What is Evidence Based Orthodontics?

00:00  Slides 1-2

So, I'll start a little bit.I have no conflict of interest related to this presentation.

00:10  Slide 3

And I just want to give you a little bit of my background.

I don't know, you see Corfu, that's where I live, that's the island.It's between Italy and the mainland of Greece. And that's where I have my orthodontic office.

So, I traveled all the way to Athens and then to China.

00:34  Slide 4

So that's the island, and I did my dental degree in Athens University.

00:44  Slide 5

and then after that, I went to the Ohio State University, where I did my orthodontic practice, specialty training certificate, and a master.

00:54  Slide 6

I went also to the University of Texas and did a fellowship in craniofacial orthodontics.

01:02  Slide 7

And then I came all the way back to Corfu and I opened my office.

But in the meantime, I brought somebody with me, my wife.

01:11  Slide 8

So then I started my practice in 1991.

So I've been working almost 35 years now, and I still work every day when I'm there.

But then after I've been working in my practice, after 10 years I had a midlife research crisis, as I call it.

So I wanted to find out more things about how we do things and why we do them.

So then I started doing some research by myself in the office, but then soon I realized that I need to get more formal education in order to do good research.

01:51  Slide 9

So then I started with Dr. med dent, it's kind of like a PhD in biomechanics at the University of Bern.

See, I was working at the same time, I was doing that.

Then I understood that it's important to know how to do clinical research and I did a Master’s in Clinical Trials at the London School of Hygiene & Tropical Medicine, where I also ended up teaching there for like 15 years.

Then I was hired by the University of Bern, where I have now a position there as you already know.

Then I understood that I needed to do something more and I did a PhD in epidemiology which was basically mainly on research synthesis methods like meta-analysis.

And finally I did a Master's in Biostatistics at the University of Hasselt in Belgium, and from all the things that I've done, that was the most difficult one.

Because the Masters was taught by mathematicians, so I didn't have the background.

So I was working in my office, then I had some mathematicians come to help me out and so forth.

But I made it.

02:57  Slide 10

Anyway, so this is just a little bit of my background.

And the message I want to give you is that it's important to ask why and to understand why we do things.

And that was my incentive of doing all those things because I was going to the lectures and I wanted to understand more about what was going on in more depth.

And this would drive me to do all the stuff that I did.

I know it's difficult to do all those things.

They will tell you to do the same thing, but you should ask why.

That's important.

Anyway, so going now to the lecture.

So every day we see patients in our office and we have to make decisions.

What should we do to the patient? How should we treat the patient, what kind of appliance to use.

03:41  Slide 11

And I'm also a clinician, and I have the same dilemma that you have every day.

You know, when you're in the university, you can have the professors to help you, but once you leave, then you're alone, and you're going to face difficult problems and difficult cases.

So you need to make a decision.

So how should you make that decision?

04:04  Slide 12

Should you ask your friends, your colleagues, your peers, your professor, call them up and say, what should I do with that case?

04:11  Slide 13

You also go to meetings.

04:15  Slide 14

You hear speakers talk, they introduce you to new products, you take courses, but what are your expectations?

Why do you do that?

Obviously we do things because we want to give better care to our patients.

But now the question is, when you go to those meetings, or to those congresses, or those workshops.

Can you trust what you hear?

Do you believe what they say?

04:40  Slide 15

So who else could I ask?

Should I ask an authority?

Or what is the best thing to do?

I don't know many authorities.

I know only one.

And that's my mother, because she knows everything.

04:55  Slide 16

So the next thing, which is very common now, we have the companies which come to you and they bombard you all the time, either in your office or in the meetings and so forth.

So should I go and listen to what they're trying to tell me?

Should I go and use the first new product that comes to the market?

05:15  Slide 17

But what is the issue with the companies?

Do they do a new product because they want to benefit the patient or is it because of a commercial interest?

05:27  Slide 18

So I'm going to give you an example of a typical process of a new product introduction orthodontics to see how these things work.

05:36  Slide 19

I think you're all familiar with self-ligating appliance and the conventional appliance.

And the idea was that we changed the design of the bracket

So you have this one, you have the elastic, which pushes on the wire.

And this one you have a door, so the wire is loose.

So the company makes a new design, which is called passive self-ligation.

Now, with a new design, they make a series of assumptions.

And those are the assumptions.

You have less friction, because the wire is moving, is floating into the bracket.

And you also have lower forces because of that.

You see, those are all assumptions based on the new design.

Then you have more physiologic tooth movement, then you have better bone adaptation, faster tooth movement, and faster treatment.

So you have a new design, and because of the new design you make a series of assumptions.

However, when this was tested in clinical trials, all those assumptions were company claims.

There was no evidence for it.

07:00  Slide 20

And, you know, for your patient, what does that mean?

If you work like 30 years and you do 100 cases or 200 cases or 300 cases a year, that means you have to increase the cost of the treatment for your patient.

But if you ask your patient to give you more money, shouldn't you be confident that you're going to deliver something better for the patient?

I think you should.

07:27  Slide 21

That's another example.

Perhaps you know this.

Are you familiar with this system?

So basically you vibrate, you use that 20 minutes a day, and you speed up orthodontic tooth movement.

And the information or the evidence is supported by 15 clinical studies.

This is the advertisement of the company.

Then you have 50% faster tooth movement and lower pain.

Then I'm looking for this citation, which is number one you see in the yellow circle.

And then I'm trying to find in this paper to see what does it say.

And all I find is data on file.

And I can't find anything of the 15 clinical studies.

08:20  Slide 22

And then some studies came out.

For example, the first trial that came out was in Seminars in Orthodontics, which is not exactly a peer-reviewed journal.

And it shows that you have increased alignment using this system 20 minutes a day.

And just to tell you a little bit of an anecdote, somebody told me that they asked the company,

why did you set up 20 minutes a day and not 15 minutes a day or 30 minutes a day?

And the answer was because I didn't think the patient was going to use it longer.

So it wasn't based on the evidence.

And in this specific study, which showed to be effective, one of the authors worked for the company.

So we had a conflict of interest.

Now later on, new evidence came out and none of the scientific evidence that was published actually showed that this was effective in alignment or in space closure or in using combination with aligners.

09:25  Slide 23

So we have this scenario which is common, which is called "Fake it til you make it".

You see a product in the market, you can use it because it's very easy to bring it to the market.

At the same time, we don't know if the product is working and the company is trying to make the product work, so they're faking it until they make it.

09:53  Slide 24

This is a publication we did a few years ago.

We actually have done an update and the findings were the same.

So we looked at papers that examined the effectiveness of clinical products in orthodontics.

10:11  Slide 25

We identified in the period of 2012-2016 84 randomized clinical studies, which about half of them tested marketed products, like for example the Acceladent that I showed you.

Now, half of those products did not show any evidence in the publication that they were effective.

And that's the point that I want to make, that there's no need for the new products in orthodontics to be shown that they're effective.

They just have to show that they're safe to be used or they're similar with something else which has been used.

So a lot of the products that we use are sold as cosmetics.

And now the burden is on us, the clinician, to conduct a study and show whether this is effective or not, while using it on your patient and testing it on your patient.

I'm not sure how fair and ethical is that.

11:12  Slide 26

The ideal would be to have independent investigators examine and assess the products before they come to the market.

Instead of having data on a file or the company is telling you we use this with some doctors and it's working very well.

11:20  Slide 27

And this is what I call an Oxymoron.

Do you know what this word means?

This is actually a Greek word, "oxi" means "acid", "moron" means "stupid".

So it's a conflict.

And the conflict is the following: that we can use a product in our office without any evidence, but if we want to see whether this product is working or not, we have to go and get ethical approval and design a study that will take forever to conduct.

But if we don't care about that, we can just use it.

So that's the conflict.

12:11  Slide 28

And I know I've been a little negative on the companies, but I just want to give you the correct perspective and that's what we need to do.

We need the companies because they help us with making fantastic products that have made our life very easy.

But on the other hand, we need to be the ones making the decisions because we are the dentists, we are the orthodontists, we have the knowledge on what and how to diagnose the patient and how to use these therapies.

So we need to remember that.

12:50  Slide 29

Because if we forget that, we are just going to end up being the company's beautician.

You know how you go to a department store and then they come to you and they say they're going to paint you and make you look beautiful and so forth.

We're just going to end up doing that.

Taking the product and delivering it.

13:06  Slide 30

I think you understand now that the ideal way is not to go by what the company says.

And then there's another approach which we call the evidence-based approach.

So what is the evidence-based approach in orthodontic clinical practice?

13:22  Slide 31

Perhaps you've seen that and we have the three components.

We have the first component is the clinical expertise.

13:33  Slide 32

What does that mean?

You have a patient, this is a young patient, he's in a mixed-dentition,

Class II, Division 1, deep bite.

Okay, now you're the specialist, you're the clinical expert and never forget that.

Because you're very important in this process.

Because you're the only one who can diagnose this case.

You have the ability to diagnose, you have the ability to treat the case, and you also have the equipment and the infrastructure to make it happen.

14:08  Slide 33

Now, the next level, or the next component of this approach is what we call the best available scientific evidence.

14:18  Slide 34

And the best available evidence can be found in scientific journals and especially on peer-reviewed journals.

Do we all understand the meaning of peer-reviewed journals?

14:30  Slide 35

And in terms of the evidence, perhaps you've seen this character of evidence, the pyramid of evidence, and on the bottom you have low-quality evidence and as you go up you have higher-quality evidence, but you have to remember this is a probabilistic scheme or pyramid.

What does this mean?

It doesn't mean that the expert will give you the incorrect idea or incorrect conclusion.

All it says is that the probability of making a mistake is lower if you use higher quality of evidence.

And perhaps in orthodontics a lot of times it's not as important, but in medicine it's more important because we're dealing with issues of life and death.

15:25  Slide 36

So at the bottom, as we say, we have ideas, expert opinions, personal opinions, okay?

And that's what we call evidence-based medicine, which means we trust on the expert, or if we do evidence-based medicine, we place more focus on the numbers, on the data.

15:41  Slide 37

And I found this, that's from the BMJ 1999, making the same mistakes with increasing confidence over an impressive number of years.

That's what is evidence-based medicine.

And I think that's kind of common in orthodontics because a lot of things we do, maybe we're used to been, we continue doing them, but we don't know exactly or for sure whether this is the optimal thing to do for our patient.

But because often we don't have the side effects and because we're confident with it, we just continue doing that.

16:15  Slide 38

The next level is what we call the case reports.

Those are individual cases which are helpful to illustrate something, but they're not helpful to illustrate the scientific evidence.

16:27  Slides 39-40

Because everybody can show you a case.

That's one of my cases I did many years ago, which has a nice result. it was a Class II, Division 2 case, but everybody has a nice case to show you, but that doesn't mean anything.

16:43  Slide 41

Then the next level is what we call observational studies.

16:48  Slide 42

I'm going to make a little bit of an explanation here.

We have, from the clinical study perspective, we have two types of studies.

We have non-experimental and experimental.

17:00  Slide 43

I want you to pay attention to this diagram.

You see it says the question is, "Did the investigator assign the treatment?"

If the answer is no, or if it's yes, you go to experimental or observational.

So the investigator assigned the treatment, meaning that he decided to do a study from now on in a prospective way, and he randomized the patients to treatment A or treatment B, and then you follow them for X amount of years, months, and so on.

But then on the other hand, we have what we call observational, meaning that the investigator did not assign the intervention.

17:48  Slide 44

But what does that mean? I'm going to show you an example.

So let's say I've been working 35 years, and I've been using for impacted canines the open and the closed exposure techniques.

So let's assume that I started, you know, in the beginning doing the open technique, and then later on I went to the closed technique.

I did apply the intervention, but it wasn't intended into an experimental setup.

Because now I'm going back retrospectively, I'm pulling out the files of the patients, and I want to see the patients that I treated all those 35 years using the two methods, which one gave me better periodontal outcomes. or maybe eruption success and so on.

But that's a retrospective study, it's an observational study.

Even though I did the treatment, it wasn't in a planned perspective experiment, so that's the difference.

And the majority of the studies that we have in orthodontics published are observational studies, and they have limitations.

18:56  Slide 45

And some of them is like, for example, this case, the example I gave you, maybe in the closed technique, I had easier cases. Maybe the canine impact wasn't as severe.

So this actually confounds the association.

So the closed technique looks better because maybe I had older patients or maybe I had like less severe impactions.

19:29  Slide 46

And this is an interesting book that talks about how we think.

And the left and the right brain, parts of our brain, you have on the one side,

you have what we call the intuition.

So we see something in our office and automatically we associate it with previous experience we have.

And we jump on it and do something based on what we know before. what we know before doesn't necessarily mean it was the correct thing, but we automatically tend to go to that way because it's easy for us.

Now on the other side, you have to work much harder because you have to reason and evaluate the data.

20:16  Slide 47

And if you, we all know, if you sit on the couch or on the seat and you watch TV and hear nice story, it's much easier to follow that instead of me showing you some numbers and trying to explain to you what's going on.

And there's nothing wrong with you, it's just that's the way we are, that's the way the human brain is working and that's what we try to fight.

20:42  Slide 48

We confuse what we call causality with correlation.

Things happen at the same time, but it doesn't mean one is causing the other.

20:55  Slide 49

And this is an example for that. So ice cream sales go up in the summer we all understand that, but also we have an increase in attacks by sharks in the summer. Is there an association or a correlation for this one.

21:16  Slide 50

And the way to answer that is as follows: Can ice cream sales predict shark attacks? Yes, they can predict them. Because you have an increased number of shark attacks, at the same time you have increase in ice cream sales. But the next level of question is this:

Can we intervene on ice cream sales and change the frequency of shark attacks?

And the answer is no.

So, what I'm saying is if the increase on the ice cream sales is causing the shark attacks,

if I start selling ice cream, then the shark attacks should go down.

If I haven't, then we have causation, but we don't have that obviously. So that's the point.

22:08  Slide 51

So we talked a little bit about the limitations of observational studies, so the next level is what we call a randomized clinical study.

22:18  Slide 52

And what is a randomized clinical study?

22:20  Slide 53

It is a study where you randomize the allocation. And there are specific ways to do that, I'm not going to go into much detail on that now. You have, you use a control, and you also have a controlled experimentation, you have very specific methods to allocate the interventions and to follow the basis and so on.

And this is an experimental design because I start now, I design it and I move on prospectively.

Unlike the example that I gave you before, which was the observational going back and looking at my records.

22:57  Slide 54

And the RCT is what we call the gold standard and the best design where applicable to assess causality. We can know correlation but causality. And I say where applicable because it's not possible to do a randomized clinical study in all cases. For example, you can know a randomized patient to start smoking and another group of patients not to smoke and follow them prospectively because this is not ethical. In those scenarios, we will have to use an observational study.

23:30  Slide 55

And the aim of a randomized clinical study is to make patient groups which are similar in both known and unknown parameters, and the only difference between them would be the intervention.

Because if they're similar in all ways, and the only difference is the intervention, then we can assume that if we have an effect, we have a causal effect.

23:58  Slide 56

This is a flow diagram of a clinical study.

You assess, you know, you design your study, you write your protocol, you assess whether the patients are eligible for your study. Once they accept to sign the consent, then you can randomize them into one or the other intervention, you follow them, and when you come to the end point, then you analyze your data and you publish your paper.

24:30  Slide 57

And some of the requirements of a randomized clinical study has to be controlled.

It's important to use a control.

And if you see a publication that doesn't have a control, you should be aware.

24:44  Slide 58

And the reason is the following.

Let's say my back is hurting today.

If I take some medication, maybe I'll get better.

But also if I don't take any medication, maybe next week I'll be fine.

So is it the medicine or is it the time that treat my disease?

Now if you have a control, some patients taking the medicine and some patients not taking the medicine, then you can be more certain whether there's an effect or no effect from the intervention.

25:16  Slide 59

I'll give you a more dental example.

Perhaps you've seen the discussion about,

"Is orthodontic treatment causing recession?"

Yes or no.

Unless we have a control of patients that did not have orthodontic treatment, it will be difficult to make this assessment, because we already know that as we get older, we have more recessions.

So if you only look at orthodontic patients, and we are comparing them to the control, prospectively, then how can you say orthodontic treatment is causing recessions?

25:56  Slide 60

And I want you to study this.

You see on the left side I have the treatment.

So imagine that the height of the bar is the effect of the therapy, in the treatment and the control group.

But the actual treatment is not the whole bar, it's only the blue part.

Because you have to take out the effect of what will happen with time to the control.

And that's why it's very important to have a control, because otherwise you cannot tell.

26:34  Slide 61

And that's one of my favorite quotes:

"The art of medicine consists in amusing the patient while nature cures the disease."

It's what I said before, you know, if I don't do anything, maybe my back will get better.

26:53  Slide 62

And the other issue is you have to have a study which is unbiased.

I talked about a couple of biases in observational studies, also randomized clinical studies. If they're not done properly, they also have biases.

27:08  Slide 63

And there is a distinction between what is biased and what is the quality of the study. And quality means did I do the best that I could do for my patients?

Because sometimes you could do the best that you can do, but you could still have bias.

For example, if you cannot apply blinding in the intervention, you could end up with some bias, but it doesn't mean you didn't try to do your best.

27:34  Slide 64

And bias means should I believe the results, the conclusions of the study.

27:40  Slide 65

And this is just a quick diagram without going into details about all of them.

At each level of the clinical study, you have different types of biases, which I'm not going to discuss, just to give you an idea.

28:00  Slide 66

So moving from the individual study, which is the randomized clinical study, now to a systematic review because you have to remember the aim is to do what is best for your patient.

Where do I get the evidence from?

From the highest quality of the evidence.

It's not ideal to make a conclusion based on a single study.

So that's why we have what we call a systematic review which combines under certain conditions all the available evidence.

So then we're more confident as to whether an intervention is working and as to whether we should go this way or the other way in terms of deciding.

28:42  Slide 67

So the purpose of a systematic review is to assess all the scientific evidence which is available, and sometimes there are studies, or often maybe, that they're pointing to opposite conclusions.

So a systematic review will come in and possibly help you to solve these controversies that exist.

29:04  Slide 68

So they use a standardized and transparent methodology, you identify the eligible studies and you extract the information and combine the data.

29:16  Slide 69

And this is a diagram, you start with a question that you have, and we use PICO, participants, interventions, comparision and outcomes.

So for example, in our case, it's a patient that I showed you, mixed dentition, and the intervention, for example, could be one stage versus two stage treatment.

The comparision will be one of the two, and the outcome will be, for example, the reduction of the overjet or maybe the risk of having fracture of your upper incisors.

So you have your inclusion and exclusion criteria, and based on those, you select the available study that you find in the literature. you extract information, and I don't mean just the numbers, also the specific details. For example, how did they randomize? Did they have blinding? Did they follow all the patients? Were the patients some patients missing from one group versus the other? And so on.

So, in that way, you can assess the quality of your study. Because we want to combine into a systematic review and particular meta-analysis, studies which are homogeneous and are high quality.

And then you can meta-analyze your data if you decide that the information you have is eligible to be combined to a meta-analysis, and then you can interpret your findings and make your decision.

30:55  Slide 70

So the systematic review, you find all the studies, you filter them through this funnel, and then if possible you make this mathematical combination which we call a meta-analysis and you can see what you see here is a forest plot. I assume you're all familiar with this forest plot.

I will explain what it is, how you read that.

31:20  Slide 71

And this is just a comment, perhaps you've heard garbage in, garbage out. It's easy to do a systematic review and do a forest plot, but it's also at the same time not easy. Now with a computer you can put in the numbers and get something out, get a plot out, but that doesn't mean it's appropriate. You have to go through all the steps.

31:46  Slide 72

So I will explain now how you, what are the different parts of the forest plot.

So on the left you see the number of studies in this particular forest plot, the forest studies.

Then you have the number of patients, for example, the first study has 25 patients.

Then you have the mean and the standard deviation.

The outcome here was like, for example, overjet reduction.

So n2, mean2, sd2, also the number of patients, the mean value and the standard deviation of the control arm.

Then on the side where you see the box, we have what we call the mean difference. It's called here weighted mean difference, but they also use the term mean difference.

And what it says is that when you combine your studies, you don't add up the numbers and get the average.

So that means I'm not going to add the -0.7, 0.1, 0.44, 0.52, and divide it by 4.

You give different weights to your study.

And that's what you see.

Okay, you'll see in a moment, okay?

So that's the estimate, the 0.70.

And that's the weight.

So different studies, depending on their variance, or let's say simply the sample size, will have different weights in your meta-analysis.

And that's important.

You put less weight in smaller studies.

But then it also depends on what kind of model you've used.

If you use a fixed effect or a random effects model,

I'm not going to discuss that now.

And this is your overall estimate, which is a weighted combination of the values from the above.

33:55  Slide 73

So that was a quick explanation of the forest plot.

So, so far, we have this patient,

nine-year-old boy, Class II, Division 1, mixed dentition,

We examine the patient, we use the clinical expertise, we discuss what is the best available evidence.

And the last thing in the last component is what does the patient want?

Because maybe we have nice things to do for our patient, but maybe the patient doesn't care.

So he's an important part of the equation.

34:30  Slide 74

Because maybe this boy doesn't care, maybe he does.

34:36  Slide 75

So how could I apply all that information that I gave you in my office and say we'll do evidence-based orthodontics in my office?

34:49  Slide 76

So I start again with a clinical expertise.

34:52  Slide 77

This boy comes in, I diagnose the case, and now I'm thinking, should I do something now, 9 years old, or should I wait till the patient gets all his permanent dentition in his mouth?

So that's my dilemma.

35:07  Slide 78

And I'm thinking, what are the advantages of doing something now?

Because that's the information you can also have to discuss with the parents of the patient.

Because at the end, as I said, they have to make the decision.

If I do something now, maybe the patient will feel better if the kids are making fun of him at school.

So you can improve the psychology and have an aesthetic improvement.

35:31  Slide 79

Perhaps you decrease the chance of the boy having an accident, because the boys are that age, they play football, they run around, and so they could fall and break their teeth.

35:46  Slide 80

What are the disadvantages, though?

If I start a patient at 9 years old, and then this patient would need full treatment, perhaps I will go up to 14, 15 years old.

So that's a prolonged period of intervention, which could also have some side effects, like white spot lesions.

36:10  Slide 81

Or maybe the patient will say, I had enough.

If the patient is tired, then the cooperation goes down, so maybe the treatment is not going very well.

36:22  Slide 82

It could also have higher cost.

But maybe for whom?

But maybe it's a good thing for us, but maybe not a good thing for a patient.

And this is my personal opinion.

I don't think it's a good idea to have too many young patients in your office that you could actually delay their treatment for later with similar, you know, results.

36:50  Slide 83

So I diagnosed the case.

I have my dilemma, should I go for one or two-stage treatment?

So the next component is, okay, what is the scientific evidence telling me?

Should I prefer one approach, the one-stage or the two-stage?

37:11  Slide 84

So now I'm looking at my patient and I'm starting, as I said before, with the PICO.

So I need to find a systematic review that looks at the participants who are similar with my patient in the characteristics in age and so forth.

And then I'm looking also at the types of interventions that I could apply, which would be doing something now or wait until the patient changes into a full dentition.

And also the outcome, which would be the reduction of the overjet, which would be of main importance and interest in this particular case.

37:50  Slide 85

So I go to PubMed and I go to Clinical Queries and I type "correction of upper prominent teeth".

37:58  Slide 86

And then I get a number of studies and then I pick up a Cochrane systematic review.

I think you're all familiar with Cochrane, it's a non-profit organization producing high-quality systematic reviews.

38:12  Slides 87-88

And then I find this systematic review.

They included 17 trials and 721 patients.

However, they looked at different outcomes.

38:26  Slide 89

So the conclusions were that there was a reduced risk of incisor trauma with early treatment.

So that's one positive thing if I do something now.

38:38  Slide 90

And this is the forest plot showing that.

However, you'll see they only have three studies.

They don't have as many patients.

But the evidence shows that it favors doing something now to decrease the risk of a patient at breaking his teeth.

38:55  Slide 91

The other important outcome was the reduction of the overjet, the occlusal outcomes.

38:58  Slide 92

Again, you see the forest plot. We have, again, three studies.

Now the conclusions are not so positive, they're about the same.

You see, there's a difference of 0.21 millimeters, which means if I do one method versus the other, my difference will be very small.

It's not statistically significant, but more importantly, it's not clinically important.

39:30  Slide 93

Therefore, my conclusions are that I can have a lower chance of breaking the teeth, but my outcome average of correction will be the same if I do one stage, if I wait for the patient, versus doing something now.

So we have now to weigh the advantages and the disadvantages of the one stage versus the two stage diagram.

39:56  Slide 94

So we have to balance what we call the cost and the benefit.

40:00  Slides 95-96

And now we have to bring in the third component from the equation, which will be the patient.

And then we're going to have to ask the patient, "Those are the pluses and the minuses, so then we're going to wait for them to give us their decision."

And perhaps the patient will say, "I don't care, I don't want to do that now."

Or they might say, "I care and I want to do it now."

40:27  Slide 97

And of course nowadays it's not easy to be a practitioner, because of everything that's going on.

40:37  Slide 98

We have all the new technologies, and of course we don't have the evidence.

40:44  Slide 99

We have to keep pace with the technology and also the evidence.

Now it's more complicated because to be able to understand systematic reviews, you have to understand methodology, you have to understand more statistics, and it's making it more difficult to make those decisions because we often lack this type of knowledge.

41:06  Slide 100

So that's the end of the first presentation.

That's a classic photograph of the island of Corfu.