all right guys so let's try to get started we got about 16 of these these uh questions these are the most ones you're most commonly going to see so uh let's get started and again when you when you study this just kind of go through the questions and in your head kind of watch this uh no sense in working them out over and over and over so just kind of watch these first one says a new test diagnose UTIs and women is being assessed the comparison gold standard is positive urine dipstick uh plus urine culture results are given so they're going to give you a chart like this two by two table they're going to ask you what is it what is a test specif sensitivity specificity positive predicted value or negative predictive value remember how it goes now here they're asking for specificity let's just go back to what we remember sensitivity you Circle here go down specificity here go up positive values this way negative predict values go this goes that way so you should have all the formulas just based on this now with specificity it's here you've recycled here and went up so on the top goes 180. on the bottom 180 plus 20. when we connected it you take both numbers okay so the specificity in that case is 180 over 200 you cancel out you get 9 over 10 and it's 90 percent if they said sensitivity we would have said we went here and go down so it's 40 over 40 plus 160 40 over 200 we start canceling and then we're looking at about 20 so in this case specificity was 90 answer Choice uh e the next one says a five-year study is planned to assess the incidence and ideology of respiratory disease in 600 individuals greater than 50 years of age study consists of two groups one cares for a pet dog the other one and second does not care for any animals in the household at the onset of respiratory symptoms cultures and serological studies will be performed which the following best describes the study so when we see a question like this basically they're going to ask they're going to try to see if you know the difference between case control and cohort and remember what we said case control has an A and an O So an A and an o two different things it's the most meaning like one person has a disease and one does not the other one is a cohort o and an o so basically both both sets of people start out without the disease so when you look at this problem they said they talk about these people that are 50 years old and then they're like well we're just looking at the ones who care for a dog and the ones who do not have animals so at the onset of this at the onset of the study both the 50 year old did not have the disease they're actually looking for it to happen in the future given these circumstances so in this situation they're actually looking for a cohort study remember oh and oh nobody has a disease initially now since it's like relatives right relatives look the same so when you see again so just remember when you see cohort you say relative risk when when you say case control you need to say odds ratio you just got to have that memorized okay they look the same they're relatives relative risk nobody has disease initially it can look it can go ahead and look forward and backwards now when someone has this disease and someone does not you think odds ratio case control and you really you only want to look backwards because we don't care about going forward on that one anymore it says a new study is to diagnose prostate cancer is being evaluated the sensitivity of the test is 70 and the specificity is 90. in the study there are 100 patients who truly truly have UTIs and two 200 is truly not how many false negatives are there in the study so when you skip this I didn't give you the chart initially so you got to create it so when if you ever get stuck you say what what do I know well I can always create a chart and I know up on top we always say reality goes there and when I say the test goes over here positive negative positive negative got to be able to label this now positive if the test is positive and the reality is positive that's a true positive test is negative reality it was negative it's a true negative so and everything is based on the test so if the test was negative and reality it was positive that's a false negative based on the test test was positive but in reality it was negative that's a false positive now what is this question says says the sensitivity test is 70 so we know sensitivity was this going down so we know here this is going to equal 70 somehow specificity is here going up so we know that's got to equal 90 percent so in the study there's a hundred patients who truly have UTIs so in reality a hundred patients actually had UTI so this category here is going to equal 100 patients and and 200 who truly do not so that in reality there's 200 people who do not have UTI so this little category goes here so it says how many false negatives are in this study so that'd be that number so I know that something over the total of a hundred something over this total of 100 equals 70 percent okay so what would that number be 70. correct so if we have 70 over 100 that gives us uh 70 percent but that's not what they asked to ask me how many false negatives so 70 plus the 30 equal 100. So my answer in this one how many false negatives this right here uh answer Choice C uh number 30. now if they if they were to ask false positives I would have said oh I know that ninety percent of 200 is is 180 and 180 plus 20 equals to 200. so if they would ask me how many false positives I could have just said 20 okay but you always go back once you write this table out I don't care what they give you you just work backwards and you can solve this now this one says uh basically says what type of study is being conducted uh being conducted and so again we're always always look back between cohort and case control for the most part everything else is pretty self-explanatory so it says a test is being conducted to determine if older students have a lower score uh on US money step one a group of students older a group of older students greater than 50 who took step one or compared to to a group of younger students who took step one data shown below so here's a two by two table and basically they're saying that you know there should be a better a better example here meaning more of a disease but here they're saying just a lower test score versus a normal test score older older person versus a younger person um so basically we already know that we already pretty much know the outcome in this so if we already know the outcome someone like say for example has disease and someone does not then that's what we called a case control now if we didn't already know the outcome in this not in this situation but if we didn't know the outcome we can actually go forward looking or backwards and that is considered a cohort study but in this situation we already know the outcome so basically it's the equivalent to saying someone has disease and someone is not so that one would be a case control now this is the same question but now the question is what is the odds ratio okay and again we knew that because it was said case control um would be we always think odds ratio you got to have that you may see a question that just say odds ratio and then you got to go back and say oh that's case control now when we when we say odds ratio we got to know this odds ratio versus relative risk think odds when you're in Vegas you think odds so it's one number over one number when you're when you say relative relative risk you got to think one number over two you got to keep that in mind odds you're in Vegas three to one odds two to one odds one number over one number relative risk one number over two you do that you get it right now when we read math problems we read them top to bottom left to right so you got to read this properly it says what is the odds ratio relative that of the younger student of older students having lower test scores so it's very important to understand they're asking older students compared to the younger so who's going to go on top you know who's gonna who's gonna be my uh my thing on top and that's going to be the older students so let's see older students and it's odds ratio it's one number over one number 60 over uh 200 over the younger the younger student 40 over 160 okay and that's going to answer Choice C now if this thing was different and it basically had a relative risk okay if it said relative visc it would look something like this it'd be one number over 2 60 over 60 plus 200 over 40. over 40 plus 160. very simple differential between those two just remember odds ratio one number over one number if it said relative risk one number over two okay you do that you get it right all right the next one it says that buy a marker is is being used for detection of a certain disease uh 500 healthy volunteers and 120 patients with a biomarker are used in the figure below so changing the cutoff value of the biomarker from point B to point a would most likely result in so again they're going to give you something like this some type of chart they're going to move the marker from A to B or B to a or they're just going to not give you this and say well I'm moving the cutoff from from 200 down to 100 or they can say moving up from 100 to 200 so bottom line is we're going to move it left from right to left or left to right okay now you have to label this properly and we said over to the left true negative over to the right true positive everybody keeps their last name so on this side right here if you keep your last name that's going to be a false negative and right here if you keep your last name right there it's going to be false positive now all we ever care about in these situations are the middle numbers I don't care about him I don't care about him because he he will not change okay for our purposes he will not change so it says change and cut off from B to a so if I'm moving this thing from B to a and remember always kind of think you're going to adjust this bottom line so if I move from B to a I'm actually going to smash that false negative so false alternate it goes down and if I move it from left to right or from B to a technically my you think this middle line goes this way and my fault's positive goes up okay now if it went from low to high the opposite occurs I'm smashing the false positive and increasing the false negative so they're only looking about uh well let's do this for lower sensitivity well what's my thing for sensitivity I'd go back and write my chart of of what I know reality test positive negative positive negative that's a true positive negative negative is a true negative everything's based on the test so that's a false negative everything's based on the test so that's a false positive so sensitivity okay we said sensitivity this going down so that's a true positive over true positive plus false negative okay so it'll be lower sensitivity so here the only thing that relates to this that's all I care about in this would be the false negative now false negative goes down but so if that number goes down the whole sensitivity actually would go up okay so it's not looking like it's a more true negatives but wait a second true negatives were out here and again we do not care about the true negatives or true positives in this scenario so as those things do not change for us more false negatives but we just talked about this if it goes from right to left it smashes the false negative so that's actually going to be incorrect higher negative predictive value now again we went back to that thing and we said sensitivity goes this place specificity that way positive predictive value negative predictive value so the formula for negative value is true negative over true negative plus false negative so so the false negatives in this area went down so if that goes down my negative predictive value actually would go up so that could be definitely an answer choice so I'm going to put a little Mark next to that or higher positive predictive value positive value is this guy going that way so the formula is true positive over true positive plus false positives that's positive predictive value now the only thing I care about is false positive and he actually went up so if the false positive goes up the whole number out here actually would go down so it's not that guy so the answer in this scenario is higher negative predictive value great question remember all you care about is the middle you got to label them correctly okay everybody keeps their last name that's how you know which side to put them on you're either going to slide them to the left or slide them to the right you're going to smash this guy or smash that guy if you smash the Lefty the right goes up you smash the right the left goes up that's all you care about right there okay the following graph shows just shows distribution values from it from a healthy group of volunteer and disease people points a through e represent various points for determining distinctions between these people we'll cut off point would determine a sensitivity of a hundred okay well what was our formula for sensitivity so again go back to our chart reality test positive negative positive negative true positive true negative everything's based on the test that's a false negative this one's a false positive so sensitivity is this guy so my formula is true positive over true positive plus false negative remember the bottom is two things whatever thing I connect the line you write both of them down there for the bottom all right so to make this a hundred percent that means I got to get this guy actually he's got to become basically a zero so if I notice he's a zero my sensitivity will be a hundred percent so where in this chart would I find the false negatives being zero well let's just label the chart we know that's a true negative this is a true positive and then all I care about is in the center I gotta label them correctly that's a false negative and this is a false positive so where do we make him zero where can I smash this guy and make it make the false negative a zero I slid them all the way right here Point C now if they they said what is the specificity well I would say oh that's specificity true true negative over two negative plus false positive where can I make the false positive zero where can I make him zero oh if I smashed him this way and then so the specificity would be Choice e all right so what will happen to the sensitivity and specificity um of a test when the markers are moved from the blue curve to the red curve so from the blue to the red or pink whatever you see here and again you see the scenario all I care about is the inside I don't care anything about this true negative I mean true negative uh true positive so here I do my draw my line so on this side it was actually the false negative and on this side it was actually the false positive but going from the blue from the blue to the blue to the pink the area under this actually went down it went this way so the so it's going from here smaller so the false negatives got smaller it went down and in the false positives got smaller so now all I care about I got is plug this back into my formulas okay and so all I'm looking for sensitivity and specificity back to what I know positive negative positive negative reality test true positive true negative everything's based on the test so it's a false negative this one is a false positive so sensitivity goes this way specificity goes that way so sensitivity positive plus false negative and specificity is true negative right here going up true negative plus false uh positive so on both these scenarios in both those situations the false negative false policy went down so the false negative goes down so if he goes down the this whole number gets bigger so sensitivity goes up false positive he went down so if that number goes down the whole number goes up so in this situation when we went from this the blue to the pink the area under the curve got smaller for both of those guys smaller if both those get smaller it's a higher sensitivity and a higher specificity all go back to our formulas you got to know this okay but all we care about in this situation is the center I don't care about him I don't care about him checking blood pressure to health fair would be an example of what type of prevention okay this can come up pretty easily just make sure you know these first two okay primary primary prevention some like immunizations and then secondary prevention is something like when you're trying to screen for this stuff such as checking blood pressure it would be an in a scenario where you use second is secondary prevention so I kind of know these um you know just kind of read through them if you get a chance primary again education immunization before the thing happens secondary screen for disease early to reduce the impact those are your two main ones basically make sure you know those okay and let me see here we talked about the uh case fatality again when I say Kate when it says case break case rate all I care about is the case they're talking about so it says the table shows distribution of spinal cord injuries and death what is the case fatality for Falls okay so case fatality for Falls so I don't care about anything else except fall so case fatality here's number of fatal ones here's number total case fatality Falls how many Falls total 20. how many of those were actually fatal four so case fatality for Falls was four out of 20. okay just make sure you understand that they're staying within that category they're not asking about anybody anything about this number this number any of that stuff case fatality Falls 4 out of 20. a new instrument is purchased by the hospital to check serum levels of of some type of uh x uh the published value for the standard is 40 the technologist runs the tests on patients and gets readings of 70 68 70 17 75 respectively what can we conclude about this instrument all right so the average they're asking about two things they're asking about accuracy and precision now you know if this was a bullseye you know act you know accuracy if they're going to give you something that says to determine accuracy they got to give you a gold standard so with accuracy you got to have some type of marker or uh or gold standard some type of reference to know if you're hit if you can't hit the bullseye so in a bullseye they go the gold standard is going to be the center of the target so if you hit around this you know obviously you know you're if you're getting close to the mark You're accurate okay as long as you're close to the mark You're accurate now with Precision you know you're just in the same area okay that's all you just want to make sure you're pretty pretty tight with that okay so with accuracy you got to have some type of goal Center to measure Yourself by with precision you know you just kind of be in the same area so in a situation like this where the standard is 40 yet this guy's hitting these readings with 70 60 uh 72 75 so he's pretty tight in this region so this guy is pretty precise but when you reference him next to what the gold standard is he's not very accurate so in this situation he's precise but not accurate answer Choice B all right new study showed that the mean HDL level of a non-diabetic patient was 42 and that the mean HDO level in diabetic was 35 probably this was due to chance was .05 okay there's also a 15 probability that there is no difference in the HDL measurement when their reality was one so first thing because what is the p-value of study what's p-value mean basically you got to think of p-value just says what is the you know chance of it happening Happening by chance okay and in this situation they actually gave it to you probability this was due to chance was 0.05 or change that five percent and remember for uh for a study to be actually a good study uh it's got to be either point or less okay so .04 is that a good study yes because it's less than .05 is point zero uh six a good study we're going to say no because the rule says it's got to be .05 or less okay or less not higher what is the power of the study well this gets back to the whole null hypothesis stuff so when we draw out our null hypothesis you know we still stick with our reality over here um I always like to do just the text and stick with tests but it's whatever situation it is okay now we gotta label it correctly one and an o one and an O and it's all no is the null okay that's the null hypothesis so no meaning there is no association okay so let's fill out our Charter what we know so if if the test says there is an association but in reality there is no association that's called an alpha error okay alpha Air type 1. again the test says there is an association but in reality there was not one that's an alpha error now the tester situation says there is no association but in reality there was one that's called a beta okay beta or type two error okay and it's all based on Words you've got to know how to First write this out 100 reality in the test and now you got to put this into words Fancy on you got to know this in word so again if there if the test says there was no association but in reality there was one beta error okay beta error if there is an association reality was not Alpha error now how do I find this one right here whether it says well yeah there is an association reality there is one how do I find that it's one minus beta also known as power if you can write out this if you can draw out this you can answer any question they're going to ask you pretty much on step one when it comes to the null hypothesis but you got to know what it means in words okay so it says what is the power of the study so we want to know what this box is right here so how do I find that well let's see what they gave me they said that there is there's also a 15 probability of concluding that there is no difference in the HDL measurement when in reality there is one again 50 is probably a complaint there is no difference we're going to try to conclude in the issue measurement when there is one in reality so they're saying there is no difference when a reality there was one there's a 15 probability of that happening well what do I got to do I take one that was Betos to the 0.15 so 1 minus the 0.15 it's going to be 0.85 and that's and that's actually going to be my power okay answer Choice C but you got to be able to write this box out okay um and then this is just the most common question just like with just like we did it right here this is the most common question they're going to ask that you can understand that this in words actually means the beta box okay and so one one minus that that's your answer okay now the prevalence the prevalence of prostate cancer compared in two groups of men and the following data was obtained based on this data was relative risk okay bottom line relative risk and when we when we read math problems read them top to bottom left to right a deal on a prostate cancer in men who had no children compared to men who had children so we got to compare men who had no children to the ones who did so who's going to go on top The Men Who had no children now it's relative risk now we said odds ratio we go one number over one number if I said relative risk it's one number over two okay so relative risk of No Children compared to men who had it so no children so that was going to be 80 over 80 plus 920 because it's one number over two because it's relative risk compared to the men you had who've had children 220 over 220 plus uh one two eight zero okay now again at this at odds ratio I would have just went 80 and odds ratio in this scenario I went 80 over 920. over 220 over one two eight zero okay but since it's relative risk one number over two over one number over two Gotta Know It All right so then if we kind of uh kind of whittled that down 220 over 1500 I mean we can kind of you know do the math here hopefully they'll give you a a lot easier uh scenario 220 now you can cancel out a lot of stuff so if we didn't do that by 500 that's three two again if I did by 10. 44 we're almost looking you know looking close to about 50 uh roughly 55 uh percent all right very good scatter uh scatter diagram shows correlation between alcohol consumption and test scores all right so you're going to get a scenario like this and either the scenario is going to be going like this way and you just gotta look at the dots and draw whatever line you think would most match where this thing's going okay so in this situation it's that way if it was like this it would be that way now if it's going in this way it's like as you're as you uh drink more alcohol okay if you drink more alcohol your test score is going to go down okay so that's called that's so this is going to be a negative association okay I'm just using negative one because basically it's basically saying that if I go over one I can also go up one it's a one to one ratio the line looks like it's one to one I go over one up one it's equal to negative one in a situation like this the more I study uh so the more I study the higher my test score again over one up one or or up one um over one it's a one to one ratio and then you can kind of go from there now in this situation for this answer it would have been negative one but you got to be able to understand if it was negative point two the slope would be a little bit bigger if it was a it was if it was a positive 0.2 it is slope would be a little bit um flatter so for right now just understand negative association positive Association and then understand the slopes can be a little bit less if it's one of these numbers all right last one it says a study of 200 patients 200 patients in a hospital uh Patients Hospital patients blah blah with complications related to pneumonia show their serum cholesterol level is normally distributed variable with a mean of 210 standard deviation of 15 based on the study how many patients would you expect to have cholesterol greater than 240. all right um so it's just standard deviation stuff so when in doubt just kind of write out what you know so there's a standard deviation curve it says there's 200 people in the study they mean a 210 so we know the mean is 210. standard deviation is 15. now we know one standard deviation is 68 we know two standard deviations is 95 percent what three standard deviations what is it 99.7 all right so you basically have to have this memorized now they love this one that's 95 um just because it's a nice number uh they know you can use it the 95 a lot easier you can use 68 but you got into this one is 68 2 is 95. now uh in a standard deviation of 15. so basically it's what they're saying is if they come out 15 points 15 points going down is going to be 195 and that 15 points going up is going to be 225 and basically that's saying between 195 and 225 there should be that's one standard deviation there's 68 of the people should be in this in between here now the question on this one says based on the study how many patients how many patients would you expect to have cholesterol greater than 240 okay uh here I got to get to 240. okay well I can see what they're doing here so if one standard deviation was adding 15. so another standard deviation another deviation out will be adding 15. so they're basically looking at two DB two standard deviations so I'm adding 15 and that takes me to 240. I could minus 15 and that's going to take me to 180. so what that's saying is now in here between all this I should have 95 percent of the people should be within this range so again back to the question it says how many patients would you expect to have cholesterol greater than 240. so really all we're looking at in this whole problem is the number of people that are out here going this way so let's look at what we know we know 95 there's 200 people in here 95 percent are contained in here so if I had 200 and if I did 95 okay so I know 90 is 180 200 so that should be about a hundred and ninety so 190 people are in the center here so that leaves how many that leaves 10 that aren't so 10 should make up the outer edges but again they're going to they would try to trick you on this and you know they want they want everybody to buy it on this 10 but that's not the answer because the question so how many patients would you expect to have cholesterol greater than 240. so if there's 10 left I got to put 5 on this side 5 on that side so the answer was greater than 240 would be five not the 10. so again when you study this you know obviously you just want to go through these just real fast and know the concept this is pretty much the the meat maintain is what you'll see on step one um just kind of go through these and I think you'll do well well on the test so hope this helped guys we'll see you later