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And just uh okay. Yeah, that's historian conditions. Okay. She is. Yeah, really? Thanks George. Okay. So you speak about levels of evidence, but it looked a bit about as to what exists a bit of history. Um understand a bit more about the levels themselves, uh what they're useful and recommendations and considerations. So why do they exist? Well, clinicians and researchers busy people as we all know. Uh And if you imagine as for the Oxford uh Center for Evidence Based Medicine website, you have the Schematic and they say choose what type of research you're going to use to answer your questions or where do you begin? That could be for any question that you're looking into. So you can get 2000 plus articles, seven RCTS, 300 cohort studies. But what is the best thing for your question? Uh As prof candies you mentioned this morning, um Evidence based medicine is the cornerstone of our practice. Uh The definition is right there. And ultimately, it's about providing a hierarchal system of classifying evidence so we can make good decisions for our patient's, it's a bit of history. Um The Canadian task force in 1979 wanted to characterize the level of evidence, underlying health care recommendations and the strength of recommendations. And so they came up with this initial um organization of levels, as you can see our ct at the top expert opinions at level three, so look shorter than what we're used to. Nowadays, Sackett then subsequently expanded upon this when looking for anti thrombotic agents. Uh and he kind of increased it to 12345. And as you can see our cities at the top and case series at the bottom, and this is simply based on the study design and then theoretically the amount of bias as per what profit you you mentioned this morning in terms of the different studies having different types of bias levels. However, different questions exist, different medics or different questions in different ways. And so it depends on what you're asking and what you're studying and looking into. So treatment research is very different too. You're looking at prognostic research or diagnostic research and even economic analyses. And so this is where modifications were made. And so if you look at the top left prognostic studies, uh you know, the highest level for them, you could argue is a cohort study which is prospective uh as opposed to on the bottom, right, which is for therapeutic studies. And that's something most of us probably familiar with from medical school. Um You'll see the triangle versi, but that is basically the triangle that we're all familiar with where you have one A BC, 23, etcetera. And as you can see, for therapeutic studies, a systematic review of our CTS or meta analysis is probably a lot more useful as we probably would all agree. So the triangle, as I promised, now, there are loads of triangles. When you Google this, there's so many different triangles you sit there and think well, which one should I use? But essentially they're always at the top, you have met analyses and systematic reviews going all the way down towards uh expert opinion. And it's to do with the design of the study I level of bias. But also the fact that the top studies are more filtered as someone's going through the data, analyzed it thoroughly as opposed to the bottom ones which are considered unfiltered, the other ways of summarizing it as Mr Kumar mentioned before experimental studies, observational studies, etcetera. But that is what we're familiar with. But you see this only tells you that study design and surely the design of the study by itself cannot just be enough. You have to look at the study itself. I'm not gonna go through these slides because in the interest of time, but essentially is what Mr Kumar and prop can use. And everyone has kind of mentioned the benefits and negative negative points for each type of study. This is probably key to understand, to understand the level of evidence. Um but as I said, Mr Kumar already gone through it. So it's all about bias and understanding the pros and cons of these studies. Uh Okay. So the Oxford Center for Evidence Based Medicine is probably the most useful one that we all are familiar with. So first developed in sort of 2000, September subsequently has been revised, many original evidence ranking systems as I showed you before, from seventies and eighties were essentially just looking at therapy and prevention. However, a team from Oxford decided we need to look into this and identify what research should be looked at for prognostic studies, uh diagnostic studies, etcetera. And so they came up with this is the most recent table 2011 1. So let's go through this. So if you look at it instead of a triangle, they essentially created a table which is probably a lot more useful. Um So if you look at the left hand column under question, they've imagined the clinician has a condition in front of them and they want to understand the epidemiology all the way to treatment uh and beyond. So if you look the first question is how common is a problem? It makes a lot of logical sense, doesn't it? And then you work your way down on the left. So that from the next column onwards on the left is the highest level of evidence for that type of question type, moving all the way to the right, which is the least amount of uh least uh evidence. Um If you also notice that the topic says level 12345, not one A BC. So from 2009 to 2011, what they did was they revamp this and they made it simplified because they thought all these subdivisions just gets a bit confusing for conditions. So that's one of the benefits um going forward. We're looking at the literature. They suggest that actually if you look at the treatment question because that's probably the question most of us will look at and be interested in. It's not just um what will happen if we do not add a therapy or sorry, apologies. Um What does this intervention help? It should be more, does this intervention help and compared to its alternatives, what are the risk and benefits of this as well as the alternatives? And that is the next sort of iteration that might include that in terms of the table and that will evolve things such as um brother reviews where you take all the evidence and really compare everything against everything, which is a much more holistic and overview, a bigger overview you could say. Of note, this is not just simply the study design and these guys are moving more towards quality of the study as well. So if you look at the bottom left, uh sorry, but the bottom with the single asterix, it says level maybe ground graded down on the basis of study quality imprecision in directness, etcetera. So how the person is conducted, study matters as well as what type of study. So on the quality of evidence, essentially, you got your RCT and we all think that must be great that actually you got to look at the type of errors, the power. So a low powered study might miss a significant difference between to um, sort of interventions of medications or surgery. So they're our scales out there such as Jada Deskee scale, etcetera, uh which assess all CTS and tell you how good they are. And therefore consideration when you're looking at papers, etcetera should also include, you know, the blinding process randomization, um confidence intervals, etcetera, things you do when you uh analyze the paper and journal club, for example. So a couple of studies that just kind of looked into this. So Vandalia al this is from 2000 to looked at the RCTS and the JBJS. And out of 2468 studies, 72 were considered our CTS. They're to investigators who use a scale with 14 parameters on it and the average score was 68. Now, an excellent score is above 75. And at that period of time between 1988 to 2000, these two assessors who had a good inter observer availability, they basically found that 60% of studies had a score less than 75. So that's quite a considerable number of studies are not considered, you know, excellently done. And the conclusion was it was mainly due to lack of appropriate randomization, blinding, etcetera. And they suggested using a much more standardized approach in reporting are CTS. And as mentioned earlier this morning, the contour statement is something that's used nowadays. So this is where you know, assessing the quality can make improvements. Similarly, Poo Manal looked at the evidence rating as documented by the authors and the Cochran reporting quality school between 2003, 2004 and 32 studies were found to be our CTS out of over 900 to investigators. And what they essentially summarized was that you should not assume that a level one is truly a level one and then a level one and level two that there's that much difference between the two. So it's worth again looking at the quality, not just the type of study itself. So how are these levels of study evidence use? So, you know, you've got them, we essentially get told, okay, look at your systematic reviews, look at your meta analysis, that's fine. But in terms of, you know, in the bigger picture for healthcare delivery, um it's all about recommendations and providing clinical guidelines. So the Center for Evidence Based Medicine, they've got a recommendation system where because they look at the quality of the evidence as well, they give you a BCD and that's based upon the type of levels. Uh So for example, consistent level one studies which obviously are considered level one truly and good uh you know, the recommendations given a a and therefore, as conditions, it's a lot easier than to go, you know. Well, I'll use this type of treatment because there's a good amount of uh evidence behind it. Similarly, there's an alternative called Great, which is grading of recommendations, assessment development and evaluations. The BMJ uh summarizes is being a transparent framework for developing and presenting summaries of evidence and provide a systematic approach for making clinical practice recommendations. Again, and RCTS assumed once again to be the highest level of evidence and observation studies are considered lower. But as you can see from this uh table there, um thing, you know, studies can go up and down. So again, it's all about looking at the quality and not just assuming that just because it's an RCT, it will definitely be worth following what they find. And as I think Profit mcdonald mentioned earlier, if you've got one study that's an RCT, you know, is that enough? Surely you need to have a few to really confirm findings and this is what they essentially do. They take that data and then they say give a certainty recommendation as to how certain they are, that the authors have confidence that the true effect is um similar to the estimated effect. So go back to triangles which you know, is what we assume when we think about levels of evidence. So top left a is what we've probably been taught all our lives. And what we still get taught be is probably what Morada I'll suggest is the great system I we take away the systematic reviews, which is what they use by the way to grade the, the findings. But the wavy lines essentially represent the fact that things can move up and down. This whole world is fluid. It's not, it's not stagnant. And then see is what they suggest that maybe we should be taking the systematic reviews, but then taking it and using a magnifying glass to really uh look at the quality in more detail between these studies and allow things to move up and down. So finally, considerations, well, Oxford Group can suggest these, you should not assume obviously that the levels provide a definitive judgment about the quality of evidence need to look into yourself. Remember that Pullman paper where you know, a lot of level ones were not true level ones. Uh the type of question availability of research need to be considered, you need to make sure you're asking the right question back to Mr Kumar's uh presentation, you know, just because the cinematic review answers a question does not mean it's your question. And you must consider your patient suitability, the treatment itself and alternatives and what's best for that patient between the risk and benefit um profile. So final site um I would say this is something I read when I was looking at the Oxford website and it comes like a disclaimer. They say just before you read or use their evidence levels, they say no evidence wrapping system or decision to it can be used without a healthy dose of judgment and thought. And that's key your experience, your understanding of the condition as well as your understanding of the quality of data matches as much as just looking and saying, oh, that's a level, you know, to study. It must be great. Thank you.