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USLME Kiss my ass and pray > Biostats > Flashcards

Flashcards in Biostats Deck (81):
1

APGAR

Appearance
Pulse
Grimace
Activity
Respiration

1 and 5 min
>7 good, 4-6 assist, < 4 resuscitate

2

Sensitivity

TP/(TP +FN)

-set up a 2x2
Sensitivity rules out - If negative, very likely not going have. Too sensitive of a test you are going to have many false positives.

3

Specificity

TN/(TN+FP)

Sp -in rules in. If positive likely positive test

4

1-statisitcal power =

Type II error

5

Odds ratios are calculated in what type of study

Case control

6

Relative risks are calculated in what type of study

Cohort studies

7

How does odds ratio relate to Relative risk?

Odds ratio is an approximation of relative risk because you cannot know the entire population in a case control. In a cohort the population is defined and risks can be calculated

8

Case control study is looking for what?

looking for risk factors and exposures that are in common in a group of people with a disease in comparison to those without the disease

it is retrospective and observational

9

Cohort study is looking for what

it is comparing those that have an exposure or risk to those without and seeing what becomes of it

It is observational and can be prospective or retrospective (form a cohort after an exposure and follow then)

10

Cross sectional study gives what about a disease

the prevalence

a snapshot in time of those that have the disease, can start looking at associations w/ risks to determine correlations

11

Twin concordance studies measures what?

heritability

12

Clinical trials can be improved w/ what 3 design strengtheners

Control group
Randomization
Double blind

13

Phase I of a drug trial asks

Is it safe

Tests on healthy people for toxicity and pharmacodinamics

14

Phase II of a drug trial asks

Does it work

Test on sick people for efficacy, dosing and adverse effects

15

Phase III of a drug trial asks

Does it work better

Large #s of people and clinical trials

16

Phase IV of a drug trial asks

What else can go wrong?

Post market surveillance

17

Meta analalysis

Pooling together of different studies based in inclusion criteria to gain statistical power

-some selection bias and concern for individual merits of the studies

18

Sensitivity tests what?

Formula

Sensitivity tests proportion of those that test positive to the disease and compares to ALL that have the disease

TP/(TP + FN)

19

Specificity Tests what?

Formula

Specificity tests the proportion those that test negative to the disease compared to ALL those that do not have the disease

TN/(TN+FP)

20

Positive predictive value tests what?

Formula

PPV compares those that test positive and actually have the disease to the the proportion of ALL those that test positive to the disease

TP/(TP and FP)

21

negative predictive value tests what?

Formula

NPV compares those that are actually disease free to the proportion of ALL those that test negative to the disease

TN/(TN + FP)

22

How does Specificity and sensitivity change with prevalence?

They don't. Specificity and specificity are limited to the categories of those that either have the disease or don't.

23

How does PPV and NPV change with prevalence?

With increased prevalence the PPV increases and NPV decreases.
-testing in an area where there is a lot of disease you are more likely to believe a positive test over a negative test

With a decrease in prevalence, the PPV decreases and NPV increases.
-Testing in an area where there is not a lot of disease. more likely to believe the negative test than the positive test

24

Given only the false negative %, what is the sensitivity?

1 - FN

25

1 - False Positive% =

Specificity

26

Which test do you use to screen for and which do you use to confirm?

you screen with a highly sensitive test because you want to catch all the positives. May have some FP.

You you then run a high specific test which is looking for those that are negative(Specific tests are those comparing those that are truly neg compared to all those that test negative); if you test negative you are negative in the disease and eliminates FP from the sensitive screen

27

what is incidence?

Formula

Incidence is the amount of new cases found in a population at risk

# of cases/those at risk (minus those w/ disease)

28

what is prevalence?

Formula

prevalence is the amount of people with a disease (all cases) in a population at risk

# of existing cases /population at risk

29

How does time course of an illness affect prevalence and incidnce

incidence = prevelence x time course

The shorter the disease duration the smaller the prevalence. Ex: the flu

Chronic disease may have a low incidence but a high prevalence (COPD, DM)

30

ODDs ratio

formula?

odds ratio is the odds that a group exposed to a risk will develop the disease compared to those that are not exposes - case studies

(a/b)/(c/d)

31

Relative risk

formula

RR is the incidence of a disease in a population exposed to a risk divided by the incidence of a disease in those not exposed - Cohort

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

RR -> OR when the prevalence of the disease is really small ( a and c are minuscule)

32

Attributable Risk is ?

Formula

Associated w?

the difference between incidence of those that are exposed to a risk with a disease compared to those that are not exposed

a/(a+b) - c/(c+d)

Associated w/ Number needed to harm which is 1/AR

33

Absolute risk reduction is?

Formula?

Associated w?

the difference between the incidence of the disease in those NOT exposed to a Rx to compared to those that are

c/(c+d) - a/(a+b)

Associated with number needed to treat
1/ARR

34

Number needed to treat

Determines the cost effectiveness of a treatment. Number of people that get treatment before having one positive effect

1/Absolute risk reduction

1 / [c/(c+d) - a/(a+b)]

35

Number needed to harm

determines the number of people needed to be exposed to a risk before before disease

1/ Attributable Risk

1 / [a/(a+b) - c/(c+d)]

36

precision is

the reproducibility/repeatability of a test

May not be accurate

37

Accuracy is?

the truthfulness of a test

may not be precise/reproducible

38

Selection bias

nonrandom assignment to participation in study
-ex may be those reffered to a study are closer to end stage disease

39

Berkons bias

subtype of selection bias where selection of patents are more likely to be hospitalized

- selection skewed since those selected were more likely to be hospitalized anyways

40

Recall bias

knowledge of a disorder impacts the ability to recall detail for a study

Ex parents of autistic kids remember more than parents of kids w/o autism

41

sampling bias

subjects are not representative of the target population

ex - avg age of participants is less than avg age of target group

42

Late look bias

information gathered in a timeframe that preferentially selects for this w/ more indolent course of disease; severe cases dead and limits generizability

43

Procedure bias

Subjects are not treated the same in a clinical trial

ex: experimental drug rx may receive extra couching and disease education compared to controls

44

Lead time bias

esp pertinent to screening studies
- falsely attributing increased survivability when in fact early screening only found the disease sooner

natural course of the disease has not changes

45

observer expectancy effect/pygmalian effect

the confidence of the researchers assumption of the results of a study influences the study to match expectations.

Not malignant in change, maybe participants conform to thought

46

Hawthorne effect

disruption of truthfulness of the study due participants knowledge of being observed

ex: hand washing frequency

47

confounding error

when there is a 3rd variable related to the variable tested and the measure result that either modifies or magnifies the result

Something else may be going on

48

Cross over study

patient serves as their own control. Take both the experimental and control substance unknowingly to determine effect

49

positive skew in a distribution

tail to the right

meaning the mean>median>mode

50

negative skew in a distribution

tail is to the left

meaning the Mean< mode

51

maintain Ho when H1 is true

False negative or type II error (beta)

falsely saying nothing is going on with 2 variables when in fact there is a relationship

52

alpha in biostatistics

is type I error - making a statement that there is an association when in fact there isn't; rejecting Ho for H1 when Ho is true

alpha is a usually selected at 0.05 for the cut off of risk of making a type 1 error- 5 % chance of saying there is something going on when there is not. p needs to be less than 0.05

53

beta in biostatistics

type II error - making a statement that there is nothing connecting 2 variables when there is something

a false negative

54

p value

is probability calculated from the data the the results are due to chance alone.

Compared to alpha value and usually needs to be less than 0.05 If so then, you are safe to reject the null hypothesis, for there it is unlikely that there is nothing going on and an alternative hypothesis must be accepted

55

Power in biostats

1- beta(or type II error)
the probability of falsely rejecting a null hypothesis when it is in fact false.
-or the likelihood of finding a difference if one in fact exists.

empowering your decision to reject null, increase power, increase rationality that it is ok to reject null

56

Increase power how?(3)

increase sample size
increase expected effect size
increase precision of measurement

57

% of population w/in?

1 SD
2SD
3SD

1SD- 68%
2SD -95%
3SD - 99.7%

58

SEM =?

SD/ square root (n)

n = population
- as n increases SEM decreases (less error)

used in calculating Confidence intervals

59

Confidence interval -

Mean +/- Z x (SEM)

Z= 1.64 w/90%
Z= 1.96 w/95%
Z= 2.5 w/ 99%

60

When to not reject Ho with a confidence interval

When confidence interval includes 0

When CI for an OR or RR includes 1

61

t test?

checks difference between the means of 2 groups of continuous variables (i.e weight)

62

ANOVA

checks the difference between the means of 3+ groups of continuous variables (i.e. weight)

63

Chi Square

tests the difference between 2 or more percents or proportions of categorical incomes

ex: yes/no; age 50-59 vs 60-69; men vs females

64

r

is pearsons correlation which can range from -1 to 1

the closer the value is to the 1 the stronger the positive correlation that exists between 2 variables

0 = no correlation

65

Coefficient of the determinent

=r squared

the goodness of bit and variance within the data pts. reflects the proportion of variance in y that is due to variance in x

66

Car seat recommendations

) booster

67

Vaccines in kids 0-6(10)

Hep A
Hep B
Rota
DTP
HiB
Varicella
Pneumococi
IPV
influenza
MMR

68

Vaccines in kids 7-18 (4)

TDaP -> Td q 10yrs
meningococcus
HPV
Influenza

69

Vaccines in adults

influenza
Herpes zoster > 50
pnumococci >65
Meningococci
Hep A and B if liver damage

70

Screening recommendations in adults age 50

Colon q 10 yrs
Depression
BP
dyslipidemia
DM
Obesity
Tobacco and alcohol

71

ASA use for preventative measures?(2)

45-79 - daily in Men for MI

55-79 daily in women for Stroke

72

Kubler Ross grief stages (5)

DABDA

Denial
Anger
Breievment
Depression
Acceptance

73

When does grief become pathological

depression criteria med at least 2 weeks after the 1st 2 months
generalized feelings of hopelessness, helplessness, worthlessness, and guile

Suicidal
Distreessed feeling > 6 months
inability to move on > 6 months

74

3 leading causes of death in adults > 65

CA
Stroke
Heart disease

75

Odd recommendation for AAA screening

1 US for men 65-75 who have ever smoked

76

OSteoperosisis screening

DEXA scan q 2 yrs older than 65

77

PAP smears age

start age 21 end age 65

78

Mammogram screening age

~50-75

79

Reportable diseases (5)

STDs - Chlamydia, gonorrhea, Shyphilis HIV
Hep A, B and C
Diarrheal - salmonella and shigella
vaccine preventable diseases like mumps
TB

80

What does not change in the elderly (2)

Sexual interest (may have mech issues though)
intelligence

81

Changes in sleep with elderly(3)

increased latency and awakenings
Less REM and N3 (deep sleep)
total sleep time declines