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21 Cards in this Set
- Front
- Back
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What is Pre-test Probability? |
1. The probability of the target condition being present before the results of a diagnostic test are known. |
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What are Pre-test Odds? |
1. Odds that the patient has the target disorder before a diagnostic test is carried out. |
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What is Post-test Probability? |
1. Probability of the target condition being present after the results of a diagnostic test are known. |
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What are post-test Odds? How is it calculated? |
1. Odds that the patient has the target disorder after the test is carried out. Post-test odds= (Pre-test Odds X Likelihood Ratio) |
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What is the difference between probability and odds? Explain. |
1. Prob= Count(x)/TotalCount *The Ratio of Observed over total options 2. Odds= Count(x)/(Total Count - count(x)) *Ratio of Success to failure |
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What are the conversions between odds and probability? |
1. Odds=Pr/(1-Pr) 2. Pr= Odds/(1+Odds) |
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What is sensitivity? |
1. The proportion of people who truly have a designated disorder who are so identified by the test. 2. Sensitivity tests have few false negatives *SnOUT= Test with high sensitivity is Negative, rule out the diagnosis. |
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What is specificity? |
1. The proportion of people who are truly free of a designated disorder who are so identified by a test. 2. Specific Tests have few false positives *SpIN= WHen a test is highly Specific, a Positive result can rule in the diagnosis. |
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What is the equation for sensitivity (Sn)? |
Sn= True Positives/(True Positives + False Negatives) # of people correctly caught by the test over that number plus those that should have been caught. |
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What is the equation for selectivity (Sp)? |
Sp= True Negatives/(True Negatives + False Positives) # of people correctly shown to not have the disease over that number plus those that were shown to have the disease but really didnt. |
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Use the table to explain Sensitivity and Specificity. |
1. Sn=a/(a+c) 2. Sp=d/(d+b) |
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Among women without breast cancer the clinical breast exam correctly identifies 94% as not having breast cancer. What term describes this finding?
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1. Specificity *Always considered with identifying correctly those without the disease |
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At age 40 approximately 1 in every 800 women will develop breast cancer within one year? What term describes this statement? |
1. Incidence ***Always has a time increment |
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The clinical breast exam is able to correctly detect 54% of all women with breast cancer. What term describes this finding best? |
1. Sensitivity ***Always concerned with correctly detecting those with a condition. |
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What is a Positive Predictive Value? What is the equation? |
1. Proportion of people with positive test results who have the disorder. PPV= a/(a+b) PPV= True Positives/(True Positives + False Positives) |
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What is the Negative Predictive Value? What is the equation? |
1. The proportion of people with negative test results who are free of the disorder. NPV= d/(d+c) NPV= True Negatives/(True Negatives + False Negatives) |
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What is a likelihood ratio and how is it determined? |
1. Relative likelihood that a given test result would be expected in a patient with (as opposed to one without) a disorder of interest. |
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Using the table, how are Positive and Negative Likelihood Ratios Determined? |
LR+= True Positive Rate/False Positive Rate LR-= False Negative Rate/True Negative Rate |
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What are the significant numbers for a likelihood ratio to affect the probability of disease? |
1. LR>10= Disease More Likely (3-10) 2. LR<0.10= Disease is Less Likely (0.3-0.1) *LR=1 is no effect on likelihood |
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Memorize this Table |
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