I think it's sort of. Many of the things that there will be in this talk.
May never happen. Some of them will happen. Some of them already happening now.
How that will evolve, to what extent and how all of these things will blend into one future.
It will be interesting to explore. So.
When I was thinking about his lecture, the first thing I thought is whether does actually defining me as a cardiac surgeon when?
What? Do people see on me when we look around and I thought that these four things currently were the most appropriate thing that defines us,
so Koppel, life, go-gos and the.
Bypass machine, you know, put these things together, and probably you have a kind of a cardiac surgeon more or less.
However, if you look at them, really a basic.
Started from this car pool that is 6000 7000 technology and moving more advanced things, but really amazing.
So here are some things that I was trained.
But not practise anymore, at least that frequently, you know, I was I was trained to I want to start a cardiac surgery.
We used to do a very big incisions almost down to the on black was cutting both legs open.
And then asking that patient to walk or recover. Big laparotomy.
But of course, to me. I remember patients lingering the ward for days.
We. Now, things have changed.
This is what I was not trained to do.
But I practise every day. We moved into more and more minimally invasive, more accurate grafts.
Patients have spent about.
In days, most of our patients actually go Home Depot, the vast majority of my patients to stop taking painkillers after a couple of weeks.
And he has some things that there were not even on the menu when I would start training.
It didn't even exist. There were probably thought of somewhere know somebody crazy in Paris putting some vibes in or God knows what.
But they're here to stay. And.
We move on. What about today?
I think today we are getting to an era of patient optimised surgical care.
The sequence of the woods, I think it's important. We moved into what we call it, courting territory, putting two point zero.
In that one, each member is equal. And it's important.
And the team should be based on diversity and enable cross fertilisation, that collaborative approach.
That we've been having up until now.
Is primitive, we should move beyond that, because complementary is a temporary solution, or the ping based 1.0 was based on complementary services.
But being complimentary means that if I don't need you more today, you're out.
Shouldn't enable established partnerships. People working together not to actually decide what we're going to do, I want to get cabbage or PCI.
But actually go beyond. Decide how we're going to do this cabbage.
Or how we're going to do this by. Focus on similarities in synergies and emphasise core competencies and not skills.
Because competencies involve. Skills probably stay with you.
In a more static way. We should understand surgical techniques, yes, but what we should understand is technology.
Techniques is a static. But surgeons are obsessed in teaching techniques.
Technologies are dynamic. Our techniques are static.
The technology evolves around us and around our techniques, and all of these things are changing.
Surgical college curriculums primarily, they talk about techniques they talk about, think of information, hardly anything there about technology.
And this is where everything is changing. What does surgery give you?
Surgery gives you durability. OK.
Yes, we have Tavis, and we have aortic valve replacement.
And we may say Paris with a new trials, are suitable for low risk patients.
But low risk patient doesn't mean low age patient. It can be a low risk 80 year old and a low risk 60 year old.
Surgery has durability. And this is what should we base our decisions upon?
And then we have complexity. As the easier, low risk move, more and more into very contentious approaches.
Then how new surgeons will learn how to do the easy stuff.
If said ended up doing more complex stuff. How the new generations of will be trained.
We'll be trained in the conventional way as we use to train them I to an easy cabbage training,
using air and move on, or we're going to end up having to do them a practise and we are.
So is a challenge, you said that becoming a real statesman and probably a surgeon.
You need to think about the next generations and not about the next elections.
So you need to think about a couple of steps ahead of you.
So I think what we should think about is start building walls.
The other thing is that in the modern world, especially for young generations, people starting their careers.
Should stop fighting in defending borders from an invasion of this.
Stop fighting about if Poppy is better than surgery.
You should find the way in blending into those things.
Start building trust, because this is the most important component of teamwork and it's a great vacuum.
We want to think that we were walking teams, are we really?
It's extremely important to build the future and trust.
Because when the patient comes to theatre, I trust my misfits, that's going to do its best job across the street.
The nurse is going to do it. The perfusion is. The president was looking after the intensive care.
And the people there. So trust is extremely important.
Never been put.
We expect to know you expect to be blanketing you are appointed as a consultant or a registrar, you're working for unit, you know, nobody.
People should trust you and you should trust everyone. Educate.
And how do we educate today? We get brilliant minds.
It put them in the squeeze for everybody to get the same more or less active getting that.
It is what we want to educate. Can everyone climb the tree in the same way?
That's because we have a treat, because it means that every person is equipped for that role.
I think we should educate full time capacity and knowledge. We should educate by engaging people.
Understand that there is an individuality amongst humans.
OK, we're equal, and we may have different colours.
And we should educate to elevate. Time is of the essence, what is the point of creating cardiac surgeons had a.
Who are training for basic cardiac? Paediatric adult.
That's my training, eventually doing just adult cardiac. A value.
But is it really? Let's move in the future now, and I think emerging virtual reality, augmented reality.
We are part of our future. Imagine is not only obtaining information but has moved on.
It has moved on into projecting 3-D at 9:40, adding tactile capacity to it.
And simulation, is he already in training at Halley herself, surgical procedures?
And leading into standardising procedures and training.
We can actually probably perform the operation before we actually do it.
And it will be better doing it.
We don't necessarily need to train people straight into theatre, we may move into actually doing it in simulation environment.
Because you cannot afford to do 200 cases of each type and make people competent on everything
before they move into doing straight complex cases because the easy cases will go continuously.
So imagine we will move on, and it's here, all of these things happening as we speak.
It's not that much of a future will evolve because it will be the integration that will happen.
But actually, this is present.
And Imogene is troubling, it's becoming better in capturing increases, smiles, smaller structures and functions inside the body.
We have functional MRI is not only MRI. Sensory, then, might need to move forward.
Interventions at the lower level, not macroscopic anymore.
Even down to cell level. 3D printing.
Okay, if you're somebody would have asked me about two or three years ago which one is going to have the most impact?
Probably, I would say 3-D printing, because that's going involve we can compress. Not so sure anymore.
3-D printing and planning technologies are already used in surgery.
Personalised implants in surgical instruments. So what can we plan we bring with practise and we perform?
The first fully plastic valve. It's in stage a trial stage three and implanted about five months ago, pacing.
He's alive and kicking and moving on. One of these things will come.
But we are not going to be only printing valves or printing organs.
I think we're going to move to bring in food. Printing pills.
Specific to microbiome and the physiology of each individual patient, you don't need to go to the pharmacy.
You're pretty depending on what ink you put can produce whatever you want.
Nanotechnology, nanotechnology is here today.
It is here in many forms in forms of pure metallic bits that we use for breaks and navigation on DaVinci models or anything like that.
But also on nano drugs. Nanjing delivery systems, tissue engineering and genetic engineering.
The. We have a problem with nanotechnology.
We have a problem because there are not sufficient information about biological safety on nano peptides at cell level.
And nano peptides and particles can produce allergic reactions, cause inflammation can cause direct toxicity to live in cells.
The minute we put it in the body. And we actually stop them.
Carry on forever. How do you get them up? Future of shattering genomics.
Aortic surgery now in the ageing surgical team. We have somebody who does genes.
So we're moving to understand things in a different way. We used to treat macroscopic stuff.
We move to understanding better.
And we understand this is profiles, and we helped develop precision medicine, but also precision care to our patients.
And in that we have greater nomics, we have pharmacogenetics pharmacogenomics.
STEM cell therapies and cloning. All of these things will evolve, come and catches.
We already hear that billions spent in each one of those.
But this can only happen in materialise. With fully integrated capacity to deal with big data.
And I think now I'm coming to the idea that big data.
Is what's going to make the difference? Artificial intelligence.
Why do we place our current medical practise on statistics?
Yes, everything is based on statistics, which are what everything is told by a population.
By means quiet house confidence in the roads. What is machine learning and algorithms versus artificial intelligence?
Yeah, it's ability to learn from daily data without being explicit programmed.
That's the definition of artificial intelligence. And it's moving in.
It's moving into the reasoning, and it will influence the way we practise.
So artificial intelligence will be involved into the initial pre operative part and also introspectively
and postoperatively will be influenced by collecting surgical data and from population analysis,
which will interact in real time. Now looking to the capacity of humans in the capacity of our.
Machine. We are just below the crossing point.
Susan, what's going to happen is that machine capacity and machine will surpass human demands by a couple of months ago said that probably soon.
Computer talking to humans will be a similar situation. Humans are going to treat currently.
For humans, one millisecond is. Fast for artificial intelligence.
It's an eternity. The fastest computer today will be exceptionally slow.
For quantum computing, that's coming. The fastest computer today to deal with an algorithm encryption algorithm would take 10000 years.
Quantum computing can actually go through an algorithm in 0.1 of a second.
Next, superpower, be the one that will make one of them crazy, the one that has missiles.
Robotics. Developments in robotics, surgical tasks will be increasingly be automated with more guidance, support and information available.
You're going to have your Alexa to help you when you perform an operation because you can't remember everything.
Alexa, we'll be checking you if you're doing it right up until the computer picks it up.
Fully automated robot surgeons probably are likely to populate operating theatres in the next decade, but I'm not so sure about the decade after.
You have the first thing in your theatre, maybe a stack, almost never the fear that you find a stack.
In what a lot of fear did you find the net generation of da Vinci?
And it's moving on. But probably we're moving to integrated technology.
This is actually a model Cath lab. I went to a meeting recently where a cardiologist from India had to go away sitting in front of his computer,
he'd do an angiogram in India from Germany.
Using this technology. What we will need is a human, perhaps,
though the human rights of clinicians and relationship with patients will remain central to the delivery of excellent care.
Because we are all human. Big data.
I think this is. What I believe the breakthrough will happen with big data.
Data collection analysis when enabled, better prediction of disease,
along with personalisation of treatment options, an increase in effectiveness and already.
Bias will decrease, and holistic approach to treatment will increase the best,
the best laboratory in the world, but probably over 60 percent efficacy be generated by humans.
Driverless cars are not crashing because they're stupid.
Yeah, crashing because they are based on information programmed by humans with human errors.
So big data. Big data, what is it?
How much is growth you give us on 13, we have 153 exabytes.
A 2020, generally, we expect to have 2310 exabytes or more, which is 48 percent increase per year.
Your series, listen to you constantly, EPIs, constantly collecting data constantly.
That happens across the globe.
Now, look, what we'll have to do, are we ready for this mortality from heart disease and developing atrial fibrillation,
which is just being present in the American Heart Association meeting in November?
Big data from one point seventy seven million EKGs. 400000 people.
Medical records from 20 years ago was able to accurately predict chances of dying or developing atrial fibrillation in the next year.
The of the artificial intelligence, the algorithm was able to accurately predict even on passages that have been cleared by clinicians.
Even when three clinicians were looking to the same messages, they couldn't really identify the patterns in their.
But I did. Researchers are moving on, trying to integrate those algorithms treatment options.
Big data from aortic stenosis, what do we base our treatment of everything stent options on?
Papers of that I take. Gouging the gas station in the guidelines, which took off about paper from 20 years ago with 28 patients.
A correspondent on and on now, mortality from aortic stenosis and big data, over 500000 echoes analysed.
What has shown patience with previous Article five interventions being excluded, five years and mortality?
If you have a moderate or severe losses, it's over 50 percent.
More importantly, it's over 50 percent if your aortic stenosis, it's got a gradient over 20.
Which is verging into mild. Are we ready for this?
How would you know those patients? If we replace a native ISS with a surgical induced disease with it, which is a new valve, is it better?
We don't know. We as clinicians, we are trained to recognise established disease.
And we are we are trying to treat established disease.
The I can crunch data and potentially teach us things that we have been maybe misinterpreting for decades.
So the whole environment would change. But there is one fundamental thing here is ethics.
Yes, the future will be full of complexity, cost and certainty.
But full of ethical implications, can we treat everyone? How far can we go?
Ethical and social economic implications, I think, probably are the only incidents in translating these technologies into routine medical practise.
Thank you very much.