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1. Foundations of Medicine > EBM > Flashcards

EBM Flashcards

1
Q

what is evidence based medicine?

A

the conscientious, explicit and judicious use of current best evidence in making decision about the care of individual patients

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2
Q

what does evidence based medicine consider?

A
  • clinical judgement
  • relevant scientific evidence
  • patients’ values & preferences
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3
Q

what is epidemiology?

A

‘the study of the occurrence & distribution of health-related events, states, and processes in specified populations, incl. the study of the determinants influencing such processes, and the application of this knowledge to control relevant health problems’

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4
Q

how do you use EBM in medicine?

A
  • diagnosis
  • prognosis
  • aetiology
  • treatment
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5
Q

how is EBM used in diagnoses?

A

will the result of this test help me improve the accuracy of my diagnosis?

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6
Q

how is EBM used in prognoses?

A

how long will a patient with this disease survive?

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7
Q

how is EBM used in aetiology?

A

what are the risk factors for this disease?

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8
Q

how is EBM used in treatment?

A

is this treatment better than the existing treatment or no treatment at all (placebo)?

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9
Q

what kind of epidemiological study designs are there?

A
  • observational
  • interventional
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10
Q

what are examples of observational study designs?

A
  • descriptive
  • ecological
  • cross-sectional
  • case-control
  • cohort
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11
Q

what are examples of interventional study types?

A
  • randomised controlled trials (RCT)
  • experiment
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12
Q

what is the Bradford Hill criteria for judging whether an association is causal ?

A
  • risk factor PRECEDES disease
  • strong & consistent association
  • higher levels of risk factor associated w more disease
    risk factor is SPECIFIC to the disease
  • biological mechanism explains the association
  • removal or risk factor prevents/reduces disease
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13
Q

how can we rank epidemiological study designs from strong evidence of causality to weak evidence of causality?

A

STRONG -> WEAK:

RCTs > cohort study > case control study > cross-sectional study

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14
Q

what are cross-sectional studies?

A
  • measure PREVALENCE of disease in a population
  • OR examine relationship between diff variables
  • ‘clinical iceberg’
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15
Q

what is prevalence?

A

number with disease at a particular time __________________________________________

total number in a population at that time

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16
Q

what is the clinical iceberg?

A

tip of iceberg that is seen: known to medical services
unable to see: not seeking advice but aware of illness, diseased but not aware of illness, clinically well

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17
Q

what is a confounding factor?

A

a confounder is a THIRD variable that provides an alternative explanation for an association between two factors (deciding if its reverse causality or condounder)

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18
Q

what is a case control study?

A

researchers identify group of individuals with a particular disease/condition (cases), and COMPARE to a group without the disease/condition (controls)

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19
Q

what is the aim of a case control study?

A

to identify factors/exposures that may be associated w the disease/condition. look at possible reverse causality of factors, and considers confounding factors also

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20
Q

what is a prospective cohort study?

A

group of individuals who do NOT have a particular disease/condition of interest are followed over time to determine whether they develop it or not

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21
Q

what are prospective cohort studies used for?

A

to identify risk factors for diseases or conditions and to study the natural history of diseases

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22
Q

what is a RCT?

A
  • gold standard in assessing efficacy of interventions
  • designed to minimise biases & provide a rigorous assessment of cause & effect
  • investigate effectiveness of new medical treatment/intervention
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23
Q

how does randomisation work?

A
  1. details of everyone taking part in the trial are put into a computer
  2. computer puts each person into a treatment group at random
  3. computer programme takes into account details such as age & stage of cancer to make sure groups are as similar as possible
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24
Q

what are the types of variables?

A
  • numerical
  • categorical
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25
Q

what are numerical variables?

A
  • continuous
  • discrete (counts)
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26
Q

what are categorical variables?

A
  • ordered categorial
  • unordered categorical
  • dichotomous/binary
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27
Q

what are examples of continuous (numerical) variables?

A

height, weight

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28
Q

what are examples of discrete (numerical) variables?

A

no. of children in a family

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29
Q

what is an example of ordered categorical variables?

A

severity of disease - mild, moderate, severe

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30
Q

what is an example of unordered categorical variables?

A

ethnicity

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31
Q

what is an example of a dichotomous/binary variable?

A

sex

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32
Q

what type of variable is social class?

A

ordered categorial

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33
Q

what type of variable is platelet count?

A

continuous, although theoretically could be discrete

  • regarded as continuous bc large no of possible values
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34
Q

what type of variable is post treatment mortality?

A

binary

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35
Q

what type of variable is educational level?

A

ordered categorical

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36
Q

what graphs are representative of categorical data?

A

bar chart, pie chart

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37
Q

what graphs are representative of continuous data?

A

histograms

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38
Q

what are descriptive statistics for binary variables?

A

prevalence, risk, incidence rate

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39
Q

how can we calculate risk?

A

no. of NEW cases of disease in a time period
______________________________________________

            no. initially free of disease
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40
Q

what is the incidence rate?

A

how fast new cases of disease are occurring

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41
Q

how can we calculate incidence rate?

A

number of new cases of disease
_________________________________________

no initially disease free x TIME INTERVAL

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42
Q

what is the relationship between prevalence and incidence?

A

under certain conditions,
prevalence = incidence x average disease duration

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43
Q

what are measures of effect?

A

risk difference
risk ratio

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44
Q

what is risk difference?

A

ABSOLUTE MEASURE that assesses the difference in risk between the treated/exposed group & the control/non-exposed group

units (e.g. risk per 100, or 1000)

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45
Q

how can you calculate risk difference?

A

risk in treated/exposed - risk in controls/unexposed

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46
Q

what is the risk ratio?

A

RELATIVE MEASURE of strength of association between a treatment/exposure and a disease outcome

(no units)

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47
Q

how can we calculate the risk ratio?

A

risk in treated/exposed / risk in controls/non-exposed

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48
Q

how can we interpret risk ratios?

A

scale of 0-2

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49
Q

what does it mean if risk ratio is 1?

A

there is NO difference in risk between groups

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50
Q

what does it mean if risk ratio is less than 1?

A

treatment/exposure is associated with a REDUCED risk of outcome
e.g. if risk ratio is 0.75 = a 25% reduction in risk of outcome

51
Q

what if risk ratio is more than 1?

A

treatment/exposure is associated with an INCREASED risk of the outcome

e.g. risk ratio is 1.75 = 75% increase in risk of outcome

52
Q

what are descriptive studies?

A
  • describe patterns of disease in terms of time, place, or person
  • DON’T consider association or causative (aetiological) hypotheses
53
Q

what is a major advantage of conducting cross-sectional studies?

A

they detect cases which may have not presented otherwise

clinical iceberg: would pick up those who are aware of illness but not sought advice, or those diseased but not yet aware of illness

54
Q

how can we conduct a cross-sectional study?

A
  1. define a target population
  2. define a selected sample
  3. carry out the study using a study sample
55
Q

what is a target population?

A

population to which inferences from study sample are to be made

56
Q

what is a selected sample?

A

representative sample of individuals from target population

57
Q

what is a study sample?

A

individuals who provide the study data

58
Q

how can we use statistics to make inferences about the population from the sample?

A

population -> random sampling -> sample -> statistics -> back to population

59
Q

what is standard deviation?

A

measure of the spread of INDIVIDUAL observed values about the mean

60
Q

what is the 95% reference range?

A

95% of observed values lie between the mean -1.96 SD and mean +1.96 SD

i.e. the reference range

61
Q

what is sampling variation?

A

when the sample means/proportions are different every time when we take repeated random samples from the population

62
Q

how can we normally distribute sample means/proportions

A

by making samples large enough

mean of sample means = population mean

63
Q

how can we estimate a population mean, or a proportion from a single sample?

A

-> rely on a SINGLE sample, & a SINGLE mean/proportion estimates from that sample

don’t know the variation in the population = use the variation in the sample (STANDARD DEVIATION) as estimation

64
Q

what is the standard error (SE)?

A

the standard deviation (SD) of the sampling distribution of a statistic

65
Q

what does the SE measure?

A

the prevision of the sample mean as an estimate of the population mean

66
Q

what is the 95% confidence interval?

A

when sample means/proportions are normally distributed, 95% will lie between

1.96 x SE and sample statistic + 1.96 x SE

67
Q

why do we use 1.96 for the 95% confidence interval?

A

bc 95% of individual sample means/proportions are + or -1.96 standard errors of the mean of the sampling distribution

68
Q

why is the 95% confidence interval used?

A

can be 95% confident the interval actually DOES contain the true value of the population statistic

IF study is unbiased

69
Q

how can we used the 95% confidence interval (C.I.) to assess our sample statistic?

A

NARROWER the confidence interval = GREATER the prevision of sample statistic

(as estimate of the target population statistic)

70
Q

what is a disadvantage of 95% C.I.?

A

doesn’t tell us about ACCURACY
(whether the range of values actually includes population value)

71
Q

how is accuracy determined?

A

by how representative the study sample is of the target population
influenced by participants selected into the study

72
Q

what is falsification?

A

much easier to find evidence AGAINST a hypothesis than to prove it to be true

  • essence of the scientific process

(for a theory to be scientific, MUST be possible to test if it is false)

73
Q

what does the null hypothesis state about exposure v outcome?

A

states there is NO ASSOCIATION between an exposure & an outcome

-> can use data to look for evidence AGAINST null hypothesis (falsification)

74
Q

what are P values?

A

used to investigate hypotheses

probability of finding the observed (or more extreme) difference if null hypothesis is true

75
Q

what does the P value tell us?

A

the strength of evidence AGAINST the null hypothesis; and that the true difference in the population is zero

76
Q

how does P value relate to null hypothesis?

A

smaller the P value = stronger evidence AGAINST null hypothesis
(from 0.01 –> 0.0001)

77
Q

what does it mean if P value is 0.05?

A

5% probability that the observed difference is due to chance if the null hypothesis is true

(i.e. 1/20 times we would be wrong)

78
Q

what P value would provide strong value against null hypothesis?

A

P<0.001
i.e. less than 1 in a 1000 chance of being wrong

79
Q

what semi-standard structure do research questions often follow?

A

PICO

80
Q

what is PICO?

A

Patient, Intervention, Comparison & Outcome:

‘In [PATIENT] what is the effect of [INTERVENTION] or exposure compared with [COMPARISON] on [OUTCOME]?’

81
Q

what are measures of effect in RCTs?

A

risk ratio
risk differences

82
Q

what does Pearson’s correlation coefficient indicate?

A

the degree to which two variables have a linear relationship (ranges from -1 to +1)

83
Q

what do ecological studies examine?

A

the correlation between average exposure in populations and overall frequency of disease in the populations

84
Q

what is ecological fallacy?

A

the assumption that the average characteristics of populations are applicable to individuals within the population

85
Q

what is linear regression?

A

describes the linear relationship between one variable and another using the equation of a straight line

86
Q

what is the equation of the regression line

A

y = a + bx

outcome = y-axis intercept + (slope of line x exposure)

87
Q

what does linear regression allow for?

A

the estimation of the change in value of y (outcome) per unit change in x (exposure)

88
Q

how can we determine association/causality?

A
  1. is it result of chance?
  2. is it due to bias?
  3. is it due to confounding?
  4. is it an example of reverse causality?
  5. is it causal?
89
Q

what is the criteria of a confounder?

A

3rd variable must
- be associated with exposure
- be a risk factor for the disease
- not be on causal pathway between exposure & disease

90
Q

how can we deal with confounding?

A

control in the study design (randomisation in RCT)

control in the analysis (stratification)

91
Q

what is stratification?

A

within each stratum everybody has the same value of the confounder

92
Q

what bias can we encounter in RCTS?

A

confounding
selection bias
loss to follow up bias
performance bias
detection bias

93
Q

how can we solve confounding in RCTs?

A

randomisation

94
Q

how can we solve selection bias in RCTs?

A

ensure that the allocation sequence is concealed from clinicians/researchers who recruit participants into the trial

95
Q

how can we solve loss to follow up bias in RCTs?

A

intention to treat analysis

96
Q

how can we solve performance bias & detection bias in RCTs?

A

ensure patients & outcome assessors are unaware of treatment allocation

97
Q

how can we deal with confounding bias in cohort studies?

A

adjust for confounders in analysis

98
Q

how can we deal with selection bias / loss to follow up bias in cohort studies?

A

minimise losses to follow up during the design & conduct of the study

99
Q

what is non-differential misclassification (bias)?

A

misclassification of exposure/outcome occurs randomly

leads to underestimation of true effect of exposure/risk factor on an outcome

100
Q

how can we deal with non-differential misclassification (bias) in cohort studies?

A

ensure that exposures & outcomes are measured accurately and consistently between participants

careful design, testing, & standardisation of data collection instruments

101
Q

what type of bias do we encounter in cohort studies?

A

confounding

selection bias (loss to follow up)

non-differential misclassification

102
Q

what type of bias are in case-control studies?

A

confounding

selection bias

recall bias, interviewer bias

103
Q

how can we deal with confounding (bias) in case-control studies?

A

adjust for confounders in analysis

104
Q

how can we deal with selection bias in case-control studies?

A

ensure that controls are a representative sample from the at-risk population

105
Q

how can we deal with recall & interviewer bias in case-control studies?

A

interviewers must be careful to ask each study participant (cases & controls) in the same way so as not to influence their responses

use STANDARD questionnaires

106
Q

what is the Bradford Hill criteria?

A

set of guidelines developed to help determine whether an observed association between an exposure and an outcome is causal

(a framework for evaluating the strength of evidence for causation)

107
Q

what does the Bradford Hill criteria include?

A

temporal sequence
strength of the association
consistency of the association
biological gradient (dose-response)
specifity
coherence
reversibility

108
Q

what is public health?

A

‘the science & art of preventing disease, prolonging life and promoting health through the organised efforts of society’

109
Q

what is the focus of public health?

A

to improve the health of ENTIRE POPULATIONS rather than individual patients

(aims to encompass the whole clinical iceberg)

110
Q

who is the patient in public health?

A

the population

111
Q

who does public health want to target?

A

ALL ILL HEALTH, INCL.

  • asymptomatic/prodromal population
  • population who have not yet presented to medical services
  • population already being managed by health care services
112
Q

what are the three domains of public health?

A

health improvement
health protection
healthcare public health

113
Q

what is health improvement?

A
  • wider factors that affect health & wellbeing
  • healthy lifestyles & choices
  • inequalities
114
Q

what is healthcare public health?

A
  • disease prevention
  • service improvement
  • evidence based practise
  • equity of provision
115
Q

what is health protection?

A
  • infectious diseases
  • emergency response
  • environmental hazards
116
Q

what is the bell-curve shift in populations?

A

shifting the whole population into a lower risk category benefits more individuals than shifting high risk individuals into a lower risk category

117
Q

what are examples of tools for improving population health?

A
  • health improvement; schools & workplaces
  • screening programmes; detect disease at an early (treatable) stage
  • immunisation; prevent transmission of infection diseases
  • legislation; prohibit actions or behaviours (e.g. smoking in enclosed public places)
  • promote healthy actions/behaviours; e.g. extend cycle lanes to encourage active transport
  • development of new clinical services for treating disease
118
Q

what are the types of disease prevention?

A
  • primary
  • secondary
  • tertiary
119
Q

what is primary disease prevention?

A

aims to prevent ONSET of disease

may alter environmental factor/change behaviour

120
Q

what is secondary prevention?

A

aims to HALT progression of disease

focuses on early detection or diagnosis followed by prompt & effective treatment

may be aimed at asymptomatic people

121
Q

what is tertiary prevention?

A

focus on treatment and rehabilitation of people w established disease

aims to minimise complications & disability

122
Q

what are the advantages of cross-sectional studies?

A

relatively quick & inexpensive to conduct - useful tool for generating hypotheses for further research

123
Q

what are the disadvantages of cross-sectional studies?

A

cannot establish causality or directionality of relationships between variables

may be subject to selection bias if sample is not representative of population of interest

may not account for changes in prevalence of disease/condition over time

1. Foundations of Medicine (4 decks)

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