Brainscape's Knowledge GenomeTM

Browse over 1 million classes created by top students, professors, publishers, and experts.


See full index

Medicine > EBM > Flashcards

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
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

EBM effect on Diagnosis:

A
  • Will the results of this test help me to improve the accuracy of my diagnosis
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

EBM: prognosis

A
  • How long will a patient with this disease survive?
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

EBM: aetiology

A
  • What are the risk factors to this disease?
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

EBM: treatment

A
  • Is this treatment better than the existing treatment or no treatment (placebo)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Main Types of study:

A
  • Observational

- Interventional

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

Observational study types:

A
  • Cross-sectional study
  • Case-control study
  • Cohort study
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

Interventional study types:

A
  • Randomised control trial (RCT)

- Experiment (NA)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

Rank epidemiological studies for strongest evidence of causality:

A
  1. RCT
  2. Cohort
  3. Case control
  4. cross-sectional
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
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’
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

Prevalence:

A

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

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

Confounding factors:

A
  • A confounder is a third factor that provides an alternative explanation for an association of two other factors
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
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
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

Example of a case-control study:

A
  • Case: bowel cancer
  • Controls: no bowel cancer
  • Exposure: red meat consumption
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
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
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
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

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
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
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

What is a standard deviation?:

A
  • The variation in the sample, utilised as an estimate for variation in population
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

What does standard error measure? :

A
  • It measures the precision of the sample mean as an estimate of the population mean (SD)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

Standard error equation:

A

SE = SD/square root(n)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
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)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
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
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
23
Q

Precision in stats:

A
  • How close two or more measurements are to eachother
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
24
Q

Accuracy in stats:

A
  • How close a measurement is to the true value
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
25
Q

Difference between calculating a reference range and a confidence interval:

A
  • Mean - (1.96 x Z)
    to mean + (1.96 x Z)
  • Reference range: Z = SD
  • Confidence interval: Z = SE
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
26
Q
  • Null hypothesis

- Falsification:

A
  • A hypothesis that states no association between an exposure and an outcome
  • finding evidence against the null hypothesis to prove an association
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
27
Q

P values:

  • Use
  • What does it tell us?
  • Practical use
A
  • 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
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
28
Q

Statistically significant but not clinically significant:

A
  • If a small effect but a large sample size

- Impact may be small

29
Q

Clinically significant but not statistically significant:

A
  • If a large effect but a small sample size

- Promising, but larger studies are required

30
Q

PICO acronym:

A
  • Patient Intervention Comparison Outcome

- In [Patient] what is the effect of [Intervention] or exposure compared with [Comparison] on [Outcome]

31
Q

Measures of effects of RCT’s

Clue: Ri

A
  • Risk ratio

- Risk difference

32
Q

(RCT) Risk ratio:

A
  • RR= Risk in treated / Risk in controls

- Tells us the amount by which exposure to [smoking] multiplies the risk of [lung cancer]

33
Q

Risk:

A
  • The probability that an individual in a defined population will develop a disease
34
Q
A
  • RD = Risk in exposed - risk in unexposed

- Measures the extra risk of lung cancer in smokers compared to non-smokers (per 1000)

35
Q

Historical (retrospective) cohort study:

A
  • 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
Q

Methods used to compare cohorts in a prospective cohort (4)

A
  • In-person/phone interviews
  • Imaging tests
  • Internet/mail questionnaires
  • lab tests/physical exams
37
Q

Advantages of a prospective cohort study: (3)

A
  • No ethical issues of a RCT
  • Easy to calculate incidence and prevalence rate
  • Multiple disease outcomes can be studied at the same time
38
Q

Disadvantages of prospective cohort studies: (3)

A
  • Selection bias and confounding variables
  • Expense and time consumption
  • Usually requires a very large sample size
39
Q

Example of a historical (retrospective cohort study):

A
  • 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
Q

Example of a prospective study:

A
  • 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
Q

Measure of effect in a case-control study:

A
  • 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
Q

Difference between case-control and retrospective cohort:

A
  • 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
Q

Ecological studies:

A
  • Examine the correlation between average exposure in populations and overall frequency of disease in the population
44
Q

Ecological fallacy:

A
  • The assumption that the average characteristics of the populations are applicable to individuals within the population
45
Q

Linear regression:

A
  • 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
Q

Criteria for confounding: (3)

  • A E
  • R F
  • C P
A

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
Q

Bias in RCTs and how to deal with it:

  • Confounding:
  • Selection bias:
  • Performance/detection bias:
A
  • Confounding: randomisation
  • Selection bias: allocation sequence is concealed from clinicians/researchers who recruit participants
  • Performance/detection bias:
48
Q

Bias in cohort studies:

  • Confounding:
  • Selection bias:
  • Non-differential misclassification:
A
  • 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
Q

Bias in case control studies:

  • Confounding
  • Selection bias
  • Recall/interviewer bias
A
  • 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
Q

Bradford hill criteria: temporal sequence

A
  • The cause (exposure) precedes the effect (disease outcome) is an absolute criterion for causality. Can we exclude reverse causality?
51
Q

BHC: Strength of the association

A
  • The stronger the risk ratio the more likely the relationship is causal and not explained by confounding
52
Q

BHC: Consistency of the association

A
  • 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
Q

BHC: Biological gradient

A
  • Results are more convincing if risk increases with exposure
54
Q

BHC: specificity

A
  • An exposure disease association should ideally be specific and not associated with multiple outcomes
55
Q

BHC: coherence

A
  • Is there an explanation for the observed Association (biologically plausible mechanism?)
56
Q

BHC: reversibility

A
  • Prevention of exposure should reduce or prevent disease.
56
Q

BHC: reversibility

A
  • Prevention of exposure should reduce or prevent disease.
57
Q

What is public health?:

A
  • Defined as “the science and art of preventing disease, prolonging life and promoting health through the organised efforts of society”
58
Q

What does public health target?:

(3) levels of disease

A
  • All health including:
  • Asymptomatic/prodromal
  • not yet presented to medical services
  • being managed by medical services
59
Q

3 domains of public health:

A
  • Health improvement
  • Health protection
  • Healthcare public health
60
Q

Public health: health improvement: (3)

A
  • Wider factors that affect health and wellbeing
  • Healthy lifestyle and choices
  • Inequalities
61
Q

Public health: Health protection

A
  • Infectious disease control
  • Emergency response
  • Environmental hazards
62
Q

Public health: healthcare

A
  • Disease prevention
  • Service improvement
  • Evidence based practise
  • Equity of provision
63
Q 
Examples of tools for improving population health: (4)
- S P
- I 
- L 
_ P of H B
A
  • Screening programmes
  • Immunisation
  • Legislations
  • Promotion of healthy behaviour
64
Q

Primary disease prevention:

A
  • Aims to prevent the onset of disease

- May alter an environmental factor or change behaviour

65
Q

Secondary disease prevention:

A
  • 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
Q

Tertiary disease prevention:

A
  • Focus on treatment and rehabilitation of people with established disease
  • Aims to minimise complications and disability
67
Q

Incidence rate:

A
  • Incidence rate=

no. new cases of disease / (Total no. disease free at outset x time interval)

68
Q

Prevalence:

A

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

Medicine (18 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2024 Bold Learning Solutions. Terms and Conditions