Likelihood Ratios Explained
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- เผยแพร่เมื่อ 5 ก.ย. 2024
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This is not medical advice. The content is intended as educational content for health care professionals and students. If you are a patient, seek care of a health care professional. Kai explains in depth how to calculate likelihood rations using equations and the nomogram method. Pre-Test and Post-Test probabilities are also covered.
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thank you very much i will include you in my prayer every day
Very much appreciated Fatima!
Thank you for the explanation. I think using the nomogram to determin the post-test-probability is applicable in practice. But the accuracy of the result is totally depend on the therapists "guess" of the pre-test-probability. So what would you suggest to improve the accuracy of estimating the pre-test-probability? I'm pretty sure, that the "inter-tester-reliabilty" of the estimated pre-test-probabilty is really weak for most cases. How to train that skill? Can that estimation be evidence-based?
Hi Arne,
the challenge in clinical practice is that you don't have much literature on prevalence rates and on the validity of several items of your patient history.
So before a test you can only estimate how high the pre-test probability of a certain disease/pathology is.
Don't even think that a nomogram is applicable.
We find that the likelihood gives us the best estimate of how good a test is to confirm or exclude a certain hypothesis and after using the nomogram or calculating a couple of scenarios you have a pretty good feel of how much your post-test chance is influenced.
At the end of the day we will all have to learn to live with clinical uncertainty - we just have a better idea about how great that uncertainty is.
@@Physiotutors Wonderful answer that also applies to other areas of investigation as well as general measurement practices. Thanks for the extra insight!
Very informative, and concise. Thank you.
Cool, happy you like it Adil and thanks for subscribing.
Thanks a million for your hard work. This clip save my life.
Exam tomorrow and you just saved the day!
Good luck Melike!
you guys are awesome! really clear and reliable videos, keep it up!
Thanks a lot Ali, we certainly will!
The buff angel is on point as expected ;)
Really good explanation, thanks!
is there any information how the basic parameters are provide to calculate likehood ratio?
Thanks
Video is very nicely presented. Can you guide on how to estimate pre test probability?
You have to look into the literature how prevalent certain pathologies are in your country and setting. That's a good starting point.
Then signs & symptoms from your anamnesis will make a hypothesis less or more likely but it remains guesswork.
@@Physiotutors thank you.
Thomas Bayes has entered the chat.
Excellent !
thanks!
how did you set the pretest probabilty to 60%. is there any rule?
Very good, thanks for posting
Happy you like it David! No worries and thx for following us!
Thanks for making this topic so easy to understand great 👍
Ur welcome sharine
love you guys!
Thanks 🙏🏼 appreciate the love
In this lecture he says LR+ should be greater than 10 and LR- should be less than 0.1. But in practice the maximum values of both Sn and Sp is between 0 and 1 which further implies that LR+ cannot go beyond 10 and LR- cannot go less than 0.1. Kindly clarify this if someone can. Thank you.
Yes, the first part is correct. LR+ can go to unlimited and is good above 10, LR- can go towards 0 and is good below 0.1.
Sn and Sp can be a percentage (0-100%) or a decimal (0.00 - 1.0).
LR+ = Sn / (1-Sp)
LR- = (1-Sn) /Sp
Just fill in different examples (like shown in the video) and you will see how LR+ can exceed 10 and LR- can be lower than 0.1
Thank you so much. It works with your example.
LRs of 2 to 5 and 0.5 to 0.2 generate small (but sometimes important) changes in probability. EBM Manual JAMA evidence 2 Ed
you are a born teacher 🐣
What is the name for the formula of the PPV and NPV?
positive predictive value / negative
What is post-test probability?
The probability (%) of the pathology/disease being present after your test. It either goes up with a positive test or down with a negative test. The magnitude of the pre to post difference depends on the tests properties (e.g the likelihood ratio).
how can one sipmply say from history 60% of pretest ????
ich wollte nach LR-Test für die lineare Kombination von Parametern suchen...wieso bin ich hier gelandet....
ok... hab mir sogar zum Ende angeschaut...
Gwapo Mo
i dont understand shit
he is hot