Hills and Valleys is a podcast that uncovers stories from leaders in healthcare, tech, and everything in between. Straight from the heart of Silicon Valley, we give you a look at the good, the bad, and the future, one episode at a time. Brought to you by Potrero Medical.
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About Dr. Robert Stevens, MD, FCCM
Dr. Stevens is fellowship-trained and board-certified in critical care medicine, neurocritical care, and anesthesiology. He treats patients with critical illnesses such as sepsis, ARDS, acute kidney injury, traumatic brain injury, and stroke. He has special expertise in the resuscitation of patients after cardiac arrest. Following medical studies, Dr. Stevens received postdoctoral research training in molecular neurobiology, cellular electrophysiology, advanced magnetic resonance imaging, and brain mapping. He holds faculty appointments in the Johns Hopkins Institute for Cell Engineering, Institute for Computational Medicine and the FM Kirby Center for Functional Neuroimaging. Dr. Stevens is on the Council of the European Society of Intensive Care Medicine and chairs the Committee on Computational Critical Care Medicine at the SCCM. He is an Associate Editor of the journal Thorax, and serves on the Editorial Boards of Critical Care Medicine, Neurocritical Care, and Frontiers in Neurology.
Dr Stevens’ vision is to deploy Precision Medicine for the benefit of critically ill patients. His research aims to discover and validate patient-specific biological signatures associated with trauma, surgery and acute conditions such as stroke, cardiac arrest, and sepsis. To achieve this, he engages with an interdisciplinary group of basic and systems neuroscientists, biomedical and computer engineers, biostatisticians, data scientists, and neuroradiologists. Dr Stevens is the principal investigator of the Neuroimaging for Coma Emergence and Recovery (NICER) project, which examines MRI features of the brain connectome to enhance classification and prediction in patients recovering from severe brain injury. Other projects from Dr Stevens’ group analyze features captured through neurophysiologic monitoring, structural and functional MRI of the brain, serum biomarkers and wearable sensors, with the goal of enhancing classification and prediction in vulnerable, acutel ill patients. In the lab, Dr Stevens’ group studies molecular and cellular determinants of injury and recovery in experimental models of traumatic brain injury, stroke, and sepsis, with a special emphasis on neuro-immunological responses and cellular regeneration.
Follow Dr. Stevens on Twitter @RDStevensMD
Interview Transcript
Omar M. Khateeb had the pleasure of interviewing Dr. Robert Stevens, who is currently working at Johns Hopkins university. Khateeb first met Dr. Stevens Orlando at the Society for Critical Care Medicine.
As many of our readers are pre -med, medical students and residents. Khateeb asked Dr. Stevens, what got him into medicine.
Dr. Stevens responds by saying
“Yeah, that’s a great question.
Actually, I started off my studies with an interest in topics that are quite remote from science and medicine. I was very interested in philosophy, political science and literature. But little by little I came to have a sort of deeper understanding of what is involved in being a doctor and the sort of scientific approach to evaluating and treating human disease.
This occurred over several years and involved multiple discussions with friends and family. Finally, I decided that this is probably the right thing for me. So, I entered medical school and I must say that it’s been a great adventure. I do not regret it in any way. ”
Dr. Stevens grew up in Switzerland. As he completed his medical training in medical school. After medical school he went into residency training. He went into different areas in internal medicine and surgery. Through his rotations, Dr. Stevens quickly became fascinated with intensive care medicine.
“That’s when I decided to go do anesthesiology residency.”
It was then, during that residency where Dr. Stevens took the opportunity to work for several months in the intensive care units. He then followed up with the fellowships and even did three different ones in intensive care, as well as neuro critical care.
“Simultaneously, with all this, one of the reasons why I entered medicine and why I remain in medicine is because of the science and the research. So throughout my career as a student, as a resident, as a fellow, and now as a professor, I’ve been very passionate about trying to advance the science in this field. This has been a major preoccupation of mine.”
Khateeb: Hi everyone! This is Omar M. Khateeb, the director of growth here at Potrero Medical. We’re joined by a very special guest, Dr. Robert Stevens, who I got the pleasure of meeting at SCCM. It was a fantastic background. He’s currently at Johns Hopkins university, and I’m going to go ahead and pass it off to him.
Dr. Stevens, thanks for joining us. Can you give us a little bit of your background and your current role at Hopkins?
Dr. Stevens: Hi, how are you? My name is Robert Stevens. I’m an associate professor in the Department of Anesthesiology and Critical Care Medicine at Johns Hopkins University, School of Medicine. I have also joint appointments in neurology, neurosurgery and radiology. I’m the co director of the precision medicine center of excellence for neuro critical care.
I also have a very robust research program, which is primarily dedicated to optimizing the care and outcomes of patients admitted to the ICU using computational and quantitative methods.
Khateeb: Fantastic. Now, Dr. Stevens there’s one question I have to ask. We have a lot of people who are listening who are premed and medical students and, of course, residents. So, just out of curiosity, what got you into medicine? Why did you decide to go into medicine?
Dr. Stevens: Yeah, that’s a great question. Actually, I started off my studies with an interest in topics that are quite remote from science and medicine. I was very interested in philosophy, political science and literature. But little by little I came to have a sort of deeper understanding of what is involved in being a doctor and the sort of scientific approach to evaluating and treating human disease.
This occurred over several years and involved multiple discussions with friends and family. Finally, I decided that this is probably the right thing for me. So, I entered medical school and I must say that it’s been a great adventure. I do not regret it in any way.
Khateeb: Fantastic. After medical school, what did you decide to go to do your residency and training in and why?
Dr. Stevens: I grew up in Switzerland. Having completed my medical training in medical school, I subsequently went into residency training. I went into different areas in internal medicine and surgery. Then I became rapidly fascinated with intensive care medicine through my rotations. That’s when I decided to do anesthesiology residency.
During that residency, I had the opportunity to work for several months in the intensive care units. Then I followed up with the fellowships. Actually I did three different fellowships in intensive care and neuro critical care.
Simultaneously, with all this, one of the reasons why I entered medicine and why I remain in medicine is because of the science and the research. So throughout my career as a student, as a resident, as a fellow, and now as a professor, I’ve been very passionate about trying to advance the science in this field. This has been a major preoccupation of mine.
How can we gain greater knowledge on health and disease using advanced methods?
Khateeb: Yeah. And speaking of which you and I first met a couple of weeks ago in Orlando at the Society for Critical Care Medicine. You were leading a lot of the sessions and panels on artificial intelligence and machine learning, which really I thought was very well done. Just because even though we talk a lot about it in medicine, I don’t think there’s a lot of physicians who, number one, have a good understanding and command of what AI in medicine looks like. And more importantly, they don’t necessarily do a great job of translating that to their peers.
But your sessions were really fantastic. So, when it comes to AI as it applies to precision medicine, what are some things that you’re genuinely excited about and why?
Dr. Stevens: You bring up several interesting terms. First of all, precision medicine. This is something that I’ve personally invested in for several years. I think that we are at a unique time in our history when we have the ability to acquire extremely detailed, high resolution, high frequency information on human health. This can obviously include genomics, imaging, and data from the electronic health records to mention a few.
Currently, we have an unprecedented amount of data that is accessible and can be leveraged. Simultaneously with that, we have techniques like artificial intelligence in particular, machine learning that allow us to effectively and efficiently analyze these complex data sets and extract knowledge that can be helpful to understanding health and understanding disease and how to treat them.
“I think that the convergence that you talked about of precision medicine and artificial intelligence is a very powerful one. I think the goal, of course, of precision medicine is to develop an individualized paradigm of human health, meaning that every single human being is unique. We also need to understand how the health trajectories of each individual are absolutely unique in biological terms. I think we now have the capabilities to do that.”
Then we need to develop interventions to promote health and to solve disease using this highly individualized approach, right? So, I think medicine is evolving rapidly and one of the keys to that evolution?or maybe revolution?is AI because it allows us to process huge amounts of data very fast and very effectively in ways that were just not imaginable even just five or ten years ago.
Khateeb: Absolutely. For the general audience that’s listening, tell us a little bit more what exactly is precision medicine? Is medicine not precise today or in the past, and if not, what does it mean to come closer to having precision medicine?
Dr. Stevens: Many people would like to think that the medicine or the health care that they’re receiving is precise. But the truth is that in many cases, we base our knowledge and our practice of medicine not on what we are seeing in terms of individual characteristics of a patient, but more on inferences that we’ve made on the basis of analyzing groups and large populations, right?
What this means is let’s take a condition that is very common, let’s say, hypertension (high blood pressure). It’s estimated that about anywhere between 40-60% of adults in the United States will develop hypertension in their lifetime. This is very common yet we are beginning to understand that the causes of hypertension are not single. They’re not unique. There are many different potential changes or abnormalities that can occur which can lead to hypertension. And yet the way that we treat hypertension is what you would say is a sort of one size fits all.
We commonly will prescribe the same medication to very heterogeneous groups of individuals who have hypertension not fully appreciating that some of those individuals may benefit from the treatment while others may not. Some may actually be harmed, right?
So when we talk about precision medicine, we’re saying, why don’t we leverage the more detailed biological knowledge that we can gain on individual patients to develop more personalized or more precise therapies. Why don’t we leverage genomics, for example, to identify the specific abnormalities that are leading to hypertension and then target those abnormalities in the treatments that we propose.
This is what precision medicine is all about. It’s essentially trying to tailor the therapies so that we can deliver the right treatments to the right patient at the right time. The reality is that the way that we practice medicine today is a long way from that approach.
Khateeb: Got it. One thing you mentioned that I thought was incredibly important is this advent of having all this data, right? I think the exciting thing in medicine over the last 20 years is that a lot of industries, including medicine, have started to go online and better ways of capturing and providing data have been seen.
But the problem with that is that it’s kind of like a couple hundred years ago when the microscope was used and we looked into a water drop and discovered hundreds of thousands and millions of organisms. I feel like it’s the same way now with medicine and data where it’s great that we have this data, but now we’re getting an onslaught of all this information.
And so doctors and nurses seem to be very overwhelmed with all the data and what to do with it. Do you feel that that’s where, at least, machine learning can help and if so, where do we start in medicine? Where’s the best application?
Dr. Stevens: I think you bring up several important points. I think at the level of where most doctors and nurses practise, many of them feel overwhelmed because there’s so much information that they have to process, document and read to effectively deliver the care that’s expected of them. But at another level, it is true that these very large data sets are becoming available. For example, genomics or different multi omics, transcriptomics, metabolomics, information on the microbiome and then also very detailed quantitative imaging data and quantitative physiologic data. These are things that are beyond the capacity of a single human brain to effectively process and analyze so we do need advanced statistical and machine learning methods to help us with that.
But I would also say that machine learning is useless in the absence of strong biological foundations and hypotheses. I think the only way that this field can advance is through the combination of three things. One is obviously the availability of high resolution, high quality data on human health. That’s one thing. The second is, of course, the implementation of advanced statistical and machine learning modeling approaches. But I think the third piece of this, that is really the key to success, is to have some strong biological hypotheses that will drive the cycle of discovery.
So, it’s not as if you can magically put big data and machine learning together and then some solutions are going to emerge. You need to have the input of domain experts, people who have a deep and broad knowledge of human medicine to be able to really guide the process and move it forward. It’s really those three things that are essential in my view.
Khateeb: I absolutely agree. And that’s the first time I’ve heard articulated that effectively. I think that one of the issues in my opinion that I see, while I’m based here in Silicon Valley, is that the tech world looks at the medical world and says, Oh, you know, if you have all this data in the EMR, we can plug in and just consolidate all this data and then we’re going to change medicine. But the problem with that is that you have to have some strong hypotheses?and I really love that you put it that way?rooted in foundational physiology/biology that’ll help say, if we have the data on this, and then we have some ML and AI capabilities, where’s it going to be most effective and where’s it going to make sense? Because if not, then you can start being led down a complete rabbit hole.
There’s one that I like to point out. My company is focused on fluid management and specifically on urine output for acute kidney injury and about a year ago, Google published a paper on predicting acute kidney injury within 48 hours. So we were all very intrigued. We were like, Oh, that’s great to see this. Let’s see what they have. What they did was they took an algorithm and plugged into the EMR based off of creatine which is, unfortunately, a lagging indicator. You don’t really predict AKI based on that, right?
And so I think you’re right in that the hypotheses have to be strong and rooted in physiology. Right now in medicine, what are some top areas that you think have strong hypotheses to use AI and data to change practice?
Dr. Stevens: I think there are domain experts in many different fields of medicine, certainly in oncology for example. You can see how this field has been transformed just in the past 20 or 30 years. I mean, oncology was largely based on a sort of clinical, histological and gross pathological criteria 20 – 30 years ago. But now it’s largely driven by our understanding of the genetic changes that are either responsible for or result from the cancerous transformation of tissues. These genetic changes are in many ways driving the kinds of therapies that we implement for cancer patients. I would say that if you wanted to talk about success stories for personalized or precision medicine, oncology is one of them.
It’s certainly a story that’s still unfolding, but I think we can learn a lot for what’s being done in the field of cancer.
But my field, which is intensive care medicine, I think is also on the cusp of a major revolution. I think we have a lot of domain expert people who are studying intensive care from different angles who have very valuable, deep insights into why people develop conditions like sepsis or ARDS. We need those people to work closely with the data scientists to effectively leverage the power of big data sets in the intensive care unit.
Talking in the ICU of not just the physiological time series that is recorded on the monitors, but I think we need to go many levels deeper. I think the sort of revolution in intensive care is going to be a combination of knowledge of physiology and also knowledge of biological changes that are the basis for the physiological changes.
So I think there’s a lot that needs to be done. I can see this almost every day in my research group because I’m very fortunate to have a group of people that are working with me. This is a combination of clinicians as well as data scientists, engineers, and computer scientists and we meet on a very regular basis.
It’s usually a constant exchange, right? Because there are data scientists who are really looking towards me and my clinician colleagues for insights on human disease and human physiology, and we’re obviously looking towards them to develop the most effective ways for modeling and for classification.
Khateeb: Interesting. I want to take a quick sidestep. One thing I wanted to mention, which was very nice that it happened this week since we’re jumping on the phone with you, was to say to you and your team, congratulations. I understand that the NCCU (Neuro Critical Care Unit) team in the area of precision medicine was designated as a center of excellence at Johns Hopkins. Is that correct?
Dr. Stevens: Yeah, Johns Hopkins has developed precision medicine and has really understood that this is a strategic priority. So, the School of Medicine and the Dean?Dean Rothman?have decided that they would periodically fund centers dedicated to excellence in a specific domain. Over the past few years, we’ve had precision medicine centers, for example, for prostate cancer and, I think, pancreatic cancer. It’s a competitive process. Every year there’s a solicitation and different teams can compete. So, we were extremely fortunate to be selected this year.
We are in the early stage of putting together a center of excellence that is devoted specifically to optimizing the care and outcomes of patients admitted to the neuro critical care unit. We have several short term objectives but the longer term vision is to do what I was talking about earlier, which is to design the ICU or the neuro ICU of the future where there will be this kind of seamless interaction between the domain experts?the intensivists or the multiple data streams?and, of course, the different tools such as machine learning that will help us to really have a deeper understanding of where our patients are becoming so ill and how we can treat them.
Khateeb: That’s an interesting concept. Tell me a little bit more about that. What does that mean, ‘the neuro ICU of the future’? What does that look like and what kind of hypotheses is that rooted in?
Dr. Stevens: One of the things that really, um, I, I’m very interested in is this question of prediction and prevention. One of the things that I think would be really important in the future is to be able to predict and prevent patients from experiencing critical illness or deterioration in their conditions. I think that we’re close to being able to do that. I think what we need are highly precise and accurate models that can tell us if a patient is about to experience a deterioration like respiratory failure or sepsis, delirium, coma, stroke, heart attack, and pulmonary embolism. These are all events that are potentially catastrophic, but that can be predicted if we have the available data and the appropriate models.
So, I’m hoping that the ICUs of the future are going to be a lot smaller because we’ll be so good at predicting and preventing patients from developing critical illness so that we don’t have to admit them anyway. That’s one thing. And I think once the patients arrive in the ICU it will be extremely good at turning them around and effectively treating them much more effectively than we do now because we’ll have a much sounder understanding of their biological derangements.
So, I’m thinking of an ICU of the future that the real ICU like the ones that we talk about or see today will be much smaller. And the patients will stay with us for lesser durations of times. That’s one thing.
The other way of conceiving it though is to think of it sort of paradoxically as much larger.
And I’ll explain what I mean. What I mean is that we absolutely need to develop methods to implement the kind of monitoring that we have in the ICU to expand that to include the whole hospital. Why do I say that? I say that because we know that in any given hospital or health system, the vast majority of people, usually 80 – 90% of them, are not in intensive care yet.
They’re not in a monitored setting. These are patients who usually are quite sick and that’s why they’re in the hospital; and they’re at risk for deterioration.
What we need?and this is where the input from my engineering colleagues and also people who are not my colleagues who are engineers is really valuable?is to develop sensing or monitoring technologies and predictive algorithms that can help us detect when a patient in the hospital but not in the ICU is likely to deteriorate in the next few hours or in the next few days. What I’m saying sounds a bit contradictory, but it’s not. What I’m saying is that, well, I think the future will look like this. The entire hospital will be like an ICU because everybody will have wearable sensors on them that’ll tell us, hopefully with high accuracy, if they’re likely to deteriorate and will give us a window of opportunity to treat them and prevent the deterioration from happening.
So, that’s one thing. And then on the other hand, I think that the real ICU for the patients who have truly sort of fallen off the cliff, those will be probably smaller because we’ll be so good at preventing those deteriorations. I don’t know if that makes sense, but that’s where I see things going.
Khateeb: No, it completely does. And it’s interesting you put it that way. I totally agree. Again, I’m gonna hedge against what I know really well, which is what we’re doing here at Potrero focusing as a precision fluid management company and urine output and things like intra abdominal pressure are important, but it’s like a piece of the puzzle.
I know that nephrology intensivists who listen to our broadcast will appreciate this, but just a few months ago, they did a study in the UK where they compared creatinine to hourly urine output. And when they measured hourly urine output very intensively comparative to the staging of acute kidney injury, they found that the staging was worse and the incidence of acute kidney injury went up by 30 or 40% and the conclusion was that there needs to be better ways to measure fluids such as urine output.
I think it goes back to, on a very high level, what you just pointed out, which is that the whole hospital is going to be like an intensive care unit in the sense that you’ll have wearables and hardware that’ll help capture and track data continuously, accurately, and first in a streaming fashion. And when you do that, that’s going to illuminate completely new paradigms in medicine on how we should not only detect but also predict illnesses and diseases. And then, of course, that’ll help with different and earlier interventions. So that completely makes sense.
Dr. Stevens: I think that’s the vision for the future, and I think we’re heading there.
I can tell you that I have a separate group of engineers who are right now developing a multimodality sensor, like a little bandage that you can put on the chest. And it provides six different physiological variables. So, you know, we’re doing some testing right now on this. We’re not the only ones who are doing this kind of thing, but it’s certainly a paradigm that we’re going to see a whole lot of and it’s going to be really important. I think it’s going to open up this window of what I would call the preventability of critical illness. I mean, in a perfect world, intensive care units would not exist because we’d become so adept at early identification and prevention.
Khateeb: We want to be mindful of your time so we’re getting close to the top of the hour, but I’ve got a couple of other questions. I’m going to ask this and if you can’t say, you can say no, but I know that our audience will be mad at me if I don’t ask this. That sensor that you’re currently working on, what are the six different modalities biomarkers you’re trying to pick up, if you can share?
Dr. Stevens: I think it might be a little bit early to talk about that, but certainly, I’ll be happy to provide an update once it’s more developed.
Khateeb: All right, so you’re on the hook for that. So hopefully in about six months or a year when things develop, we’re going to have you back on because we would love to hear more about that.
One thing that I think is interesting in the world of precision medicine, especially as it comes to data, is using vital signs?that normally we’ve kind of glanced over and not taken so seriously, just because there hasn’t been a better way to pick them up?in a new way, whether it’s a respiration, urine output, or pulse. Would you agree? And if so, what are some vital signs you think will be really important in terms of using machine learning on?
Dr. Stevens: I think it’s important to differentiate between these episodic measurements that people have relied on until now basically and continue to rely on, which is the nurse will go out and get vital signs once every four hours, once every six hours, and then we’ll look at those trends.
I think the paradigm shift that we’re talking about is continuous time series which obviously are available already now in the intensive care unit but which we’re hoping it will be available more generally throughout the hospitals through the use of wearable sensing and monitoring technologies. The reason I think this evolution is important is because I can tell you that our modeling has shown very clearly that the times series really are signatures of the underlying physiology in a way that the episodic measurements are not.
So when you’re able to sample, for example, the respiratory rate or the heart rate variability or the changes in urine output on a minute to minute or hour to hour basis, it’s a huge difference in terms of identifying physiological signatures that could be associated with imminent or impending deterioration. I think understanding how the temporal component evolves is really crucial.
Another set of parameters that we didn’t talk about, which I personally think are really important, are the neurophysiological changes, for example EEG. I can tell you that in my [….], we do a lot of continuous EEG monitoring and that’s just an incredibly rich signal. The possibilities in terms of deriving meaningful quantitative features from the continuous EEG are, are really huge. We’re just only beginning to leverage that right now.
A third area, which we don’t often think about either especially for the intensive care unit is imaging. My group has been working, for example, on quantitative approaches to CT scan and MRI. And it’s very clear that the way that we currently use routine tests like head CT or brain MRI is really just kind of scratching the surface. There’s a huge amount of information in those types of studies that were not at all exploiting and that we can analyze using systematic quantitative approaches.
Interesting. Again, we appreciate you spending some time out of your day to chat with us. Before we wrap up, I do have some interesting questions that we call rapid fire questions. We like to ask all our healthcare leaders these questions and you can take as long or as short of a time as you’d like to answer them. Of course, if you answer the question fast, then I’ll move on to the next one. But otherwise, take your time on it.
The first question is actually good because it’s something that you and I were very much able to relate to. Both you and I are really into books. From my understanding, you get in trouble with your spouse for ordering too many books on Amazon, so I’m glad that there’s someone else out there like me.
But for all the people who are listening, especially the young leaders in medicine and healthcare, what’s a book that you most often recommend or perhaps a book that you read recently that really influenced the way you think today?
Dr. Stevens: Oh, that’s a hard one because I do read a lot. I’m very partial to fiction and also philosophy. But in terms of practical business oriented books that I like the work of Nassim Teleb. He wrote The Black Swan and Fooled By Randomness. I think those are very thought provoking books.
Khateeb: He wrote one recently called Skin In The Game. The scene is fantastic.
Dr. Stevens: I have not read that most recent one but I think he’s very smart and very thought provoking. I’m also very interested in the work of Daniel Goldman. I like Emotional Intelligence, I like [….] and Thinking Fast And Slow.
I think those are really interesting books that I’ve really enjoyed quite a bit.
Khateeb: Oh, those are fantastic recommendations. I completely agree and I’ll leave links in the show notes for our audience. Here’s the next one and we can wrap up on this last question.
So, I want you to imagine that everywhere in the United States, you’re going to have a billboard that’s going to stay up for one year, and every medical peer of yours is going to see this billboard as they go into work. What message would you put on that billboard?
Dr. Stevens: Probably, pay attention. I’ll say pay attention because I think?and the reason may sound very simplistic?we can gain so much by just paying very close attention to our patients, to our behavior, to their behavior, to our interactions, to gaining insights on health and disease. So I think I would just say pay attention.
Khateeb: I really liked that answer and I completely agree. I think whether you’re a physician or someone who works in the world of tech, I think the benefit of all those technologies is that yes, it does make things a little bit easier and it makes us more efficient. But more importantly, the hope is that when technology lifts the burden of some of these manual tasks and things that we don’t like to do, we have to go back to strengthening our own minds and being able to pay close attention to things. And I think that’s, that’s a big part of the human spirit.
Dr. Stevens: Yeah. I couldn’t agree more. I mean, some philosophers have opined on this subject. But you can make the case that if we were really good at paying attention, we could probably solve many of the problems that we see around us. I think that we’re usually in so much of a rush. We’re inundated by so much information that we fail to appropriately pay attention. When I say pay attention, I don’t mean I’m moving away from the technical world. I mean actually this being more insightful in the way that we appreciate what’s going on around us and try to interpret it in ways that we hadn’t been able to do in the past.
Khateeb: I completely agree. Oh, Dr. Stephens, we really appreciate you spending some time and coming on. Again, you’re on the hook with us. So, hopefully in about six to nine months or a year, we’ll have you back on. We’d love to hear updates from your research group and how things are going. Again, thank you for spending the time with us today.
Dr. Stevens: Yeah, my pleasure.
Khateeb: Perfect. Well, have a great day. And for everyone out there, we’ll see next time.
Dr. Stevens: Take care, Omar.
Khateeb: Take care.
Dr. Stevens: All right.
