions of Americans to get in shape, dropped dead of a massive heart attack during his daily run on a quiet Vermont road. He was 52, he'd quit smoking, he'd lost 60 pounds, and he ran 10 miles a day. It's the kind of story that makes us all quietly wonder: is it possible to do everything right and still have a heart attack, come out of nowhere? And for a long time, the research seemed to say yes. Between 11 and 23% of the most severe heart attacks occur in people with none of the standard documented risk factors. So no high blood pressure, no high cholesterol, no.

SPEAKER_01 0:54

I think I'm gonna fact check this a little bit later because one of the more recent articles I have seen actually shows that about 90% of people who have major adverse cardiac events have one of the classic risk factors. But let's go through the rest of this and then see. Uh we'll circle back to what we think the attributable uh percentage of uh folks who have no risk factors is at the time of their heart attack. So um let's keep going and we'll come back to this idea in a little bit.

SPEAKER_00 1:39

So first, let's take a look at the scary finding seriously, because it comes from real research, published in credible journals, and it's genuinely alarmed the cardiology community. In 2023, researchers pulled data from 15 studies covering more than 1.28 million patients who had experienced a heart attack, and what they found was that 11.6% of those patients had none of the four standard modifiable risk factors. So again, no high blood pressure, no high cholesterol, no diabetes, and they were a non-smoker. In Australia specifically, that number climbed to as high as 23%. And then there's a troubling twist that made all of these findings harder to ignore. The patients who had no documented risk factors didn't do better after their heart attacks, they did worse. So the short-term death rates were higher in these smurfless patients compared to those who had traditional heart attack risk factors. And the working hypothesis was that these patients were flying under the radar of preventative medicine. They weren't being treated with cholesterol-lowering medications or high blood pressure medications, because it appeared that they didn't need them. And so they arrived at the hospital in worse shape. And the implication of this was uncomfortable. If up to nearly one in four of the most severe heart attacks happened in people with no detectable risk factors, maybe our entire preventative care framework was missing something.

SPEAKER_01 2:44

Maybe how I think part of this is gonna be you know, are we talk are we saying that the thresholds are too high, right? They actually did have some underlying dyslipidemia or insulin resistance, but because we're using diabetes as the cutoff, or because we're using sort of older cutoffs for dyslipidemia as our marker for who has high cholesterol or who does not, or we're using outdated markers like LDLC instead of perhaps the more informative APOB, or maybe that we're not even using some of the risk-enhancing factors that might capture a significant portion of the population. For example, LP little A or HSCRP, high sensitivity C reactive protein. The American College of Cardiology doesn't consider these huge factors for the population at large. But if we're talking about, and I think it's closer to 10%, uh, truthfully, that I think that 23% is high. And just looking quickly at that abstract, it was only about 3,000 patients with heart attacks uh that they were surveying. So it's probably a pretty small percentage, but or sorry, a small fraction of a big population. But nevertheless, uh somewhere in that 10 to 20% range, you know, there there may be a bunch of these patients who could be identified if we were looking at risk-enhancing factors in addition to the classic markers and perhaps waiting until patients have diabetes is not the best situation because, for example, we know that even hemoglobin A1C, which is the most common way we diagnose this, undercaptures patients, right? If we actually used a two-hour glucose tolerance test or fast and glucose measures, we would capture more people with a diagnosis of diabetes than waiting for their A1C. So I think that, you know, if I had to guess about who we're missing, uh probably it's that and probably it's LP little A. But let's carry on, see what else Brad wants to talk to us about.

SPEAKER_00 4:39

Heart attacks really could come out of nowhere. It's an idea that Jim Fix explicitly rejected. He was confident that if a person didn't smoke and exercised enough, heart attacks were essentially ruled out, and sadly, his own story proved that he was wrong. But was Fix just an unlucky outlier or was something hiding in plain sight? Recently, a team led by Dr. Hok Hugh Lee at Yonsei University in Seoul decided to approach the question of these smurfless heart attacks from the opposite direction. Instead of looking at which risk factors patients had documented, by the time that they arrived in the emergency room, they looked backwards, they tracked people through the years of repeated health examinations before any cardiovascular event occurred, and the scale of the study is remarkable. They drew on two independent cohorts, so the Korean National Health Insurance Service database, which covers essentially the entire South Korean population, and the multi-ethnic study of atherosclerosis, which is a long-standing American cohort. And together, that's more than 9.3 million people followed up for more than 13 years in Korea and 19 years in the US. And across those years of follow-up, over 600,000 cardiovascular events, like heart attacks and strokes, occurred. For each person who'd had a cardiovascular event, the researchers went back through all of their available health data. So every recorded blood pressure reading, every cholesterol measurement, every glucose test, every documented smoking history, and they asked, did this person ever have a non-optimal level of any of these four risk factors at any point in the years before their event? And here's what they found. More than 99% of people who'd had a first heart attack had at least one non-optimal risk factor beforehand. This was consistent across both countries, consistent in men and women, consistent across age groups from under 60 to over 80. And there wasn't just one risk factor hiding in the background, more than 93% had at least two. So we've got two bodies of research telling us the opposite thing. One says that up to 23% of serious heart attacks happen in people with no risk factors, but the other says that more than 99% had at least one. So both are published in top journals and both use large data sets.

SPEAKER_01 6:29

So this was me jumping the gun again because it's actually this Jack paper that I am remembering, thinking about the number of patients who've had non-optimal risk factor control prior to their major adverse cardiac event. So again, um, this was the discrepancy that was in my mind when we started this video. Let's see how Dr. Brad is going to help us reconcile this.

SPEAKER_00 6:49

So, how could they possibly both be right? Well, here is where the detective work gets really interesting. Because the disagreement between these two findings isn't really a scientific contradiction, it's a methodological one. So the two sets of studies are answering different questions. The standard smurfless research, so they asked, did this patient have a clinical diagnosis of a risk factor? That means, were they ever told by a doctor that they had high blood pressure? Was high cholesterol ever written in their chart? Did they have a formal diabetes diagnosis? That all sounds reasonable, but there are two massive problems with it. The first is under diagnosis. So getting a clinical diagnosis requires that you've seen a doctor, that you've been screened, and one of your readings has reached a threshold where you can now be classified with that diagnosis. In the real world, though, that doesn't often happen. So around half of those with high blood pressure, so the single most common modifiable risk factor for cardiovascular disease, they have not been diagnosed. Low diagnosis rates for high cholesterol and diabetes are also well documented. So if your blood pressure has been quietly running at 138 on 88, for instance, but you've never had it flagged, you'd showed up in the Smurfless data set as no hypertension, but you did have high blood pressure.

SPEAKER_01 7:50

So this is a great point about the quality of research data that we have for some of these studies. The point Brad is highlighting is the difference between actually looking at the measured values, right? The glucose measurement, the A1C measurement, the blood pressure measurements in the chart versus what a doctor has written down and diagnosed. Because patients will show up all the time in clinic and say, Oh, I know my blood pressure was high today, doc, but it's just because I was late or I have white coat syndrome, but it's usually fine at home. And then the doctor will say, okay, and um sometimes just take the word for it or go from there. This uh should be validated with home measurement readings and noted as such in the chart. The next step that we often see in big studies is billing data, which is not only the diagnosis that might be written down in the chart, but what's actually coded. So everything that I do, for example, gets translated into a diagnosis code and a work code for the procedures that I do, for example. So it's one thing for me to write down in my notes that the patient has a diagnosis of hypertension, but if I forget to click the box in my medical record that says the patient has hypertension, now we're even one step further removed from the clinical relevant data. And I am usually pretty hesitant to make any changes in my own practice based on studies that are only using billing data. And unfortunately, the biggest data sets we have are billing data. So, like the uh Medicare data set, for example, is predominantly a billing one. Most of the insurance company data sets, like the TriNet data set, is one that's come up several times recently in the vascular surgery literature, is all a billing data set, and they can pull pharmacy records, which is nice because you know what the patient's been prescribed, but you don't know if they're taking it, and you don't necessarily have any of the actual numbers in front of you. What was that patient's hemoglobin A1C? We don't know. We just know they have a diagnosis of diabetes. What was their blood pressure? We don't know. They just have a diagnosis of hypertension. So this comes back to the idea of being really, really conscientious about what is the true underlying data set that we're using and how accurate do we think it is.

SPEAKER_00 10:13

Second problem relates to the thresholds that the researchers selected to define risk. So cardiovascular risk, it doesn't have an on-off switch. These risk factors operate on continuous, cumulative gradients, meaning that the damage accumulates even at levels that fall below clinical diagnosis thresholds. A blood pressure of 126 on 82, for instance, is not clinical hypertension by any guideline, but it is elevated above what the American Heart Association considers optimal. It can promote plaque buildup in the arteries. And if you've had it for 15 years, that's 15 years of accumulative vascular damage that wouldn't show up in a smurfless study because you were never officially diagnosed. In fact, the thresholds used in the smurfless literature, they've often been high by current standards. So this study in the Journal of Cardiology defines hypertension as blood pressure of 140 and above. This is exactly why this new study that we've been looking at used stricter cutoff points derived from the American Heart Association's Life's Essential 8 framework. So these targets are associated with ideal cardiovascular health, not just the thresholds that trigger clinical treatment. So non-optimal blood pressure is defined as a systolic blood pressure, so that's the top number, of above 120, a diastolic blood pressure, so that's the lower number of above 80. Non-optimal cholesterol is total cholesterol above 200 mg per deciliter, non-optimal fasting glucose is 100 milligrams per deciliter or above, and past or current smoking counted, not just current. So as Dr. Lee put it plainly, he said that when they looked closely, these earlier reports of risk factor-free heart attacks might have actually reflected missed risk factor diagnoses or risk factor levels that were non-optimal in terms of cardiovascular risk.

SPEAKER_01 11:41

Since so I want to point out, for example, that that fasting blood sugar of over a hundred would be a diagnosis of pre-diabetes, not actually diabetes. And so again, that may help us capture way more people if we are working under this idea that in fact insulin resistance, poor glycemic control, hyperinsulinemia might be one of the key driving risk factors for cardiovascular disease in 2026. Because I do think, you know, smoking is never going away completely, but it is becoming a smaller and smaller fraction of the patients that I see and treat. And I think for the for the cardiologists as well, you know, it's it's down quite a bit. And yet we are seeing more patients than ever. Um high blood pressure is always an issue. Again, using that 120 cutoff is uh much more aggressive. And uh let's see if we can figure out, you know, again, between metabolic syndrome, right, elevated fasting glucose, elevated blood pressures. Um, they're interestingly using total cholesterol rather than non-HDL cholesterol or LDLC. Again, I would say um LDLC and triglycerides are probably the most helpful. Non-HDL is um even better than those, or is reflective of both of those. And um APOB would be even better, though uh that is not yet reflected in guidelines, and we still don't have LP Little A, which again also not reflected in guidelines, uh, except in the very recent 2026 ACC AHA new set.

SPEAKER_00 13:13

Many of these, with risk factors, have continuous rather than a yes or no relationship with the risk of developing cardiovascular disease. And when they were asked about these striking results, Dr. Lee pointed to the consistency. So he said, surprisingly, the results were almost identical between the Korean and the US cohorts. That consistency across very different populations and very different health systems makes our findings especially strong. The two literatures, they are not conflicting each other. What they're answering are different questions. Was the patient diagnosed versus did the patient have exposure? Different question.

SPEAKER_01 13:42

So I don't think they're different questions. It's actually the same question. It's the precision of the answer, right? They're still all trying to get at do these patients have poorly controlled risk. The answer, though, is really based on the precision of the data underlying that answer. And when we actually go into the numbers and look at blood pressure measurements, fasting glucose measurements, we recognize that the granular patient-level data way outperform what a doctor captures because we gloss over the blood pressure of 129 over 84, right? We gloss over the fasting glucose of 105 often, right? I tend not to, but um, that's because this is my bread and butter. Nevertheless, in general practice, this becomes a difficult thing. And again, you know, are we actively recommending blood pressure medicine for people who are 128 over 82 when they show up in the office? No, most people would say that's gonna be kind of standard, and uh, you know, exercise more, eat better, and we'll check again in a year.

SPEAKER_00 14:57

So a smurfless study conducted at the moment of his death might have coded him as risk free. He'd quit smoking 17 years earlier, so he was a non-smoker. He wasn't a documented diabetic, and he wasn't formally diagnosed with high blood pressure. It looked like a clean bill of health, at least with three out of the four standard risk factors. But if we apply the new study's methodology, the picture is completely different. Fix was smoking two packs of cigarettes per day when he took up running at the age of 35, and he weighed 214 pounds, significantly overweight by any standard. His father had died of a heart attack at age 43 after a first heart attack at age 35, a family history of premature cardiovascular disease that should have put him in a high risk category. Then there was the fourth traditional risk factor. His total cholesterol was above 250 mg per deciliter, which is well above the 200 mg per deciliter non-optimal threshold and elevated even by clinical diagnoses standards, and his autopsy confirmed that all of this might have been predicted. One coronary artery was 95% blocked, a second was 85% blocked, and a third was 70% blocked. And there's one more detail that makes Fix's story particularly striking. So in December 1983, seven months before his death, he visited the Cooper Aerobic Center in Dallas. So Dr. Kenneth Cooper, the pioneering exercise physiologist and Fix's personal friend, urged him to take a cardiovascular stress test, but Fix refused. Cooper was haunted by this refusal. He told reporters afterwards that he adamantly refused, and that stands out in my mind now. I don't know why he refused. Maybe he had an underlying feeling that he was ill. Friends and family also reported that Fix was complaining of chest pains during his runs in the months before his deaths, and when physicians looked through his records, these may have been angina episodes, and Fix's own journal entries recovered after his death reveal his denial at work. So that spring, just months before his fatal run, he wrote, My neurotic blood pressure anxieties occasioned by feeling intense these past two months are apparently without foundation. Maybe the problem is nothing more than being hypochondria. A cardiologist commenting on this case at the time put it bluntly, the second most common symptom of coronary disease after ingina is denial.

SPEAKER_01 16:54

Fitzheaded, uh, I'm chuckling because I actually think that this is an important thing in in the vascular disease realm as well. Uh the number of patients who are in denial about symptoms is high. And I don't think it's that they're truly in denial, it's that they're so scared. And they're scared of finding out that they need surgery, they're scared of finding out that they might lose a leg or that they might have a stroke. And I get that. And part of the goal of this channel is actually to help sort of demystify some of these things, but also to empower you to prevent them so that you never ever need all any of those interventions. The other thing that I find fascinating about this is that I've done a couple of videos on the importance of exercise and the relationship between, for example, uh a high volume endurance exercise and the presence of coronary calcium. And a lot of people show up in the comments saying, Oh, well, you don't need the exercise. Look, look at Jim Fix, look at Jim Fix. He died and he was an exerciser. And I haven't actually gone back in depth to look at his history, but Dr. Brad has done a phenomenal job of uncovering all of this. And now, again, in retrospect, of course, right? It had very little to do with his exercise. Probably that kept him alive much longer than he otherwise might have been, given his very strong family history of premature cardiovascular disease. If his dad had a heart attack at 35, I am certain that there is either LP little A or a strongly inherited genetic component to that, plus uh two packs a day of smoking for a number of years, plus excess adiposity and the inflammation associated with that. So uh I am not at all surprised that poor Jim Fix had his cardiac event. And it sounds like there were a lot of reasons to believe that this was um that he would have heart disease. And then he actually had physicians who were trying to, you know, help get him to a place where they could help manage that for him. And unfortunately, that was not something he was interested in.

SPEAKER_00 19:03

His story is not about the failure of healthy living, it's about what happens if you assume that the visible transformation, so the weight loss, the cutout cigarettes, the miles run, is the whole story. And here's what genuinely struck me about this data, because I think the correct interpretation is empowering, not frightening. If cardiovascular events are nearly always preceded by detectable non-optimal risk factors, if the 99% number holds across 9 million people in two different countries, then the scenario of a heart attack truly coming out of nowhere in someone with long-term optimal risk factor levels is vanishingly rare. It's not common, it's not increasing, it's rare, and that's good news. It means the framework for prevention actually works when it's applied correctly and early enough. The key words here though are early enough. The damage from non-optimal risk factor levels accumulates over the years and decades. And the new study's data proves this by tracking people longitudinally rather than catching them at the moment of a crisis. As Dr. Nathan Wong, who directs the heart disease prevention program at UC Irvine, he put it when commenting on the study, the problem is that we practice reactive medicine rather than preventative medicine, and that is the real villain in the story, not heart disease itself, but the way clinical medicine waits for risk factors to cross treatment thresholds before acting.

SPEAKER_01 20:09

That is the I agree a thousand percent, and that is why this channel exists, and I am so glad that Dr. Brad is calling this out for all of us as well. And I agree that this is a message of hope, and this is a message of being proactive with your health. And if you have been following this channel, I think you're probably already on this journey. The other thing that he kind of went quickly past, though, which I think is really important because I see this a lot in my patients, is if you had risk factors before and you have been on this health journey and you are doing really well now, it doesn't mean that we still don't have to be a little bit more aggressive to perhaps calm down everything that preceded your amazing transformation. So I have a lot of patients who come to me after they have lost a bunch of excess fat and they are now exercising and they're now really in tune with their body and their health, and they want to make sure that they're doing well, and they're hesitant to have additional control measures like medications, supplements, or more aggressive lifestyle interventions because they're so much better already than they were. And they're like, isn't that enough? What was it all for if I still have to be on medicine, right? That's not what I did this for. I did this to get off of my meds. And I get it, that's amazing. And and probably we can be off way more meds than we otherwise would have been, but we cannot ignore a history of smoking. We cannot ignore 40 years of insulin resistance or prediabetes or diabetes, even if it's in remission. We cannot ignore years of high inflammation, high chronic stress, whatever the case may be. We just have to acknowledge that that is still influencing what's going on on the inside of your body in those artery walls, and be realistic about what the options are to manage that.

SPEAKER_00 22:03

Model that is structurally too late. The goal is to keep it optimal, so below 120 on 80 for as long as possible. Now for older adults, we may accept slightly higher blood pressure readings to make sure that they don't feel faint or dizzy. It's not to get your LDL cholesterol below 100. In my view, it's to get it below 55 to manage your weight.

SPEAKER_01 22:35

Drop me a note in the comments if you want to hear more about polygenic risk scoring as it relates to cardiac disease. The target of 55 for the person at average risk might be a little aggressive. I know that overall, yes, people are saying lower better. And I am also acutely aware that getting there may require a fair amount of medication, and those come with at least the effect of having to be on multiple medications, but also drastic side effects for some people. So I don't know that I think everybody needs to be 55 or lower for their whole life. And yes, I am certainly aware that the lower the better. We did talk about in the recent Ask Me Anything a case study that I just read where somebody had genetically low LDLC, like in the 40s for most of his life and still developed plaque because of his insulin resistance. That is uh a true statement. And so it won't protect everybody in the absence of controlling other risk factors, which I know he's getting to and would also agree, is of course very important.

SPEAKER_00 23:40

And blood sugar levels to use medications like disepatite if needed, all of that is a higher bar that most clinical practice doesn't quite aim for. But to me, that is the bar that the data actually supports. But there is a catch here, because even if your LDL cholesterol looks fine on a standard blood test, there's a reason why it might be misleading you. LDL cholesterol of greater than 55 milligrams per deciliter is a real threshold and it captures a lot, but it's a blunt instrument. What actually drives atherosclerosis, so that's the process of plaque building up in your arteries that eventually causes a heart attack, isn't cholesterol mass, it's the number of atherogenic lipoprotein particles. And each particle that can penetrate our blood vessel walls and deposit cholesterol has a tag on it, and that tag is called APOB. That is a direct count of all of those particles. And the main problem of a standard blood test that most doctors use, so LDL cholesterol, is that it measures cholesterol content carried by those particles, not the number of particles themselves, and those two things can diverge significantly, particularly with those who have got metabolic syndrome, insulin resistance, or elevated triglycerides. So you can have an LDL cholesterol that looks fine, but when you test your APOB, your APOB comes back high. Clinical medicine in the past has been slow to adopt APOB testing because of concerns around cost effectiveness. Adding APOB at roughly doubles the cost of a standard lipid panel. So is it really worth measuring something beyond the standard panel? Well, the argument just lost its last leg. A study just published in JAMA modelled 250,000 statin eligible adults across their lifetimes and compared three strategies for deciding the intensity of lipid lowering therapy. They looked at using LDL cholesterol, non-HDL cholesterol targets, or using APOB targets. The APOB guided strategy produced the most quality-adjusted life years, and it was highly cost-effective. And the 2026 guidelines have now formally incorporated APOB into its recommendations for the first time in a major US guideline, particularly for patients where LDL cholesterol may underestimate true risk.

SPEAKER_01 25:26

And one So, what I'll say about this is if we are optimally managing your insulin resistance, um, and he said trisepatide, which sure, that's a very nice drug for that in people who require it, but there are also things like metformin, uh, there are, you know, drugs that will help excrete glucose. And oh, by the way, let's talk about the nutritional component of how we get there and using both uh our foundational nutritional strategies and exercise to help us manage our insulin load. Uh, I think that is probably where I would start. Uh, the idea that your APOB is going to be very discordant or provide a different answer or target than your LDLC is unlikely because your triglycerides should be pretty low if we are managing your insulin resistance optimally, right? If you have good insulin sensitivity, your triglycerides should be well under 100. And therefore, we're not going to have an excess of remnant particles to contribute to a slight and an elevated or discordant APOB relative to our LDLC. And non-HDL cholesterol, which you can get on a standard lipid panel, is also something that will tell you that. So I think that you should get your APOB and your LDLC measured together at least once or twice and see if you have very discordant results. If you do not, and you are maximally insulin sensitive, I'm not certain that we have to keep following APOB. It, I mean, he says it doubles the cost of a lipid panel. A lipid panel is, I don't know, somewhere in their $15 to $20 range if you're here in the US. APOB is again about 18 to 20 bucks. Um, so sure, it doubles the cost. It's not an inordinate cost. And it's worth doing a couple of times just to make sure that you're concordant. Once you know that and once you have maximal insulin sensitivity, I don't think it's necessary to keep track of that over time. If you wish, by all means. But again, the people for whom we you see discordant APOB versus LDLC are people with insulin resistance who have elevated triglycerides, elevated remnant particles. Uh, there will be a few people who have a familial kind of dyslipidemia where they have lots of calomicrons or triglycerides that are unrelated to their metabolic status, largely, but um that's a very, very rare percentage, and they will be caught in other screening methods as well. So APOB is a better tool. Uh, it should be checked. Once you are concordant, you can stick with your non-HDL or your LDL and make sure that your targets are appropriate there.

SPEAKER_00 27:53

One of the most powerful tools that we've got for controlling our cholesterol levels is tragically underused. So in this next video here, I'll show you the remarkable story about how it was discovered and the data about how big an impact it can make.

SPEAKER_01 28:05

All right. Thank you, Dr. Brad. We are gonna give that video a like. So I have here the journal from the or the journal article from the Journal of the American College of Cardiology, or Jack. And this is what Dr. Brad was talking about in the video where he says that over 99% of people who have a heart attack or a heart event have a risk factor that is poorly controlled before the event. So this is what I was thinking of when he initially said that 10 to 23% of folks did not have a risk factor for a heart attack, and these were the sort of smurfless people. But in fact, this was something I had already seen, and and indeed, in fact, when we look carefully at the data, over 99% of people, but I really want to dive in deep and figure out which of the risk factors contribute the most for patients who have events, and are there any ways to sort of reanalyze the data and uh see whether there's more interesting stuff here if we dive a little deeper. So I'm gonna go through this paper with you. We're gonna go through their findings, some of the key figures from the paper, and see what we can learn. So this was published by Philip Greenland and colleagues in October of 2025. And forgive me while I scroll through here. We're gonna take a quick peek at this central illustration. So they are showing us again, as Dr. Brad said, that we have two separate cohorts here. We have the Korean National Health Database, which includes their whole population and is a really strong group because of the fact that there's really no bias here. It's the entire population. They have their lab data, they have their blood pressure measurements. And you could argue, well, that's a Korean population that doesn't necessarily represent us here in the European and Western in the United States, for example, but we now have the Mesa cohort, the multi-ethnic study of atherosclerosis, which is a really well-validated cohort, uh, largely based in the United States, where we also are capturing a large swath of the population and their cardiac events. So the MESA here is on the right, the Korean National Health System is on the left of this figure, and what they're showing you at the top is uh does CVD frequently occur without preceding non-optimal traditional risk factors? So we have many, many more patients in the Korean database here, but we have about six, almost 7,000 uh CVD events in the MESA cohort, and they're breaking these down for you. So CHD will be coronary heart disease, MI or heart attack, stroke, and heart failure, and then we total all of that to be CBD, excuse me. So the total CVD is 1.1 K in MESA, and the uh overall cohort was almost 7,000. We have 600,000 events in the Korean out of over 9 million patients. And here again is the criteria, are the criteria that they use for non-optimal risk factor control. So systolic blood pressure over 120, diastolic blood pressure over 80, total cholesterol over 200. We're gonna get into the sensitivity analysis and see that they actually also looked at non-HDL cholesterol and LDL cholesterol, which is actually more informative, not surprisingly. Then we have fasting blood glucose over 100, which again, this is a threshold for uh impaired fasting glucose. This doesn't even meet criteria for diabetes at this level, or any treatment for diabetes, and then past or current smoking. And what they're showing you in the bar graph is for each of these different presentations of cardiovascular disease, how many of the patients had one or more of these poorly controlled risk factors? And whichever of these you choose, it is well over 99% had a non-optimal risk factor here. There actually are some blue bars, they're just so tiny because they're all less than 1%. And so they say, given near universal presence of greater than one non-optimal traditional risk factors prior to any CVD, CVD events rarely occur in the absence of antecedent non-optimal traditional risk factors, highlighting the importance of primordial prevention efforts. So let's now take a deeper dive into the paper and see what else we can dig out from the results. So here's just uh a little bit more in the methodology, universal health insurance in South Korea. This is their national database. There was originally about 10 million, and they excluded some probably for missing data. Multi-ethnic study of atherosclerosis launched in July of 2000, you know, almost 7,000 adults aged 45 to 84 years. The Mesa cohort is um uh just a little bit of an older population. The Korean database includes everybody aged 20 years or older, but I don't think that's terribly relevant. Obviously, cardiovascular disease is typically a disease of the older adult population. Outcome definitions here. CHED event is defined as incident heart attack or death caused by coronary heart disease, a total CBD event, incident MI, heart failure stroke, or death. First occurrence of each outcome was considered. So if they have multiple events, they're taking the first one as the definitive event. Risk factor definitions. Definitions of non-optimal. So how do they get to these thresholds? Definitions of non-optimal risk factors were based on the American Heart Association's ideal cardiovascular health framework, reflecting evidence that optimal levels of risk factors are lower than commonly recognized and treated in clinical practice. So later in the paper, they're gonna go to clinical criteria and contrast that with these non-optimal criteria. So again, greater than 120 systolic blood pressure. We went through these earlier. And here's what I want to highlight. As a secondary analysis, exposure to clinically elevated risk factor was defined with higher cut points as often used for clinical diagnosis. And that is a systolic blood pressure of over 140 or a diastolic over 90 or any blood pressure treatment, total cholesterol over 240 milligrams per deciliter or lipid lowering treatment, fast and glucose over 126 milligrams per deciliter, which is the formal threshold for a diagnosis of diabetes, or that diagnosis of diabetes or glucose lowering treatment at any point among all available examination visits before the outcome event. And current tobacco smoking at the last examination rather than just a history of tobacco use. Okay. So statistical analysis, sensitivity analysis. All right, let's get into the results here. I'm actually going to go down to the figures because I think that they're a little bit more um illustrative here. So here is the bar graphs. The again, Korean Health Service is on the left, Mesa is here on the right. Each of the different event types is its own separate line here with the total all the way at the bottom, and the x-axis is percent exposed to non-optimal risk factors prior to the cardiovascular event. So the headline here is for total CVD events. I'm looking here at the bottom row, were at least one non-optimal risk factor prior to the event, 99.3% of patients in the Korean data set, and 99.5% of patients in the MESA cohort had at least one non-optimal risk factor prior to their CBD event. And if you want to break this down, the vast majority of that is elevated blood pressure. So 94% in MESA, 95% in the Korean Health Service had elevated blood pressure readings prior to their event. Non-optimal cholesterol is in between 73 and 77%, depending on the cohort. And non-optimal glucose is actually higher in the Korean data set at 75% and about 56% in the Mesa cohort. And past or current smoking is about half of patients in the Korean data set and about 60% in the Mesa cohort. So let's now keep going and take a look at how many had one or more risk factors, because I could see how you would say, well, this is maybe a bunch of people who just had one slightly elevated blood pressure reading at any time in their prior history, right? Somebody came in one day late for their appointment and they got a blood pressure that was like 124 over 83, and like that was, you know, the one thing. But in fact, if you go look at this, we're now breaking this down by how many risk factors did they have prior to the event? And if you're again, I'm gonna go down here to the total, um, because I think that's again, probably the big picture for everybody, whether you're worried about heart attack, heart failure, stroke, uh, let's combine them all and just take that into account. The number of people who had just one non-optimal risk factor is about five to six percent. So you say, okay, 99% of people have at least one non-optimally controlled risk factor. And you want to say, well, one is just not quite good enough because it could be a total one-off. Okay, so take away five or six percent. We're still well over 90% having uh and up close to 95% having one more than one risk factor that would predict or at least uh highly be associated with the likelihood of some kind of cardiac event. So about 20 to 27 percent had two non-optimal risk factors. But if we're gonna say three or four, now we're well into the 60 to 70 percent range. So 43% on the Korean and 41% in the Mesa cohort had three or more, three non-optimal risk factors, and 25% to 30% had four non-optimal risk factors. So, again, the point here is that this is not really an unpredictable scenario. If we're thinking about this at the optimal thresholds rather than these clinical thresholds, then we say, okay, this actually makes sense, right? We know these people have probably metabolic syndrome because of the high blood pressure and elevated cholesterol, right? Some of that's gonna be their triglycerides. And again, the the glycemic control is not as prevalent here as I would have expected, but it is definitely a big part of the associated risk, especially as it might be translating into poor blood pressure control. So let's keep going here and see how much of this is related to age. So this is a breakdown of each of these cohorts, again, by each of the event types. And now we're looking at well, is age a hugely important factor? Are we only seeing this in the older patient groups and it's not helpful in younger patient groups? And the answer to that is even just visually, you can see no, this applies to all age groups. Even if we're looking at folks under 60 years of age, let's go again down here to the total CVD event cohort or group here. Under age 60, we're still seeing 99.7% in the Korean group and 95.4% in the Mesa cohort having at least one non-optimally controlled risk factor prior to their event. And yeah, as you get in the older groups, uh, we are now up in the 99% range in both data sets. But this is again not something that is only explained by the fact that risk factor control seems to loosen a little as adults get older and we determine that it, you know, for example, blood pressure. We tend to be less aggressive controlling that in people over the age of 80 because if we are too aggressive and we drop their blood pressure too low, the risk for falls becomes high, and that's a bad event. So we try not to do that. And again, this is just going to show you that no matter where you are in life, these risk factors are important and do predict your risk of heart attack, stroke, or any cardiac issue. Um men versus women in Mesa, we're still seeing uh high levels of prediction here. So again, um, this is actually now by age and sex. So again, the older we are, a little bit stronger, but even men and women under 60, 98% in men under 60, 96.6 percent of women under 60 in the Mesa cohort have at least one non-optimally controlled risk factor prior to their CVD event. And now we're gonna look at the higher clinical criteria. This means rather than a systolic blood pressure of 120, we're now gonna bump that up to 140 and say, if we're just gonna use the criteria that you know a lot of doctors in regular practice are using to make these diagnoses, we're gonna move away from a fasting glucose of over 100 and bump it up to 126, which is the threshold for diabetes, rather than just impaired fasting glucose. Let's take that up and see how many people at this, you know, uh slightly more relaxed set of thresholds would have this, right? Is it just that we're gonna be getting too neurotic about these thresholds? And what you see is that we're still well over, not well over, we're at 90% or greater. So if you again, let's come down here to the total. Prior to total CVD event in the Korean cohort, it's 90.7%. And it is 93.2% for the Mesa cohort. So again, slightly more relaxed, we still see that we can largely account for the CVD risk based on these non-optimal or these clinically elevated risk factors. Okay. And again, here's the breakdown. Elevated blood pressure was the majority, so 74% in the Korean cohort, about 84% in the MESA cohort. Uh, the next risk factor is elevated clinically elevated cholesterol at about 51% in both, clinically elevated glucose in 40% of the Korean cohort and 30% of the Mesa cohort, and active current smoking in 23% of the Korean group and 16% of the MESA group. So again, um the clinically elevated glucose is coming down, right? This was about 50% when we looked earlier. If we had the more strict threshold, now it's much lower, and current smoking rather than former smoking is also significantly lower. Interestingly, blood pressure has come down, but it's still quite high. And the uh clinically elevated cholesterol is also still quite high. Um, the sensitivity analysis here I want to go through because I don't have a figure for this, but I think this is actually important and interesting, particularly if you're interested in the lipid component of this. So they say when non HDL cholesterol greater than 130 was used instead of elevated total cholesterol. As one of the non-optimal risk factors, prevalence of at least one antecedent non-optimal risk factor was even higher, ranging from 99.5% to 99.9%. So again, this is taking into consideration the fact that non-HDL cholesterol accounts for the atherogenic or plaque forming particles, right? That is triglycerides and your LDLC. Because again, we're taking away HDL from total cholesterol and left with the atherogenic particles. It is another proxy for APOB, again, not quite the same because we're still measuring the cholesterol rather than the particles carrying the cholesterol, but it's a better proxy than total cholesterol. And I would expect that to be more informative, and indeed it is. And they also say with lower lipid cut points, like non-HDL cholesterol greater than 100 or LDL cholesterol greater than 70, prevalence reached 100%. So again, if we are using better lipid measures and stricter lipid thresholds, we actually see significantly improved performance of this non-optimal risk factor control as a way to understand who may be susceptible to these cardiovascular events. Second, when only the first subtype of CBD event was analyzed as the outcome of interest, prior exposure to at least one non-optimal risk factor were similarly universal. Results were consistent for death from CHD and from CBD analyzed as separate subtypes. And fourth, the results were identical in a less exclusive Korean national health sample, removing only participants with no data on one or more risk factors at any visit during follow-up. So this was uh the last bit of that was just them sort of messing with the data to make sure that this is a robust finding, and indeed it is. So, we're gonna go back to this central illustration and just say the stuff that we talk about here all the time, the boring stuff, make your blood pressure normal, make your lipids boring. Don't smoke. And if you have a history of smoking, recognize that that is gonna impact you for the rest of your life. And like it is what it is, it's okay. We just have to acknowledge that there has been impact, right? This is a disease that forms the plaque forms over decades. The injury to the arteries may continue at a smoldering level, even if you have rearranged your whole life and gone on this health journey and done all the right things, right? Just like Jim Fix, we may still have some residual risk from stuff that happened earlier in life. And it's okay. We just have to acknowledge that that is still playing a role on the inside of our arteries. I hope you found this deep dive of the paper helpful. I found it really interesting, and I think it's hugely validating for those of us in the prevention space to continue doing what we're doing. And even though I love the idea of making sure that everybody gets an LP little A measured and that everybody gets an APOB measured, and that we're following HSCRP and dealing with visceral adiposity and all of the stuff, right? Clearly, if we just stick with the boring big risk factors, that is a huge, huge amount of information and all the rest of this stuff. You can understand why it's a risk-enhancing factor and not necessarily something that is central to uh our understanding of who's gonna get plaque and have an event. So let me know what you think about this in the comments. Back to the video. I don't know if we need back to the video, but there you have it. Awesome. Until next time, guys, take really good care.