Manage episode 177723435 series 1097738
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 this week really adds to our understanding of the cause/effect relationship between obesity and heart failure, this time by comparing the effects of gastric bypass surgery versus intensive lifetime treatment on heart failure risk. Before we talk about that, though, let me give you your summary of this week's journal.
The first paper brings us one step closer to understanding cardiac recovery in response to mechanical unloading by left ventricular assist devices and it does this by showing that this process may involve the transverse tubular system, which is a micro structural feature of ventricular cardiomyocytes important for contractility and consisting of tubular invaginations of the sarcolemma predominantly located at the Z-lines of sarcomeres. This transverse tubular system is crucial for efficient excitation contraction coupling by bringing L-type calcium channels in the sarcolemma in proximity to clusters of ryanodine receptors in the sarcoplasmic reticulum.
In the current study by co-corresponding authors, Dr. Seidel and Drakos and Sachse from University of Utah, the authors studied left ventricular biopsies obtained from five donors and 26 patients with chronic heart failure undergoing implantation of left ventricular assist devices or LVAD's. They used three dimensional confocal microscopy and computational image analysis to assess the transverse tubular system's structure, density, and distance of ryanodine receptor clusters to the sarcolemma.
They found that the majority of heart failure myocytes showed remarkable transverse tubular system remodeling, particular sheet-like invaginations of the sarcolemma, which is previously unknown phenotype. This sheet-like transverse tubular system remodeling led to increased distances of ryanodine receptors to the sarcolemma causing heterogeneous intracellular calcium release and consequently inefficient excitation contraction coupling. High degrees of transverse tubular remodeling at the time of LVAD implantation was associated with absence of functional cardiac recovery during mechanical unloading, whereas preserved transverse tubular systems structure was associated with recovery.
In summary, cardiac recovery during unloading may require an intact transverse tubular system at the time of LVAD implantation. And characterizing this system may help to identify patients with a high probability of functional cardiac recovery in response to mechanical unloading.
There have been a proliferation of algorithms based in high sensitivity assays for cardiac troponins for the diagnosis or exclusion of myocardial infarction. All these algorithms have the potential to overwhelm clinicians with options. Well, there is help in this week's issue with two observational studies directly comparing the diagnostic performances of multiple high-sensitivity troponin testing strategies.
Now, before I describe these two studies in detail, here are some important reminders. Remember that as of early 2017, although high-sensitivity troponin assays are routinely used in many regions of the world, they are not available in the United States. Thus, the specific algorithms discussed here are not applicable with the contemporary sensitive assays that are presently used in the United States. Next, let's remind ourselves that both the United States and European professional guidelines recommend serial measurement of cardiac troponins at presentation or zero hours and three to six hours later with additional testing beyond six hours in patients who have electrocardiographic changes, or intermediate or high clinical risk features.
The 2015 European Society of Cardiology Guidelines also included an alternative strategy reducing the sampling interval to one hour when using a high sensitivity troponin assay with a validated zero and one hour algorithm based on the 99 percentile cutoff of these high sensitivity troponin assays. Now to the two studies in the current issue, which tie together the expanding evidence with direct comparisons of several of the strategies using the same high sensitivity cardiac troponin assay by Abbott.
Dr. Chapman and colleagues from the royal infirmary of Edinburgh, United Kingdom, compared the standard ECS zero and three hour strategy based on the 99th percentile upper reference limit at both time points with the high sensitivity troponin in the evaluation of patients with acute coronary syndrome, or high stakes algorithm, and that would be a zero, three, and six hour algorithm that incorporates a zero hour criteria and at a very low cutoff of five nanogram per liter and a three hour criterion that directs patients with either a rising concentration or with an absolute concentration above the upper reference limit to additional testing.
Among 1,218 patients with suspected myocardial infarction, the high stakes algorithm delivered both a higher proportion ruled out for myocardial infarction at zero hours and a higher negative predictive value of 99.5% versus 97.9%. The ESC pathway missed 18 index and two recurrent myocardial infarction events, whereas the high stakes pathway missed two index and two recurrent myocardial infarction events. These findings demonstrate the value of adding a very low zero hour cutoff to facilitate earlier rule out as well as the value of a delta criterion to exclude increasing values among patients that progress to three hour sampling.
In the next study, first author, Dr. Boeddinghaus, corresponding author Dr. Mueller and colleagues from University Hospital of Basel, Switzerland compared the ESC alternative zero and one hour strategy with three other approaches using either a single cutoff at zero hours, or the one hour strategy. Among 2,828 patients with symptoms suspicious for myocardial infarction and no ST elevation, each of these four approaches delivered a negative predicted value above 99% comparing favorably to the ESC zero and three hour algorithm that had a negative predictive value of 98.4%.
Now, although each of the strategies performed similarly among patients presenting more than two hours after symptom onset, among the early presenters, the negative predictive value and sensitivity were diminished using the single zero hour cutoff of five nanograms per liter. The authors concluded that the single cutoff strategy, the one hour algorithm, and the zero and one hour algorithm, allow the triage towards rule out of myocardial infarction in more than half of consecutive patients presenting with suspected MI to the emergency department. However, the single cutoff strategy should not be used in patients presenting early after chest pain onset.
These papers are discussed in an excellent editorial, which also puts everything in perspective by Dr. David Morrow from Brigham and Women’s Hospital in Boston, Massachusetts. I particularity want to refer all of you to the figure that's found in its editorial which really helps you to understand the different strategies involved.
The final study tells us about potential death averted and serious adverse events occurred from the adoption of the SPRINT intensive blood pressure regimen in the United States. As a reminder, the systolic blood pressure intervention trial, or SPRINT demonstrated a 27% reduction in all caused mortality with a systolic blood pressure goal of less than 120 versus less than 140 mm Hg among American adults at high cardiovascular risk, but without diabetes, stroke, or heart failure.
In the current study, Dr. Bress and colleagues from the University of Utah School of Medicine applied the SPRINT eligibility criteria to the 1999 to 2006 National Health and Nutrition Examination Survey or NHANES and linked this with the national death index through December, 2011. They found that if fully implemented in eligible US adults, intensive blood pressure treatment was projected to prevent about 107,500 deaths and 46,100 of heart failure per year. But, you also give rise to about 56,100 episodes of hypertension. 34,400 episodes of syncope, 43,400 serious electrolyte disorders, and 88,700 of acute kidney injury per year compared to standard blood pressure treatment. Thus, they take home message is careful patients selection and implementation are important because intensive treatment while preventing deaths is associated with increased risks of hypertension, syncope, electrolyte abnormalities and acute kidney injury.
Well, that brings us to a close for the summaries, now for our feature discussion.
We are discussing obesity and heart failure. Now, we've heard of the obesity paradox, but we also know that obesity may be a risk factor for heart failure and the study today really puts perspective on this and is really one of the largest most convincing studies I've read on this topic. I am so pleased to have the person corresponding author, Dr. Johan Sundstrom from Uppsala University Hospital in Sweden. Welcome, Johan.
Dr Johan Sundstrom: Thank you, lovely to talk to you.
Dr Carolyn Lam: And especially pleased to have back on the show again, Dr. Torbjorn Omland from University of Oslo, Norway. Hi, welcome back, Torbjorn.
Dr Torbjorn Omland: Thank you very much. It's a great pleasure being here.
Dr Carolyn Lam: Johan, you know what? Could you just start by telling us about your study?
Dr Johan Sundstrom: So, we were fortunate enough to have two great databases here in Sweden. One was the obesity surgery registry called SOREG in which all people have a gastric bypass surgery, for people who are registered. And we also have a company called Itrim who provide intensive lifestyle program, which takes people down on average about 11 kilos, and they have a very structured database as well. So, we were able to pull this data in order to try and understand the effects of intentional weight loss to two different levels of weight loss, what that does to the heart failure incidence.
This is a bit of a comparative effectiveness study, so it's of course necessary to make the examples as similar as possible to apply exclusion criteria. We took away everyone who had a body mass index of less than 30 and above 50 and then we applied propensity scores to those two data sets and we had to trim the data sets a little bit further in order to get so called region of common support, which means that we were left with two samples who could have either had surgery or a lifestyle intervention. And then we applied an inverse probability weighting scheme to that. It's statistically complicated but what that does, is it's a matching, but it's not as complicated as matching. With matching, you just give people a weight of 1 or 0, but this gives people other weights as well.
So, we end up with characteristics that were very similar at baseline. So, we tried to mimic as close as possible what a randomized clinical trial looks like, but of course we did it posthoc and it’s observational. So, we get our table one, sort of, in this paper that shows very similar characteristics of the two groups. So, what we did then is we noted what happened to the people in these two groups in terms of heart failure incidence and we followed them in our national inpatient registry. So, all the Swedish citizens get a personal identification number so we can use that to follow people in our patient registry. So, we know exactly what drugs people will collect from pharmacies, and we know what they died from, and we know all of their hospitalizations. And we previously validated their heart failure diagnosis in the Swedish Inpatient Registry and we noted that you were in a pretty good position if you were hospitalized with heart failure as the main cause of hospitalization and we noted that people who had agreed to do surgery, had about half the incidence of heart failure than people who were in the intensive lifestyle program.
We also noted, if you looked at the achieved weight loss one year after baseline, we noted that a ten kilo weight loss after one year was related to about a 23% lower risk of heart failure. So we noted a litany of association between the achieved weight loss and heart failure incidence. It should said, though, that heart failure in this age group, they are only 41 on average, 41 years old. Heart failure's still very unusual at this age, even in many of these people. We only had 73 cases of heart failure. So, the exact numbers need to be taken with a pinch of salt and have wide confidence intervals around them.
Dr Carolyn Lam: Johan, this is exactly why I'm so impressed with your data. First you showed a dose response relationship between the weight loss and risk of heart failure. You also show that it's not an event that occurs very often and so, it would be very difficult to imagine doing a randomized controlled trial for example in this setting and having to wait very long for these events. So, it really goes to show your observational data are extremely important. And I really like the way you took the pains to describe how you tried to overcome the differences that exist between the groups and try to make it as much resembling a randomized trial setting as you could. So, maybe I could turn it over to you, Torbjorn. Could you tell us what you think the implications of this paper are?
Dr Torbjorn Omland: First, I will say that that this paper has all the characteristics of a very high quality study. It's a very timely topic that interests a lot of people. The paper's very well written. It's a large sample size as you said and it was very clinically meaningful difference between the groups and that translated into very clear and robust answers. So, I think that this has every mark of high quality paper.
But, of course, the very important question is how will this translate into actions? How can we use this information to prevent problems? We know heart failure is a very prevalent disease, especially in the elderly and although the incidence was lower here, I think my question for Johan at least is what would be the next step? What changes can we implement to reduce heart failure among the obese?
Dr Johan Sundstrom: That's a great question. I think in this study puts a little piece of the puzzle on the table and that's trying to add a little more evidence towards a causal association between obesity and heart failure. I'm not sure about what we can offer these patients and what will be the translation to lower heart failure incidence in the long run. Of course, we need to follow this sample for longer to have more heart failure cases, because I don't think we've seen the full impact of weight loss in these two samples. We might need to follow them into older age where they would have a higher heart failure incidence.
But, how to tackle obesity, I think we'll need accommodate population strategies and high risk strategies. I think if the general consensus in the scientific community after reading this and other important papers, is that there's causal link between obesity and heart failure, then we might need to understand that people who are obese and who have shortness of breath and perhaps swelling or what not, may not just be having low fitness, they might actually behaving signs of heart failure.
So, I think as a sort of increased diligence on heart failure, these people might be one thing. But, we didn't really study that. So, I wouldn't draw conclusion. But, otherwise I think it's more of a causal inference piece of the puzzle that we've laid rather than a clinical care piece of the puzzle.
Dr Torbjorn Omland: No, I agree, and here you won't to make any recommendations in regards to what interventions you should recommend particularly based on this particular study.
Dr Johan Sundstrom: No, because I think there are so many other things that need to be taken into account when it comes to treatment of obesity. Heart failure is actually one of the uncommon outcomes in this age group. We're looking at other outcomes after they present. Myocardial infarction, ventral fibrillation and mortality are actually much more common. So, I think a lot of other data should go into decisions on how to treat patients, not just for heart failure, which is still fairly uncommon at this age.
Dr Carolyn Lam: Going back to the other question that Torbjorn asked, do you think that this question still needs to be answered in any way? You've got the Mendelian randomization data. Now, you've got your data. Do you think it's still a question of whether obesity is a risk factor for heart failure? And just in case there's any confusion out there, would you put that together with the so called obesity paradox in heart failure?
Dr Johan Sundstrom: To answer the first one, I think we're not going to have any randomized evidence. Treatment of heart failure with intensive programs and prevention of heart failure ... It needs for huge samples that I don't think we're going to have any much better observational evidence anytime soon either. So, we can probably set that question aside a little bit. But, when it comes to the obesity paradox, first of all that's not what we studied here. We didn't have anyone with heart failure in this sample. We included all those people. We can only speculate. I'm a clinical epidemiologist myself, but I'm envious of people who have animal and other models because I think there's a lot more work to do in terms of ppars and and lipid metabolism in obesity and in heart failure. So, I think there'll be more interesting experimental research to come that can help us answer the obesity paradox.
Dr Carolyn Lam: Please don't forget to tell your friends about this podcast, and tune in again next week.
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