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Medicine Semester 1 > HaDPop > Flashcards

HaDPop Flashcards

0
Q

What information can be obtained from a census and how is this used?

A
  • Population size: can calculate rates
  • Population structure: service needs
  • Population characteristics: measures areas of deprivation: unemployment, single parents, lack of basic amenities, overcrowding, lone pensioners.
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1
Q

What is the definition of a census?

A
  • The simultaneous recording of demographic data, by a government, at a particular time pertaining to all people living in a given area.
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2
Q

What three things is a population’s size and structure affected by?

A
  • Births
  • Deaths
  • Migration
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3
Q

What are the two steps to occur once a birth has occurred?

A
  • Birth notification: by attendant at birth within 36hrs, immunisations
  • Birth registration: by parent to registrar for births within 42 days, for stat purposes.
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4
Q

What is crude birth rate? And what is its role?

A
  • Number of live births per 1,000 population

- Impacts of births on size of population

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5
Q

What’s general fertility rate? And its role?

A
  • Number of live births per 1,000 females between the ages 15-44
  • Comparing fertility of fertile female populations.
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6
Q

What is total period fertility rate? And its role?

A
  • The average number of children that would be born to a hypothetical woman in her life.
  • Comparing fertility of fertile female populations without being influenced by age group structures.
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7
Q

What is fecundity and what decreases fecundity?

A
  • Physical ability to reproduce

- Increase in hysterectomies and sterilisation.

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8
Q

What factors increase/decrease fertility?

A
  • Increase: sexual activity, economic climate

- Decrease: contraceptives, abortions

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9
Q

What is the equation to calculate conceptions?

A
  • Live births + miscarriages + abortions
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10
Q

What does SMR stand for and what is it?

A
  • Standardised mortality ratio
  • Compares number of observed deaths with the number of expected deaths if age-sex distributions for populations were identical.
  • Adjusts for age-sex distributions
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11
Q

Why is mortality data collected?

A
  • Classify causes of deaths
  • Identify patterns in mortality rates
  • Identify health problems
  • Inform service needs
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12
Q

When monitoring trends what are the different ways of interpreting them?

A
  • Chance (random) variation
  • Artefactual (systematic) reasons
  • Real phenomenon: Natural (epidemiological), Medical care effects.
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13
Q

What is an incidence rate?

A
  • Measuring new cases.
  • new cases/persons x years= persons per year
  • Make sure to times up to make it above 1
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14
Q

What is prevalence and what causes it to increase?

A
  • The number of existing cases.
  • Lower incidence
  • Deaths
  • Cures
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15
Q

How can we compare incidence in different areas?

A
  • Incidence rate ratio
  • A/B = x
  • A is x times as likely to have the condition.
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16
Q

What measures absolute risk and what measures relative risk?

A
  • Absolute = Rate

- Relative = Ratio

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17
Q

What is the confounder triangle?

A

Exposure -> Outcome
| |
Confounder

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18
Q

If an SMR was 154 what would this mean?

A

It means the study population was 54% more likely to be at risk of x

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19
Q

What are the required calculations to see if there is a significant difference between two cohort studies?

A
  • Incidence rate (cases/pop)
  • Null hypothesis (1.0)
  • Error factor (equation given)
  • 95% Confidence interval (IRxEF, IR/EF)
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20
Q

If the null hypothesis lies within the CI what does this mean?

A
  • p>0.05
  • Can’t reject null hypothesis
  • 95% probability, that the results aren’t statistically significant.
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21
Q

What is the difference between a concurrent and a retrospective cohort study?

A
  • Pick disease free individuals and classify with respect to exposure - Concurrent: From now, follow up immediately until x date.
  • Retrospective: Use historical records, so no need to wait.
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22
Q

What are the two types of comparison that can be made with a cohort study?

A
  • Internal IRR

- External SMR

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23
Q

What are the main disadvantages of cohort studies?

A
  • Takes time
  • Not good for rare diseases
  • Large, so resource intensive
  • Survivor bias
  • Investigations into definitions
  • Unknown confounders
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24
Q

What are main advantages of cohort studies?

A
  • Good for conditions that fluctuate with age
  • Studying a range of different outcomes
  • Studying a rare exposure
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25
Q

What are the 4 stages to conducting a case control study?

A
  • Identify a group of cases
  • Identify a group of non-cases (control)
  • Ascertain previous exposure status of everyone
  • Compare level of exposure within cases and control.
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26
Q

What is a case control study?

A
  • Obtain outcomes (cases/controls) then exposures.
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27
Q

What does an odds ratio signify in a case control study?

A
  • ad/bc where a: cases exposed
    b: controls exposed
    c: cases unexposed
    d: controls unexposed
  • OR signifies the measure of excess risk in cases compared to controls.
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28
Q

If the number of cases was underestimated/recorded what would this do to the OR?

A
  • Cases decreased means the OR would decrease towards 1.0
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29
Q

What would occur if the number of controls was overestimated?

A
  • The OR would decrease towards 1.0
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30
Q

How is data collected in a conventional case study?

A
  • From recall
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31
Q

What are the advantages of a nested case control as opposed to a conventional case study?

A
  • Can produce an IRR as sampling fractions are known.

- Population for sampling controls are already defined.

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32
Q

What are the 4 main problems with case controls?

A
  • Selection bias
  • Information bias (recall)
  • Confounders
  • Not good for rare exposures.
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33
Q

Define necessary:

A
  • Cause ALWAYS precedes disease.
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34
Q

Define sufficient:

A
  • The cause ALONE can lead to the disease.
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35
Q

Define specific:

A
  • Cause is ABSENT in other diseases.
36
Q

Give synonyms for the following:
Confounding
Bias (selection, information)
Chance

A
  • Confounding: erroneous
  • Bias: incorrect
  • Selection bias: wrong people
  • Information bias: wrong info
  • Chance: luck
37
Q

In the Bradford hills criteria for inferring causality what is strength of association?

A
  • Causal link is more likely with strong associations (measured by IRR or OR)
  • Strong associations are unlikely to be explained by undetected confounding or bias.
38
Q

In BHC what is specificity of association?

A
  • Causal link is more likely when an outcome is associated only with a specific factor.
  • Specificity of association STRENGTHENS the case for a causal link.
39
Q

In BHC what is consistency of association?

A
  • Causal link is more likely if the association is observed in different studies and sub-groups
  • Consistency of association between studies/groups is unlikely to be due to the same confounding/bias
40
Q

In BHC what is temporal sequence?

A
  • Causal link in more likely if exposure to the putative factor has been shown to precede the outcome.
  • Causal link can’t exist if the outcome is preceded the exposure to the putative factor.
41
Q

In BHC what is dose response?

A
  • Causal link’s more likely if different levels of exposure to the putative factor leads to different risk of acquiring the outcome.
  • Does response is unlikely to be due to unknown confounding/bias
42
Q

In BHC what is reversibility?

A
  • Causal link is extremely likely if removal or prevention of the putative factor leads to a reduction in risk of acquiring the outcome
  • Strongest evidence for causal link - often difficult to demonstrate.
43
Q

In BHC what is coherence of theory?

A
  • Causal link is more likely if observed association conforms with current knowledge
  • Coherence with current paradigms/constructs/theories- strengthens the case for a causal link.
44
Q

In BHC what is biological plausibility?

A
  • Causal link is more likely if a biologically plausible mechanism is likely/demonstrated.
45
Q

In BHC what is analogy?

A
  • Causal link is more likely if an analogy exists with other diseases, species or settings
  • Analogy is easier to infer than a biologically plausible mechanism.
46
Q

What are the two main assumptions in epidemiology?

A
  • Disease is not randomly occurring

- Disease has causal and preventable factors that can be identified through systematic investigation.

47
Q

What are the 4 main stages of epidemiology?

A
  • Hypothesis
  • Analytical study
  • Observed associations
  • Cause-effect relationship
48
Q

What’s the definition of a clinical trial?

A
  • A planned experiment which involves patients and is designed to elucidate the most appropriate method of treatment of future patients with a given medical condition.
49
Q

What is a clinical trial?

A
  • Compare the outcomes from a new treatment with standard treatment.
50
Q

What is the purpose of a clinical trial?

A
  • Provide reliable evidence of treatment efficacy and safety.
51
Q

What is efficacy and safety?

A
  • Efficacy: Ability of a health care intervention to IMPROVE the health of a defined group under specific conditions.
  • Safety: Ability of a health care intervention NOT TO HARM a defined group under specific conditions.
52
Q

What 3 things does a clinical trial require?

A
  • Fair: unbiased without confounding
  • Controlled: comparison of interventions
  • Reproducible: Experimental conditions.
53
Q

What are the restrictions of non-randomised clinical trials?

A
  • Selection bias: patient, clinician, investigator

- Confounding: known/unknown

54
Q

For a randomly controlled trail (RTC) what is the definition of factors?

A
  • Disease of interest
  • Treatments to be compared
  • Outcomes to be measured
  • Possible bias and confounders
  • Patients eligible for trail
  • Patients excluded from trail
55
Q

Why is random allocation important in RTCs?

A
  • Minimise selection bias: equal chance to be chosen

- Minimise confounding: in long run randomisation leads to similar groups in size and characteristics by chance.

56
Q

What is blinding and what is a single and a double blind?

A
  • Not allowing a party/parties to know if they are receiving the new treatment or if they’re the placebo.
  • Single blind: the patient doesn’t know
  • Double blind: the patient and clinician don’t know.
57
Q

Define the placebo effect.

A
  • Even if the therapy is irrelevant to the patient’s treatment, the patient’s attitude towards the illness and sometimes the illness itself may improve due to the feeling that something is being done about it.
58
Q

What is a placebo?

A
  • An inert substance that is made to look identical to the real medication
59
Q

What are the ethical issues of a placebo?

A
  • Using a placebo is a form of deception

- So those involved must be informed that they may receive a placebo.

60
Q

Why do we need to pre-define outcomes in clinical trials?

A
  • Prevent data dredging/repeated analysis
  • Protocol for data collection
  • Agreed criteria for measurement and assessment of outcomes
61
Q

What is a primary and secondary outcome?

A
  • Primary: preferably only one, used in sample size calculation
  • Secondary: other outcomes of interest, occurrence of side effects.
62
Q

What are the three main types of outcomes?

A
  • Patho-physiological
  • Clinically defined
  • Patient centred
63
Q

What is losses to follow up and what are the two different types?

A
  • Not every participant remains on the trial.
  • Appropriate: trail dictates that the participant leaves
  • Unfortunate: participant withdraws from the trial
64
Q

How can you reduce loss to follow up?

A
  • Maintain contact
  • Practical and convenient
  • Be honest about commitment
  • Don’t coerce or induce.
65
Q

Why is non-compliance a problem, what are the different types?

A
  • Not undergoing trial properly, so results skewed
  • Mis-understanding
  • Not liking treatment
  • Think better treatment should be taken
  • Not bothered
  • Thinking treatment isn’t working.
66
Q

What are the two different types of RTC trial?

A
  • Pragmatic: ‘Intention to treat’ Analyse all who were meant to take the treatment, preserves randomness.
  • Explanatory ‘As treated’ Analyse only those who took the medication, loses randomness, includes selection bias and confounding.
67
Q

What is the collective ethic?

A
  • All patients should have treatment that has been properly tested for efficacy and safety.
68
Q

What is the individual ethic?

A
  • Beneficence
  • Non-malevolence
  • Autonomy
  • Justice
69
Q

How do RTC impact the collective and individual ethics?

A
  • Collective: RTCs are used to properly test treatments for efficacy and safety.
  • Individual: - No guarantee of benefit
    - May cause harm
    - Allocate treatment by chance
    - May confer benefits and.place burdens.
70
Q

When referring to ethics, what is clinical equipoise?

A
  • When there’s reasonable uncertainty or genuine ignorance about a better treatment or intervention.
71
Q

When referring to RTCs what does scientifically robust mean?

A
  • Asks a valid question
  • Addresses an important or relevant question
  • Addresses biases/confounding
  • Has potential to reach a sound conclusion.
  • Can justify alternate treatment
  • Monitoring required
  • Acceptable risks
  • Procedures for publication
72
Q

What is ethical recruitment?

A
  • Appropriate exclusion

- Inappropriate exclusion

73
Q

What does voluntary mean in RCTs?

A
  • Decision should be free from coercion and manipulation or the perception that coercion or manipulation has occurred.
74
Q

What are the problems with expert reviews?

A
  • Implicit assumptions
  • Opaque methodology
  • Not reproducible
  • Biased
  • Subjective
75
Q

What are the benefits of using a systematic review?

A
  • Explicit assumptions
  • Transparent methodology
  • Reproducible
  • Unbiased
  • Objective
76
Q

What is the definition of a systematic review?

A
  • Overview of primary studies that used explicit and reproducible methods.
77
Q

Why is a systematic review a good method?

A
  • Clearly focused questions
  • Explicit statements about types of study/participants/interventions/outcome measures
  • Systematic literature search
  • Selection materials
  • Appraisal
  • Synthesis (inclusion of meta-analysis)
78
Q

What is the definition of meta-analysis?

A
  • Quantitative synthesis of results of two or more primary studies that addresses the same hypothesis in the same way.
79
Q

What is the purpose of meta analysis?

A
  • Facilitate synthesis of a large number of study results
  • Systematically collate study results
  • Reduce problems of interpretation due to variations in sampling
  • Quantify effect sizes and their uncertainty as an estimate
80
Q

What is a pooled estimate OR?

A
  • OR and CI calculated for meta-analysis
  • Combined to give a pooled estimate OR
  • Studies are weighted according to size and uncertainty of OR (smaller EF -> greater weight to result)
81
Q

Outline a forest plot.

A
  • Individual OR with their CI on either side
  • Size of square is proportional to weight (smaller CI greater the weight)
  • Diamond is pooled estimate, OR is dotted line from centre, Edges of diamond are the pooled CI.
  • Solid line is null hypothesis OR.
82
Q

In meta analysis heterogeneity is needed, what is this?

A
  • Studies being the same.

- No two studies are exactly the same

83
Q

What are the differences between fixed effect and random effect models?

A
  • Fixed effect: studies are estimating exactly the same size effect
  • Random effect: studies are estimating similar not the same size effect
84
Q

What are the two types of subgroup analysis?

A
  • Stratification by study characteristics- subsets of whole studies defined by study design.
  • Stratification by participant profile- data’s analysed by types of participants e.g. Age/sex
85
Q

Order the following in proneness to bias and confounding (less to more) cohort, case study, random, non-random.

A
  • Random
  • Non-random
  • Cohort
  • Case control
86
Q

How can studies be assessed?

A
  • Define a basic standard criteria and only include those that satisfy.
  • Give the higher quality sources a greater weighting so they have a greater influence on the pooled estimate.
87
Q

What is publication bias?

A
  • Only the studies with statistically significant or favourable results will be published and those with unfavourable results won’t.
  • Applies to smaller studies particularly.
88
Q

What is a funnel plot and what does it measure?

A
  • A plot of size of study against measure of effect.
  • Curves of best fit are produced either side of the true value.
  • If no publication bias then the funnel is balanced.
  • Publication bias.

Medicine Semester 1 (6 decks)

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