Mar 20, 2017
Dr. 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. In this week's issue, we are discussing if public placement of defibrillators in the community can be improved. First, here's your summary of this week's Journal.
Stroke incidents, prevalence, and risk factors have been changing over the past 50 years so do we need a more contemporaneous revised Framingham Stroke Risk profile to reflect these trends? Well the first paper in our issue looks at this and this is from first author Dr. Dufouil, corresponding author Dr. Seshadri and colleagues from the Boston University School of Medicine.
Let's first recall that the Framingham Stroke Risk profile was originally described in 1991 and integrates the effect of age, sex, and baseline measurements of various vascular risk factors such as systolic blood pressure, use of anti-hypertensive medications, left ventricular hypertrophy on ECG, prevalent cardiovascular disease, current smoking status, atrial fibrillation and diabetes all to describe the 10-year probability of incident stroke.
In the current paper, the authors updated the Framingham Stroke Risk profile using the means of risk factors that reflect current prevalence, the estimate of incident stroke to reflect current rates, and the hazards ratio that reflect current associations. They used the same risk factors identified in the original stroke risk profile with the exception of left ventricular hypertrophy. The authors compared the accuracy of the standard old risk profile with the revised new risk profile in predicting the risk of [alt 00:01:58] and ischemic stroke and validated the new risk profile in two external cohorts, the three cities and regards or reasons for geographic and ethnic differences in stroke studies.
They found that the new stroke risk profile was a better predictor of current stroke risks in all three samples than the original old Framingham Stroke Risk profile. The new stroke risk profile was also a better predictor among whites compared to blacks in the regard study. The authors therefore concluded that a more contemporaneous revised Framingham Stroke Risk profile could serve as the basis for examining geographic and racial differences in stroke risk and the incremental diagnostic utility of novel stroke risk factors.
The next study provides preclinical proof of principle that an apelin receptor agonist may be of therapeutic use in pulmonary arterial hypertension. And the agonist in this case is Elabela/Toddler or ELA, first identified as an essential peptide in the development of the heart in Zebrafish, and subsequently proposed as a second endogenous ligand at the G-protien coupled apelin receptor, which works at this receptor despite a lack of sequence similarity to the established ligand, apelin.
In this study from first author Dr. Yang, corresponding author Dr. Davenport and colleagues from University of Cambridge in the United Kingdom, ELA competed for binding of apelin in human hearts with overlap of the two peptides indicated by encyclical modeling. ELA activated G-protein and β-arrestin dependent pathways and as expression was detectable in human vascular endothelium and plasma. Comparable to apelin, ELA increased cardiac contractility, ejection fraction, cardiac output, and elicited vasodilatation in rats in vivo.
ELA expression was reduced in cardiopulmonary tissues from patients with pulmonary arterial hypertension and in rat models. Finally, ELA treatment significantly attenuated the elevation of right ventricular systolic pressure, right ventricular hypertrophy, and pulmonary vascular remodeling in monocrotaline exposed rats. Thus, these results suggest that a selective agonist that mimics the action of indulgence ligand apelin or Elabela/Toddler, ELA, may be a promising therapeutic strategy in the treatment of pulmonary arterial hypertension.
The final paper looks at sudden cardiac death after coronary artery bypass grafting, its incidents, timing, and clinical predictors. First author Dr. Rao, corresponding author Dr. Velazquez and colleagues from Duke Clinical Research Institute in Durham, North Carolina, looked at the patients enrolled in the STICH, or Surgical Treatment of Ischemic Heart Failure Trial who underwent coronary artery bypass grafting with or without surgical ventricular reconstruction. They excluded patients with a prior ICD and those randomized only to medical therapy. Over a median followup of 46 months, 113 out of 1,411 patients who received coronary artery bypass surgery, had sudden cardiac death while 311 died of other causes.
The five-year cumulative incidence of sudden cardiac death was 8.5%. In the first 30 days after bypass surgery, sudden cardiac death accounted for 7% of all the deaths. The numerically greatest monthly rate of sudden cardiac death was in the 31 to 90 day time period. In multivariable analysis end-systolic volume index and BNP were the most strongly associated with sudden cardiac death. Thus, this study shows that the monthly risk of sudden cardiac death shortly after bypass surgery among patients with a low ejection fraction is highest between the first and third months, suggesting that risk stratification for sudden cardiac death should occur early in the post-operative period, particularly in patients with an increased preoperative end-systolic volume index and/or an increased BNP.
Well, that wraps it up for you summaries, let's turn to our feature paper.
I love our feature paper this week. You know why? It actually tells us what Tim Hortons, Starbucks, Second Cup and ATMs may have in common and may have to do with sudden cardiac death. Indeed, our feature paper actually tells us that coffee shops and ATMs may be the best spots to place AEDs at, well at least in Toronto. And to discuss this really interesting paper, I have the corresponding author, Dr. Timothy Chan from University of Toronto as well as Dr. Sana Al-Khatib, welcome again Sana, Associate Editor from Duke University, welcome to you both.
Dr. Al-Khatib: Thank you, my pleasure.
Dr. Chan: Thank you, very nice to be here.
Dr. Lam: So Tim, was that an interesting enough lead up? I mean you have to tell us about your study, it is so fascinating.
Dr. Chan: I'm very pleased that you find it interesting and not just us. So we undertook this study, we started this actually a couple of years ago, and we've been working on this issue of defibrillator location optimization for several years, and we've been talking and we have meetings in coffee shops and we were just wondering one day, what would be the risk or the coverage provided by all these different well-recognized location types around the city, and that was really the motivation that got us started looking at this study.
Dr. Lam: Tell us what you did and also how it differs from the study you did that was published in 2016 where you also reported on the spatial temporal analysis of registered AEDs in Toronto. The current study clearly extends it, but could you clarify to us all how it does?
Dr. Chan: Maybe just give a little bit of a background and context with regards to other literature that's similar. There have been studies in the past that looked at what we would call spatial coverage of cardiac arrest, so they looked at different broad location types and they tried to calculate, they basically calculated how many cardiac arrests happened, let's say within 100 meters of those location types. And what we've done here is we've extended that in a couple of directions. The first direction is looking at spatial temporal coverage and so this is not just in the nearby vicinity, IE, 100 meters, but also that cardiac arrests happen when that nearby location that had the AED was open. So if a cardiac arrest happens, but for example, let's say there's a coffee shop that actually has an AED and that coffee shop is closed, it's almost as if that AED is not even there. So one of the major things we made sure to include was this idea of temporal coverage as well, on top of the spatial.
The second major difference I would say would be the fact that we're really looking at more granular location types, so you mentioned a few businesses in your opening such as Tim Hortons and Starbucks and so on, which are coffee shops, and so one of the things that we find is when we look at very broad location types, we tend to aggregate together lots of different types of businesses. For example, if you think about a restaurant, there are many different types of restaurants that get lumped in to this category, and they do have different cardiac arrest coverage associated with them. So by breaking it up into smaller location types, we wanted to get a better idea of the risk at different locations and if you also think about one of the long term goals of this work would be to try and help policy makers identify promising partners to partner with for, let's say public access defibrillation programs, by identifying specific businesses or municipal locations, it might actually give them better targets to try and pursue rather than let's say a group of different businesses.
Dr. Lam: That makes so much sense and it really just seems like such an important public health message as well. The sensible part being of course, if you have an out of hospital cardiac arrest, you need an AED that's both nearby and available, so that was really clever. Sana, could you give us your take on the public health implications of Tim's findings?
Dr. Al-Khatib: I think the public health implications of this work can be vast and if you look at what he's done in terms of ascending to out of hospital cardiac arrests a lot of initiatives have been launched to try to improve the outcomes of patients who have the out of hospital cardiac arrests. Unfortunately despite all the work that has been done and all the wonderful initiatives that have been launched, we still have a lot of work to do to improve the survival of those victims. So certainly a crucial step is how we deploy AEDs in a strategic way based on data and evidence such as these data that are provided to us by Tim and his colleagues.
I think this is very clever, I do agree that we have to be more strategic in how we deploy AEDs and having the data such as these will only help us improve and get better of course. Everybody has limited resources, and so if we can be more selective in terms of how we deploy AEDs I think that would help everybody. I realize this was done within Toronto and some of these findings may not be generalizable to other cities, but I think this is definitely a great way to make us reshape our thinking in terms of how we do this, and so a question I have for Tim if I may, are you aware of any similar studies that have been done looking at this in other cities and then if not, how do we encourage other groups to do similar work?
Dr. Chan: There have been similar studies done that have focused really on the spatial side of things, so doing this 100 meter radius and counting cardiac arrests that have been nearby, there's actually been fairly little work that's been done on the spatial temporal side. And a couple of exceptions that I will note that I think are important to point out is there was a very nice study that was done out of a group in Copenhagen, and they were looking at actually spatial temporal coverage, particularly the loss in coverage that you experience when you go from looking at spatial to spatial temporal. For example if you count all of the cardiac arrests that happen nearby a registered AED based only on 100 meters, and then you count the same number, but you have to now layer on top of that when the building that the AED is in is open, then you tend to get a big loss. They found quite striking numbers, I think they found a 50% loss, when you look at evenings and weekends I believe, in Copenhagen. So basically all the cardiac arrests that happened where you thought there was an AED nearby, there's actually only one in two is actually nearby and accessible when you looked into hours of operation.
And this actually comes back to the earlier question from Carolyn about how our study relates to our previous study in 2016, so we actually replicated that Copenhagen study in Toronto where we measured spatial coverage and we measured spatial temporal coverage and we measured that loss, and we found a similar loss overall, about 20%, so 1 in 5 cardiac arrests happened where there was an AED nearby, but that AED was not available because that location was closed. So that was one of the impetuses for leading us to do this study where we start to examine specifically the different location types and the specific businesses that were involved.
Dr. Lam: Wow, that's just really inspiring Tim, I mean I'm kind of thinking about the Singapore situation too and I think it's actually applicable and I would love if we had local data similar to yours, so congratulations, I really share what Sana said. Thinking though about the public health and the larger implications of what you're talking about, what do both of you think of the implications for a public commercial partnership in these things if it is coffee stores or banks that seem to be the best locations, perhaps these have implications to how the public and private should collaborate to make these things happen, what do you think?
Dr. Chan: I completely agree. These types of public private partnerships, specifically for AED deployment are not necessarily new, they already happen in some parts of the world. One of the examples I always like to bring out is if you go to Japan and they have vending machines everywhere in Japan and then you'll often run into vending machines that have an AED right in them, so one of the benefits is that first the vending machines are everywhere and second, if you're a citizen there, you probably know where the vending machines are where you travel in your day to day life and so I would say that would be a very similar thing here in North America, whether it be coffee shops or ATMs, if someone were to put me in a random part of the city and ask me, "Hey Tim, do you know where the nearest AED is?" I'd probably have a lot of trouble, but if they said could you figure out where the nearest ATM is for your bank or where the nearest Starbucks is you know, there's pretty much one on every corner. It would be much easier to identify and find, so I think there are significant benefits to partnering with these companies or these businesses that have very broad name recognition and brand recognition, are geographically well spread and located in populated areas.
I should also mention, I feel like there's a few other benefits for these types of locations, so for example for ATMs, I think there's a lot of secondary benefits, so for example, there's a built in security component, there's a video camera there, that might be able to help make sure that no one's vandalizing or stealing an AED. There's perhaps built in weather protection because there's electricity there already, so in a cold climate like Toronto where you might worry about putting an AED outside, you could have potentially a heating cabinet that would be fed by the electricity for the ATM and so on. So I think there's actually a lot of benefits if we could actually operationalize a system like this.
Dr. Lam: Sana, do you think there are some more unanswered questions?
Dr. Al-Khatib: I did want to agree with Tim on what he said, that these public private partnerships have been in place. Unfortunately we haven't been able to make much progress. As I said, I do see the results of this study as being potentially a catalyst to improve the work that we are doing and ensuring stronger partnerships and collaborations to help us achieve what we want to achieve which is basically improve the survival rate of out of hospital cardiac arrests, so I completely agree with that and I loved your idea, Tim, when you talked about now people may not recall where AEDs might be, but if you link them with teller machines or coffee shops, I think that would be much easier to remember.
You know of course there are a lot of questions that remain unanswered unfortunately. Again as was stated by Tim and his colleagues in the paper and on the call, how we can translate these findings to other locations I think is really key and then of course doing the work, meaning let's use these data to deploy more AEDs and then really looking at the impact of that. Ultimately we want to make sure that if we hypothesize that by doing this we can improve outcomes for these victims, we would want to prove that. So I think the next steps would be to see if this can be replicated in other places, but also even within Toronto, if we can accomplish some of this and then examining the impact, I think would be extremely beneficial.
Dr. Lam: Fabulous, thank you so much Sana, thank you so much Tim for sharing your thoughts today.
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