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Exams >>
MCQ/EMQ
Imaging and Technology EMQ 1
Created: 5/1/2008
Updated: 11/1/2008
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Radiology and radiopharmaceuticals
A
Diethylene triamine pentaacetic acid
B CTKUB
C CT Urogram
D
Mercapto Acetyl Tri Glycine
E Dimercaptosuccinic acid
F Mag 3 Renogram
G 99 Technetium
H IVU
I Chest xray
J 123 Iodine
K IHippuran
L Abdominal xray
M 131 Iodine
1 Effective dose of 4.7 mSv
2 Effective dose of 5.2 mSv
3 Equal to a background radiation dose of approximately 10 days
4 Localises to the proximal convoluted tubule
5 Has a halflife of 6 hours
6 Effective dose of 44 mSv
7 Handled mostly by tubular secretion
8 Equal to a background radiation dose of approximately 6 months
9 GFR dependant for clearance
Statistics
The table below gives the diagnostic performance of a test in a population of 1000 people
Disease positive
Disease negative
Totals
Test positive
90
180
270
Test negative
10
720
730
Totals
100
900
1000
A 80%
B 66%
C 6.5
D 33%
E 10%
F 4.5
G 99%
H 10
I 12.5
J 50%
K 25%
L 90%
10 What is the specificity of the test?
11 What is the positive predictive value?
12 What is the sensitivity of the test?
13 What is the likelihood ratio for a positive test?
14 What is the negative predictive value?
Statistics continued??!!!?
A Type I error
B Sensitivity
C Null hypothesis
E Specificity
F Positive predictive value
G Alternative hypothesis
H Type II error
H Power
I Confidence interval
J Median
15 Assumes no difference exists between 2 groups being studied
16 Refers to the proportion of those patients with a positive test who actually have the condition
17 Also referred to as an alpha error
18 Rejection of the null hypothesis when it is true
19 The ability of a test to correctly identify patients with the disease
20 Accepting the null hypothesis when it is false
Answers
1B 2F 3I 4E 5G 6C 7F 8H
10A 80% (720/900)
11D 33% (90/270)
12L 90% (90/100)
13F 4.5 (90/270)/(180/900)
likelihood ratio is the likelihood that a given test result would be expected in a patient with a disorder compared to the likelihood that that same result would occur in a patient without the target disorder
14G 99% (720/730)
Disease positive
Disease negative
Totals
Test positive
a
b
a + b
Test negative
c
d
c + d
Totals
a+c
d + b
sensitivity a/(a+c)
specificity d/(d+b)
PPV a/(a+b)
NPV d/(c+d)
15C The null hypothesis assumes there no difference exists between the groups being studied whereas the alternative hypothesis assumes a difference does exist between the groups being studied
16F The positive predictive value refers to the proportion of those patients with a positive test who actually have the condition whereas the negative predictive value refers to the proportion of those patients with a negative test who do not have the condition
17A Alpha error refers to a type I error and beta error refers to type II error
18A Type I error occurs when the null hypothesis is incorrectly rejected and there is no difference between the groups whereas a type II error occurs when the null hypothesis is incorrectly accepted when in fact there is a difference between the groups being studied
19B Sensitivity refers to the ability of a test to correctly identify patients with the disease whereas the specificity refers to the ability of a test to correctly identify those patients without the disease
20H See above for explanation
UrologyUk comment: It is always difficult to remember some of the statistical definitions, however they do come up. Look them up the night before the exam  both written and viva sections.
Another area which causes problems is the
power of a study
:
The power of a study refers to its ability to reject the null hypothesis when it is in fact false ie. it is the abililty of
not
committing a type II error
Its is given by 1  beta and has a value between 0 and 1  1 is max and 0 is min  the closer to 1 the better
ArticleDate:20080105
SiteSection: Article
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