 Hello, everybody. I'm Michael Castro. I'm an internist in Glenda, Arizona. I'm associate program director for a bra. So I am program and right now I'm going to introduce Dr. Vikram Singh. I didn't know that he is a PY2 residence is near and dear to my heart, you know, the residence. So he's a graduate of Chicago Medical School and he's interested in cardiology, obviously advanced heart failure and cardiac imaging. Welcome. What an extremely tough act to follow. Hi, everybody. My name is Vikram today. I'm going to be talking about utilization of evidence based cardiac amyloidosis screening and at risk African American veterans. No financial interests or relationships to disclose. And this work just like to highlight that it was funded by Pfizer as a quality improvement grant awarded to Arizona State. And the contents of this presentation don't represent the views of the United States government or Department of Veterans Affairs. Just a bit of the agenda for this short talk. I'll be going through the project background the current state of affairs briefly in cardiac amyloidosis because I know we've been hashing that all day. Some of the missions and names of this project development of this project and how we used it and some of the outcomes that we can expect. Some of the barriers and challenges as well in future directions. We'd like to take this. So as we've been told earlier today and throughout our careers, the diagnosis of ATTR cardiac amyloidosis is often made fairly late in the disease course. If we look at this busy diagram here, we can highlight that There's an inverse relationship between the infiltration of TTR and functional status and quality of life. It takes a little bit of time for that functional status quality of life to decrease. But it's important to note that the existing treatments we have for amyloidosis are really focused on stabilizing that TTR and preventing disease progression. So if we don't catch it earlier enough, we're kind of out of luck. So we can really avoid significant morbidity and mortality that's associated with early diagnosis. There are some health disparities associated with this condition. In particular, African American individuals are at increased risk for ATTR cardiac amyloidosis. There is the wild type that they're, of course, at increased risk for with age, but they also have a genetic component. 4% of the United States African American population carry TTR substitution mutation valine-122 isoleucine, which is actually the most common disease associated variant. And data suggests that states that have higher African American populations also seem to have lower rates of diagnosis, which suggests under diagnosis. Social determinants of health play a large role in disease morbidity and mortality, not just in cardiac amyloidosis, but in heart failure in general. It's associated with delay in seeking care, limited disease awareness, an inability to recognize symptoms for what they are and then inequities in access, and of course, underrepresentation and research. Veterans themselves have their own unique and similar barriers to heart failure and ATTR cardiac amyloidosis care, rural location, homelessness, and then facilities that don't have advanced heart failure specialists. This table here kind of highlights some of the intersectionality in the disparities in healthcare of cardiac amyloidosis. We can see across these three institutions, which were involved in our project, Tucson, Greater LA, and Tampa, the total number of African American heart failure patients varied, but it seems that the proportion of these patients that are facing disparities in healthcare, rural location, homelessness, inaccessibility to a cardiologist, these numbers have fairly high proportions. It's important to note, though, these patients that don't have a cardiologist, they may have a community care cardiologist that they follow up with. And then a pretty astounding statistic is this African American heart failure patients that have greater than one amyloidosis risk factor, greater than 90% at all three institutions. And then if we look, measly numbers of patients that are on treatment. So what's the current state of affairs for us? You know, we've had recent publication of consensus guidelines, the Kittles and guidelines in 2023 that really highlights the condition fairly well, but still it's relatively under diagnosed. And this diagnosis is dependent on a few things, clinician experience and knowledge being one of them. A few questions that we have to ask when making the diagnosis. What clinical features are we looking for? What clinical data should we be looking at? What do we need to make the diagnosis? And what tools are available to kind of help us risk stratify? So if we don't have longitudinal history, if we don't have access to all of this data, diagnosis can prove challenging. So what we want to do is bridge the gap that we have between science and clinical practice. We have guidelines, we have all this research that tells us what we need to do. We need to figure out how to apply it. Why would we use the VA to study? It's really an ideal setting for translation of science because we have access to longitudinal records. We have data systems that can pull labs, imaging all the data we need from all over the country. So it provides this wealth of data just for us to use and kind of extrapolate risk. So to our project, what we wanted to do was enable early diagnosis of ATTR cardiac amyloidosis and African-American veterans. Like I was saying, we want to leverage these VA data systems and our up-to-date clinical guidelines to create a protocol that allows us to put out a dashboard with risk factors that make diagnosis easier for us. We also want to identify social determinants of health that are barriers to health care access as we know that increases morbidity and mortality. So like I was saying, we really sought to create or develop this screening dashboard. We wanted to have a tool that has all of that clinical information right in front of us to make informed decisions on screening. We wanted something that was easy to use, standardized, that could be repeated at other institutions. And we didn't want any strenuous requirements for data entry. We'll leave the AI and all of the big data stuff to people like my brother in the back. And we wanted to include all patients within the facilities that are African-American with heart failure between the ages of 18 and 90. This diagram just highlights our team. Please focus on the STARS, which is the institutions where our teams are located. Tucson, Great LA, and Tampa Bay. And we have our PIs at each institution, Dr. Dev, Dr. Warner, and Dr. Gilserbell. We had a multi-disciplinary team that included folks from social work, clinicians, and informatics. And our team was very diverse in gender, age, and expertise. So when we're developing this dashboard, we needed to say, what do we want on it? What kind of things are going to help us make this diagnosis? Using the most recent clinical guidelines, we were able to pull together all of the things we think should be included and would help us make the diagnosis. For example, we have labs. We have the BNP, troponin, S-pep, U-pep, light chains. And then imaging, PYP scan, cardiac MR. Long lists of comorbidities and risk factors that are associated with amyloidosis. You're probably not going to too often find a patient that has all of these things, but a collection of them can really help you push you in the right direction. For example, diabetes, autonomic dysfunction, carpal tunnel, biceps tendon rupture. These are all things that we wanted to include on the dashboard. And then also fairly useful are echo parameters. Given it's the gold standard, a lot of patients get echoes regardless of what pathology is going on in the heart. We were able to get diameters and different measurements of the ventricular wall, the septal wall, and look for keywords as well, such as apical sparing or cherry on top. And then, of course, relevant medications were included as well. Here it is. So it's fairly long, so I had to cut it into segments, but hopefully it's digestible for you guys. We have the patient name here. It can be sorted by any of these categories, age, gender, who their PCP is, which is convenient for contacting if they have a cardiology provider. We have a risk assessment box here, which is able to take the data that we put into the dashboard, provide the Davey score, as well as the number of risk factors. And using that, it spits out a score that can help us determine really quickly if we want a screen or if we want to kind of go into the chart or if we think the risk is pretty low. And then we can see the last pyrophosphate scan. This is how we access and enter data, whether or not it's been complete or not, and then we can assign each of the clinicians who are reviewing to a patient. It also can populate the AMOLED status. Here on this lower section, this is what it looks like when we have our data, the echo parameters, the BNP troponins. Further, we have light chains, history of substance abuse, all of the different medications that could be associated with amyloidosis and then the risk factors, conditions. All populated here, a dot signifying that they have it. And then more comorbidities, more risk factors, just access to a ton of data and one easy to access site. Their next appointment and their next cardiology appointment, which we can track and see are we going to be able to see these guys fairly soon or if we need to get them follow up sooner. The pencil icon I was showing you, the click to let us access data, this is what comes up. It really has a section where we can say, was the screening complete? There's a dropdown that says incomplete. An initial risk assessment, so an initial review versus doing a chart review or an exclusion. And then tests, consults, treatments, anything that we want to order, we would document here, click view report and it would populate onto the dashboard. Here's an example of what it looks like for each individualized patient on their profile. We can see here, sorry it's a little small, but initial review is the action here, chart review and if it was complete, this patient had confirmed amyloidosis and then some notes that we can make. We're going to check up on them, test follow up, date behavior and then a treatment assigned, consults that were done. And other tests that were ordered. So as we, we have this dashboard now, we know how to use it. Now we're approaching what we need for making diagnostic decisions. So reviewing it. We start with, we start with initial, our initial review of the dashboard based on the risk factors and the scores that are piled up. And we do that initial review and we say, sorry, I keep hitting the wrong button. Is it possible? Is it initial? And if the risk is low, then we need to do a, if the risk is high, we need to do a further chart review. We're able to then go in this kind of stepwise pattern to see what testing needs to be ordered. If genetic testing is indicated, initial screening or more advanced screening is ordered. If the PYP eventually comes up positive and we confirm cardiac amyloidosis, then we're able to start therapy. It's important that we're doing this kind of in a shared decision making pathway. So any patient that we assess that has some risk, we talk to them and say, do we want to continue with this or are you not interested? Our expected outcomes are based on the re-aim outcomes. This project is still in the works. We expect to reach 50 to 75% of African American heart failure patients with risk factors and review them. We hope that we're able to identify all patients that are identified can be offered screening if it's indicated. We hope to involve at least five to six clinicians. We're already higher than that, I can tell you. And then we want to make sure we're indicating the adaptions that are made. So this project is reproducible and then continue on the plan afterward and maintain it. Some challenges we faced, several labs and imaging reports weren't standardized across the different facilities. So the informatics team had to put in a great deal of effort to make sure that they was in a digestible form for us. Clinicians themselves only have a limited time for screening on their normal clinical duties, on top of their normal clinical duties. We had to coordinate among teams that are in three different time zones to meet. And that can prove challenging in time just based on the hectic schedules we all face. This is really important for risk assessment, but it also doesn't substitute for in-person clinical assessment. Future directions. We're hopeful to implement this into primary care and cardiology clinics across VA institutions. And hopefully as this grows we can take a multidisciplinary team approach in this as well. Maybe it's something that the GI team or the neurology team or the nephrology team can implement their own data. And it becomes something used across the institution. And we know that there are other VA teams that are active in dashboard development. We hope to collaborate with them in the future and really combine efforts. I want to take some time to acknowledge the United States Department of Veteran Affairs, Pfizer, ASU and the University of Arizona College of Medicine. And then take some time to highlight some of my team members. Without all of their work, this would be possible. Thank you.