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Flashcards in Biostats Deck (18)
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1
Q

Measures the frequency of disease at a particular point in time

A

Cross-sectional study

*Only established prevalence, not causality

2
Q

Measures the frequency with which twins develop the same disease

A

Twin concordance study

-Pretty self-explanatory

3
Q

Clinical Trial Phases

A

I- Is it safe? (toxicity, pharmacokinetics)

II- Does it work? (treatment effficacy, ADRs)

III- Is it as good or better? (compares)

IV- Can it stay? (rare or long-term effects; “post-distribution surveillance”)

4
Q

Odds Ratio

A

OR= ad/bc (a/c)/(b/d)

Represents the odds that the group with the disease was exposed to a risk factor DIVIDED BY the odds that the group without the disease was exposed

5
Q

Relative Risk

A

RR= [a/(a+b)]/[c/(c+d)]

Represents the risk of developing disease in the exposed group DIVIDED BY the risk in the unexposed group

Example= If 21% of smokers develop lung cancer vs. 1% of nonsmokers, RR=21/1

6
Q

Attributable risk

A

AR= [a/a+b]-[c/c+d]

Represents the difference in risk between exposed and unexposed groups

or the proportion of disease occurrences attributable to exposure

example= if risk of lung cancer in smokers is 21% and risk in nonsmokers is 20%, AR= 20%

7
Q

Relative Risk Reduction

A

RRR=1-RR

Represents the proportion of risk reduction attributable to the intervention as compared to control (1)

Example= If 2% of pts. who receive a flu shot develop the flu while 8% who don’t develop the flu, then RR=2/8=.25 and RRR=1-.25=.75

8
Q

Absolute Risk Reduction

A

AFF= c/c+d - a/a+b

Represents the difference in risk attributable to the intervention as compared to the control

Example= If 8% of people who receive a placebo vaccine develop the flu while 2 % who receive a flu vaccin due, ARR= 8%-2%= 6%

9
Q

Number needed to treat

A

NNT=1/ARR

Represents the number of patients who need to be treated for 1 patient to benefit

10
Q

Number needed to harm

A

NNH= 1/AR

Represents the number of pts. who need to be exposed for 1 patient to be harmed

11
Q

Berkson bias

A

Study population selected is less healthy than the general population

Is a form of selection bias

12
Q

Confounding bias

A

When one factor is related to both exposure and outcome but no on the pathway =» distortion of observable effect of exposure

Example= Coal miners more commonly have pulmonary disease BUT they also more frequently are smokers

Fix? - Multiple studies, crossover studies

13
Q

Standard Error

A

SE= SD/n^1/2

Represents an estimate of how much variability exists b/w the ample mean and the true population

14
Q

Ways to decrease Type II error

A

Increase sample size

Increase expected effect size

Increases precision of measurements

15
Q

Confidence interval calculation

A

CI= mean +/- Z(SE)

95% CI, Z=1.96

99% CI, Z= 2.58

16
Q

What happens to calcium concentrations in alkalosis?

A

They decrease due to increased protein binding to Ca2+

17
Q

Lymphatic drainage of the leg

A

Lateral foot and posterior leg =» Popliteal nodes

Medial foot and leg =» Superficial inguinal nodes

18
Q

GLP-1 analogs

A

Exenatide, Liraglutide

  • Increase insulin and decrease glucagon release
  • Can only be used in Type II DM