Circulation January 2, 2018 Issue

Dr. Carolyn
Lam:              
Welcome to Circulation on the Run, your weekly podcast summary
and backstage pass to the journal and its editors. I'm Dr.
Carolyn Lam, associate editor from the National Heart Center and
Duke-National University of Singapore. Our feature paper today
focuses on LDL cholesterol results from non-fasting samples and a
personalized novel method of LDL cholesterol estimation that you
will surely want to know about. So stay tuned, coming up right
after these summaries.


                                               
The first paper provides new evidence that RUNX1, a gene
intensively studied in the cancer and blood research fields, has
a critical role in cardiomyocytes following myocardial
infarction. Co-first authors, Dr. McCarroll and He, corresponding
author Doctor Loughrey and colleagues from University of Glasgow
generated a novel tamoxifen-inducible cardiomyocyte-specific
RUNX1-deficient mouse and showed that RUNX1-deficient mice were
protected against adverse cardiac remodeling post-MI, maintaining
ventricular wall thickness and contractile function. Furthermore,
these mice lacked eccentric hypertrophy and their cardiomyocytes
exhibited markedly improved calcium handling.


                                               
At the mechanistic level, these effects were achieved through
increased phosphorylation of phospholamban by PKA and relief of
sarcoplasmic reticulum calcium pump inhibition. Thus, these data
identified RUNX1 as a novel therapeutic target with translational
potential to counteract the effects adverse cardiac remodeling
post-MI.


                                               
The next paper invites us to consider that some our
resource-intensive quality improvement initiatives may not be
fulfilling their intended goals or even justify their costs. In
this paper by first author, Dr. Kutty, corresponding author, Dr.
Chan and colleagues from St. Luke's Mid America Heart Institute,
the authors evaluated the association between the implementation
of pediatric medical emergency teams and the risk-adjusted
mortality at the hospital level.


                                               
To do this, they looked within the pediatric health information
system for freestanding pediatric hospitals and calculated the
annual risk-adjusted mortality rates for sites between 2000 and
2015. A random slopes interrupted time series analysis was then
used to examine whether implementation of a medical emergency
team was associated with lower than expected mortality rates
based on the pre-implementation trends. The authors found that
before medical emergency team implementation, hospital mortality
rates were decreasing by 6% annually across all hospitals. After
medical emergency team implementation, the hospital mortality
continued to decrease by 6% annually with no deepening of the
mortality slope as compared with the pre-implementation trend for
the overall cohort or when analyzed separately within each of the
study hospitals. Five years after implementation across study
sites, there was no difference between predicted and actually
mortality rates.


                                               
Thus, in summary, the implementation of medical emergency teams
in a large sample of pediatric hospitals in the US was not
associated with a reduction in hospital mortality beyond the
existing pre-implementation trends. This study's null findings on
hospital mortality suggests that either medical emergency teams
have no effect on mortality or are being poorly implemented in
the real world. These issues are discussed in an accompanying
editorial by Joshua Koch and Sandeep Das from UT Southwestern.


                                               
The next study tells us that carotid stent fractures are not
associated with adverse events. First and corresponding author,
Dr. Weinberg from Massachusetts General Hospital and his
colleagues reported the stent fracture rate and its association
with instant re-stenosis and adverse outcomes in the Asymptomatic
Carotid Trial 1, which was a prospective multi-center trial of
standard surgical risk patients with severe asymptomatic carotid
artery stenosis randomized to carotid artery stenting or carotid
endarterectomy. Stent fracture occurred in only 5.4% of patients
and there was no association between stent fracture and in-stent
re-stenosis or with the primary endpoint, which was a composite
of death, stroke or myocardial infarction during the 30 days
after the procedure or ipsilateral stroke during the 365 days
after the procedure.


                                               
These findings suggest that routine surveillance for carotid
stent fracture may be unnecessary and, if a fracture is
identified in an asymptomatic patient, intervention may rarely be
required.


                                               
Heart rhythm disorder management procedures are increasingly
being performed and the next paper tells us important information
on mortality and cerebrovascular events following such
procedures.


                                               
Co-first authors Lee and Ling, corresponding authors Dr. Mulpuru
and colleagues from Mayo Clinic in Phoenix, Arizona, performed a
retrospective cohort study of all patients undergoing heart
rhythm disorder management procedures between 2000 and 2016 at
the Mayo Clinic from all three campuses in Rochester, Phoenix and
Jacksonville. Among almost 49,000 patients undergoing a total of
above 62,000 procedures, the overall mortality and
cerebrovascular event rate was 0.36% and 0.12%, respectively.
Lead extraction procedures had the highest overall mortality of
0.21% and the highest cerebrovascular event rates at 0.62%.
However, most of the deaths and cerebrovascular events occurred
after device implantation procedures due to the sheer volume of
device implantation procedures, which represented 48% of all the
procedures performed.


                                               
The most common cause of death directly related to these
procedures was cardiac tamponade, being responsible for 40% of
all directly related deaths. This highlights the importance of
development of protocols for quick identification and management
of cardiac tamponade, even in procedures typically believed to be
of lower risk such as device implantation.


                                               
And that wraps it up for our summaries this week. Now, for our
feature discussion.


                                               
Lipid testing plays a major role in our day-to-day management of
our cardiovascular patients and fasting samples have long been
the standard for assessing LDL cholesterol and triglycerides
since fasting is believed to reduce the triglyceride variability
and allow for a more accurate derivation of the commonly used
Friedewald calculated LDL cholesterol. Well, I think that's an
assumption we have taken for granted, I mean, since 1972 when the
Friedewald calculation was first proposed, but in this day and
age, several clinical guidelines from Europe, Canada and the US
have now recommended non-fasting lipid testing for routine
clinical evaluations and it's time to re-evaluate perhaps the
Friedewald LDL or other methods for determining LDL.


                                               
Today's feature paper addresses this issue spot-on and we're
thrilled to have with us the corresponding author of a very
important paper and he is Dr. Seth Martin from the Johns Hopkins
Ciccarone Center for Prevention of Cardiovascular Disease and we
also have with us Dr. Anand Rohatgi, associate editor from UT
Southwestern. Welcome, gentlemen.


Dr. Anand
Rohatgi:         
Thank you, Carolyn.


Dr. Seth
Martin:               
Thank you.


Dr. Carolyn
Lam:              
Seth, that was a super-long lead up from me, but I just find your
paper so intriguing. Could you please paint the background of the
idea behind your paper today and the rationale for questioning
the Friedewald equation?


Dr. Seth
Martin:               
Yeah, my pleasure. This was the first paper to look at directly
fasting versus non-fasting using our new algorithm. To give a
little background on the algorithm, we had recognized that the
Friedewald equation, which had been the standard for decades as
you mentioned, would really become problematic in the setting of
low LDL concentrations. In fact, Dr. Friedewald himself and his
co-authors said that in their original publication in 1972
because what's subtracted out is the LDL cholesterol and it's not
a particularly accurate estimate by their equation, but at the
time, it was viewed as acceptable because the concentrations of
LDL weren't all that low.


                                               
Now, in the modern era, things are different. We treat the lower
LDL. We're lucky to have new drugs that allow us to achieve low
LDL levels and meanwhile we have many more patients with obesity
and diabetes, leading to higher triglyceride levels, so this all
means that that estimated component of the equation becomes a
bigger part of the equation and that's what spurred us on to say,
"Well, cane we estimate that better?" And we were very lucky to
have access to a huge data set that had over a million patients
and had directly measured VLDL cholesterol as well as
triglycerides, so that allowed us to really more specifically
address this estimated component of the equation.


                                               
To just give the brief details on what the equation does, is we
take the original Friedewald equation from what I view is a
one-size-fits-all approach where we divide triglycerides by 5 in
milligrams per deciliter and now we just match the patient based
on their lipid profile using the same data as the Friedewald
equation with the more personalized factors, so taking it from
one size fits all to a more precision or personalized fit and
it's one of 180 different factors that the patient may get
matched with and what we've found is that this type of approach
is more flexible, so it's going ... as patients triglyceride
levels go up in the setting of low LDL and as they go into
non-fasting states, this type of approach can adapt to that
better and provide a more reliable, accurate estimate of LDL
cholesterol.


Dr. Carolyn
Lam:              
That is so cool. It really is. It just makes so much sense in
this day and age of proceeding towards personalized medicine, to
make sure we apply equations that are personalized, so your paper
essentially shows that applying this new equation works better
than the traditional equation, particularly in the non-fasting
states, right? And for states of low LDL cholesterol or perhaps
high triglycerides. Would that be a good summary?


Dr. Seth
Martin:               
Yeah, that's a great summary and this paper ... I'm really lucky.
It was led by one of the fantastic Osler medical residents,
Vasanth Sathiyakumar, who is going to be a future star in
cardiology, I believe, and he did a great job leading our paper,
which shows that in the non-fasting state, what happens is
triglyceride levels are higher and this means that the Friedewald
equation becomes less accurate and I think this has been a little
bit overlooked in recent trends where there's been a big push to
do more non-fasting lipid profiles, which really is great for
patients, more convenient and it makes a lot of sense, but we
have to be also, in an era of precision medicine, getting precise
data and if we're going to be making clinical decisions based on
LDL concentration, we want to make sure we have good information
there and what our paper shows is that there should be some level
of caution when using non-fasting Friedewald LDL at low levels,
but our new algorithm does provide a more robust estimate in that
setting.


Dr. Carolyn
Lam:              
Anand, this is begging for the question, "What do you think are
going to be the practical implications of this very important
paper?"


Dr. Anand
Rohatgi:          I
think the clinical implications are huge and I think that's why
we were so excited when we received this, that sort of the
potential impact was there. I can tell you personally my clinic
is in the afternoon and so it's a struggle to try to get patients
to get fasting lipid levels and often they can't do it when
they're coming to see me and so the importance of non-fasting
lipid levels is clear and what Seth's group has done is showed
that we can actually accurately estimate the LDL levels. A lot of
people struggle with trying to still calculate the non-HDL levels
and, as Seth pointed out, oftentimes when you're non-fasting, the
triglyceride levels are higher and the calculated LDL from
Friedewald is artificially low, so it's very hard to combine the
convenience of just looking at the lipid levels and having sort
of a confidence in the actual calculated LDL, so in this case
clinicians can have their patients get their lipid levels at any
time and with this algorithm that's already being used by major
laboratory services will have relatively high confidence that the
LDL that they see is very accurate and then they can make a
decision based off of that and they can counsel in real time
based off of that, so it really changes the ability to engage
with patients at any time and is not restrictive.


                                               
I can tell you many patients sometimes won't even get their lipid
levels for weeks just because they can't arrange for it to be
done on a fasting state and so this really liberates patients and
it really enhances the doctor-patient relationship, I think.


Dr. Carolyn
Lam:              
I agree, Anand. I like that word that you used, "liberate" the
patient. Honestly, I think some of my patients cheat a little too
and they don't really fast as they should before their fasting
lipids and this is going to be incredibly helpful.


                                               
I have a couple of questions for you, though, Seth. In terms of
understanding the limitations of what you may have tested in the
current study, we all know that with triglycerides in the
super-high level of more than 400, for example, the Friedewald
equation breaks down. Did you test this with the new equation
because I think you excluded this group as well in the current
study, did you not?


Dr. Seth
Martin:               
That's correct, yes. Traditionally, the Friedewald equation has
excluded folks from calculation who have triglyceride levels, as
you said, of 400 milligrams per deciliter or more and the reason
for that is that's the setting where chylomicrons are more likely
to be present and therefore we're trying to estimate VLDL
cholesterol and it wouldn't make sense to do that if there's a
lot of triglycerides and chylomicrons.


                                               
That being said, we did look at this previously and found that in
that setting our equation works quite a bit better than
Friedewald, but it's still inaccurate I would say about a third
of the time due to the presence of chylomicrons, so it's an area
where we should certainly be more cautious in estimating LDL
cholesterol if the triglycerides are that high, but honestly in
that setting, often the clinical priority is going to revolve
around triglyceride lowering and the LDL may not be the most
immediate priority for clinical treatment.


Dr. Carolyn
Lam:              
And then just another question, recognizing that our podcast is
heard throughout the world, in this day and age of precision
medicine, how about accounting for potential ethnic differences,
possibly? Did you account for differences in race, gender perhaps
in these equations?


Dr. Seth
Martin:               
What we found is that this really is a lipid-dependent phenomenon
in terms of the ratio of triglycerides to VLDL in estimating LDL.
We previously looked at age and sex and found that they
contributed very, very little information to actually explaining
this ratio and so I think that it is something that's likely
going to be preserved across different demographic groups. I can
say to our listeners in places ... in Asia that the equation has
been validated over there and so there's some reassurance that
even around the world and other places like Brazil, that it is
holding up, so I think that largely this is going to be dependent
on someone's lipid profile and it is quite simple in that regard,
that we don't have to likely worry about too much differences
between men, women, older, younger or different ethnicities.


Dr. Anand
Rohatgi:          I
have a question for Seth. As we mentioned, this is an
international audience and guidelines do differ on their emphasis
on lipid targets now as everyone is aware, some still emphasizing
them and others, like the American guidelines, de-emphasizing
targets, so Seth, the question i had for you is based off of your
work. Where do you see that fitting in with how the different
guidelines and societies are trying to emphasize or de-emphasize
lipid targets.


Dr. Seth
Martin:               
The amazing thing is we're all ... really have access to the same
data. We've worked together throughout the globe to generate
clinical trial evidence that guides us as well as all sorts of
other type of evidence to guide us in clinical practice, so just
on a very broad conceptual level, my hope is that over time with
the great exchange of information around the world that we're
going to converge more on consensus recommendations and then, of
course, there may be needs to adapt those recommendations to
different cultures and that can be taken into account, so I'm
hoping there'll be a push towards more consensus and as we get
our updated American guidelines, it's looking like this upcoming
year, I hope that we come into even more harmony with the rest of
the world.


                                               
I think for a long time we've had this LDL goal in many different
guidelines as less than 70, so that's part of the reason our work
has focused on that level. The European guidelines have a target
level for high-risk patients of less than 70 for LDL and I think
what we saw in the recent consensus document on non-statins from
the American College of Cardiology was a push to be thinking at
that level when the LDL is 70 or above as a time to have a
clinician and patient discussion about whether we should be
intensifying therapy, so I guess would say the guidelines in my
view, and Anand I would be curious of your view, are more alike
than different, but I hope they become even more in harmony
because really we're all basing our decisions on the same
evidence base and I think it can be a bit confusing when we have
disparate recommendations.


                                               
The same can be said for the issue of recommendations for fasting
versus non-fasting guidelines, which have not been harmonized
either, but Anand I'd be curious to your thoughts as well on this
topic.


Dr. Anand
Rohatgi:          I
would agree with you. I think they're more alike than different.
It's just what may be the high level sort of things have come out
to the lay public and others, but I agree with you. If you really
read them, they're emphasizing risk reduction by the therapies
and by controlling the risk factors, in particular the lipid
levels, so I think that's where your work is really important and
insightful and I think will be incorporated in all of the
respective guideline revisions.


Dr. Carolyn
Lam:              
I completely agree and we're so proud to be publishing your
excellent work in circulation. Thank you, Seth. Thank you, Anand.


                                               
Thank you, listeners, for joining us today. Don't forget to tune
again next week.