EBM Flashcards

1
Q

Evidence based medicine definition:

A
  • The conscientious, explicit and judicious use of current best evidence in making decisions about the care of individual patients
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2
Q

EBM effect on Diagnosis:

A
  • Will the results of this test help me to improve the accuracy of my diagnosis
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3
Q

EBM: prognosis

A
  • How long will a patient with this disease survive?
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4
Q

EBM: aetiology

A
  • What are the risk factors to this disease?
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5
Q

EBM: treatment

A
  • Is this treatment better than the existing treatment or no treatment (placebo)
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6
Q

Main Types of study:

A
  • Observational

- Interventional

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7
Q

Observational study types:

A
  • Cross-sectional study
  • Case-control study
  • Cohort study
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8
Q

Interventional study types:

A
  • Randomised control trial (RCT)

- Experiment (NA)

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9
Q

Rank epidemiological studies for strongest evidence of causality:

A
  1. RCT
  2. Cohort
  3. Case control
  4. cross-sectional
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10
Q

Cross-sectional study: (3)

  • What does it measure?
  • What does it show/prove?
  • Metaphor???
A
  • Measures the prevalence of disease in a population at a particular time
  • Shows the true burden of a disease in a population
  • ‘Clinical iceburg’
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11
Q

Prevalence:

A

= No. with disease at a particular time / total population at that particular time

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12
Q

Confounding factors:

A
  • A confounder is a third factor that provides an alternative explanation for an association of two other factors
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13
Q

Case-control study:

  • Definition
  • Aims to:
A
  • Patients who have developed a disease are identified and their past exposure to aetiological factors is compared with a control group without the disease.
  • Aims to identify frequency and amount of exposure to identify what caused the disease
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14
Q

Example of a case-control study:

A
  • Case: bowel cancer
  • Controls: no bowel cancer
  • Exposure: red meat consumption
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15
Q

Prospective cohort study:

A
  • A group of similar people (cohort) and studies them over time
  • At the start of the study nobody has the disease of interest, but some are expected to develop it due to certain variables that would divide the cohort
  • The two groups are then later compared using a variety of methods
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16
Q

Example of a prospective cohort study:

A
  • Female nurses who smoke and female nurses who don’t smoke

- They are compared for a particular outcome, development of lung cancer

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17
Q

Randomised control trial:

A
  • The randomised control trial (RCT) is a trial in which subjects are randomly assigned to one of two groups: one (the experimental group) receiving the intervention that is being tested, and the other (control) receiving an alternative (conventional) treatment
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18
Q

What is a standard deviation?:

A
  • The variation in the sample, utilised as an estimate for variation in population
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19
Q

What does standard error measure? :

A
  • It measures the precision of the sample mean as an estimate of the population mean (SD)
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20
Q

Standard error equation:

A

SE = SD/square root(n)

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21
Q

95% confidence interval:

A
  • Sample means/proportions are normally distributed
  • So 95% of data lies between:
    Sample statistic - (1.96 x SE) and sample statistic + (1.96 x SE)
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22
Q

What does the 95% confidence interval mean?:

A
  • A 95% CI is a range of values you can be 95% sure contain true sample statistic
  • i.e. We can be 95% confident that the interval does contain the true value of the population statistic
  • The narrower the CI, the greater the precision of the sample statistic
  • CI not a measurement of accuracy
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23
Q

Precision in stats:

A
  • How close two or more measurements are to eachother
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24
Q

Accuracy in stats:

A
  • How close a measurement is to the true value
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25
Difference between calculating a reference range and a confidence interval:
- Mean - (1.96 x Z) to mean + (1.96 x Z) - Reference range: Z = SD - Confidence interval: Z = SE
26
- Null hypothesis | - Falsification:
- A hypothesis that states no association between an exposure and an outcome - finding evidence against the null hypothesis to prove an association
27
P values: - Use - What does it tell us? - Practical use
- Used to investigate the hypothesis - The P value tells us the strength of the evidence against the null hypothesis - The smaller the P value, the stronger the evidence against the null hypothesis
28
Statistically significant but not clinically significant:
- If a small effect but a large sample size | - Impact may be small
29
Clinically significant but not statistically significant:
- If a large effect but a small sample size | - Promising, but larger studies are required
30
PICO acronym:
- Patient Intervention Comparison Outcome | - In [Patient] what is the effect of [Intervention] or exposure compared with [Comparison] on [Outcome]
31
Measures of effects of RCT's | Clue: Ri
- Risk ratio | - Risk difference
32
(RCT) Risk ratio:
- RR= Risk in treated / Risk in controls | - Tells us the amount by which exposure to [smoking] multiplies the risk of [lung cancer]
33
Risk:
- The probability that an individual in a defined population will develop a disease
34
[RCT]: Risk difference
- RD = Risk in exposed - risk in unexposed | - Measures the extra risk of lung cancer in smokers compared to non-smokers (per 1000)
35
Historical (retrospective) cohort study:
- Case group contains people who have a disease/outcome and control group who do not. - Study investigates back in time to identify frequency of disease in those exposed to certain factors
36
Methods used to compare cohorts in a prospective cohort (4)
- In-person/phone interviews - Imaging tests - Internet/mail questionnaires - lab tests/physical exams
37
Advantages of a prospective cohort study: (3)
- No ethical issues of a RCT - Easy to calculate incidence and prevalence rate - Multiple disease outcomes can be studied at the same time
38
Disadvantages of prospective cohort studies: (3)
- Selection bias and confounding variables - Expense and time consumption - Usually requires a very large sample size
39
Example of a historical (retrospective cohort study):
- 100 people with AIDS are asked about their lifestyle choices and medical history to study the origins of the disease - A control group of 100 people without AIDS are also studied to compare the two groups
40
Example of a prospective study:
- 100 people with high risk factors for AIDS are followed for 20 years to see if they develop the disease - A control group of 100 people with low risk factors are also followed for comparison
41
Measure of effect in a case-control study:
- Odds ratio (OR): how much more common the exposure is in cases vs controls OR = Odds of exposure in diseased / ODDS of exposure in non-diseased
42
Difference between case-control and retrospective cohort:
- Case control: concerned with the frequency and amount of exposure in subjects with a specific disease - Retrospective cohort: concerned with the frequency of disease in exposed and non-exposed individuals (specific exposure)
43
Ecological studies:
- Examine the correlation between average exposure in populations and overall frequency of disease in the population
44
Ecological fallacy:
- The assumption that the average characteristics of the populations are applicable to individuals within the population
45
Linear regression:
- Describes the relationship between variables using the equation of a straight line - Allows estimations of value of y (outcome) per unit change in x (exposure)
46
Criteria for confounding: (3) - A E - R F - C P
To be a confounder, the third variable must: (i) be associated with exposure (ii) be a risk factor for disease, and (iii) must not be on the casual pathway between the exposure and the disease
47
Bias in RCTs and how to deal with it: - Confounding: - Selection bias: - Performance/detection bias:
- Confounding: randomisation - Selection bias: allocation sequence is concealed from clinicians/researchers who recruit participants - Performance/detection bias:
48
Bias in cohort studies: - Confounding: - Selection bias: - Non-differential misclassification:
- Confounding: adjust for confounders in analysis - Selection bias: minimise losses to follow up - Non-differential misclassification: exposures and outcomes to be measured accurately and consistently
49
Bias in case control studies: - Confounding - Selection bias - Recall/interviewer bias
- Confounding: adjust for confounders in analysis - Selection bias: controls are representative sample from at-risk population - Recall/interviewer bias: Questions must be asked in the same way so as to not influence response (standardised questionnaire)
50
Bradford hill criteria: temporal sequence
- The cause (exposure) precedes the effect (disease outcome) is an absolute criterion for causality. Can we exclude reverse causality?
51
BHC: Strength of the association
- The stronger the risk ratio the more likely the relationship is causal and not explained by confounding
52
BHC: Consistency of the association
- Is the observed association consistent when examined under different circumstances? - Do the geographical and temporal data show what would be predicted by the hypothesis
53
BHC: Biological gradient
- Results are more convincing if risk increases with exposure
54
BHC: specificity
- An exposure disease association should ideally be specific and not associated with multiple outcomes
55
BHC: coherence
- Is there an explanation for the observed Association (biologically plausible mechanism?)
56
BHC: reversibility
- Prevention of exposure should reduce or prevent disease.
56
BHC: reversibility
- Prevention of exposure should reduce or prevent disease.
57
What is public health?:
- Defined as "the science and art of preventing disease, prolonging life and promoting health through the organised efforts of society"
58
What does public health target?: | (3) levels of disease
- All health including: - Asymptomatic/prodromal - not yet presented to medical services - being managed by medical services
59
3 domains of public health:
- Health improvement - Health protection - Healthcare public health
60
Public health: health improvement: (3)
- Wider factors that affect health and wellbeing - Healthy lifestyle and choices - Inequalities
61
Public health: Health protection
- Infectious disease control - Emergency response - Environmental hazards
62
Public health: healthcare
- Disease prevention - Service improvement - Evidence based practise - Equity of provision
63
``` Examples of tools for improving population health: (4) - S P - I - L _ P of H B ```
- Screening programmes - Immunisation - Legislations - Promotion of healthy behaviour
64
Primary disease prevention:
- Aims to prevent the onset of disease | - May alter an environmental factor or change behaviour
65
Secondary disease prevention:
- Aims to halt progress of disease - Focus on early detection or diagnosis followed by prompt and effective treatment - May be aimed at symptomatic people
66
Tertiary disease prevention:
- Focus on treatment and rehabilitation of people with established disease - Aims to minimise complications and disability
67
Incidence rate:
- Incidence rate= | no. new cases of disease / (Total no. disease free at outset x time interval)
68
Prevalence:
No. with disease at a particular time / total population at that time