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Year 3 Exams > Medical stats > Flashcards

Medical stats Flashcards

1
Q

levels of prevention

A

Primordial- health promotion using legislation .g. banning alcohol

  • prevent development of risk factors

Primary- vaccination, exercise

  • prevent onset of disease

Secondary- screening for diseases to catch early and treat

  • catch it early

Tertiary- treatment- stopping the progress of established disease

  • reduce mortality and morbidity
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2
Q

health improvement examples

A
  • Smoking cessation
  • Public mental health
  • Sexual health services
  • Substance misuse services
  • NHS health checks
  • Weight management
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3
Q

five criteria for screening

A
  1. The condition
  2. The test
  3. The intervention
  4. The screening programme
  5. Implementation
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4
Q

the condition

A

important health problem

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5
Q

the test

A
  • sage, precise and validated screening tool
  • acceptable to target population
  • diagnostic test available for those who test tissue
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6
Q

the intervention

A

effective treatment if found to have condition

  • treating early should give better prognosis
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7
Q

screening programme

A
  • Proven effectiveness in reducing mortality or morbidity
  • beenfit gaine dby individual should outwieght nay harm
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8
Q

sensitivity

A

is the proportion of cases which the test correctly detects

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9
Q

specificity

A

is the proportion of non-cases which the test correctly detects

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10
Q

positive predictive value

A

is the proportion of positive tests who are cases

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11
Q

negative predictive value

A

proportion pf negative cases who are not cases

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12
Q

screening is diff to evaluate because

A
  • Lead to time bias
  • Length time bias
  • Selection bias
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13
Q

lead time bias

A
  • Early diagnosis falsely appears to prolong survival
  • Screened patients appear to survive longer, but only because they were diagnosed earlier
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14
Q

length time bias

A
  • Screening programmes better at picking up slowly growing, unthreatening cases than aggressive, fast growing ones
  • Diseases that are detectable through screening are more likely to have a favourable prognosis, may indeed never have caused a problem
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15
Q

selection bias

A

Studies of screening are often skewed by healthy volunteer effect

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16
Q

calculate

A

the positive predictive value is 132/1,115 = 0.118, or 11.8%.

17
Q

null value for odds ratio

A

1.0

18
Q

null value for risk ratio

A

0

19
Q

answer

A

Answer: b
An odds ratio of less than the null value of 1.0 indicates that being a gym member might be a protective factor against depression (but note that the confidence interval spans the null value of 1).

20
Q

Types of study design

A
  • Studies can be qualitative or quantitative

1) Experimental- intervention of the researcher, observation of what happens

  • Randomised controlled trials (RCT)
    • Reduce confounding/ bias
    • Compare two treatments
    • Compare new treatment against placebo/ usual care
  • Non-randomised controlled trials
    • Comparing results of two treatment pathways one used in one hospital, the other in a different hospital

2) Observational- subjects are observed, no action from researcher

  • Cohort studies
  • Case- control studies
    • May be vital in identifying new emerging diseases
    • May be useful in suggesting aetiological associations
  • Cross-sectional
    • Often studies of prevalence
    • May explore the link between disease and possible exposure
    • Issue with confounding
    • Often used to address questions of “time, place, person”
  • Ecological

Reviews

Systematic reviews combine study results together

  • RCT
  • Observational studies
  • Qualitative studies
21
Q

forest plots

A
22
Q

forest plots

A

a graph that compares several clinical or scientific studies studying the same thing → i.e. for representation of a meta-analysis

23
Q

what does the size of the squares represent

A
  • proportion of weight given to each study i.e. effect
  • e.g. size of study
24
Q

what do the horizontal lines represent

A

95% confidence intervals

  • if it crosses 1- no significant difference in outcomes
    • OR
25
Q

what does the vertical line represent

A
  • the null hypothesis OR
    • 1= no difference
26
Q

what does the diamond represent

A
  • Meta-analysis estimates
  • width of the diamond represents the confidence intervals
27
Q

confidence intervals above >1 or <1

A
  • significant results
  • 0.05%
28
Q

analyse this forest plot

A

Example interpretation

  • 6 out of the 7 RCTs had an OR > 1.00 indicating greater odds for survival amongst patients taking aspirin after MI
  • Only 1 RCT (the largest) had a statistically significant result, but its OR was less than the other RCTs with an OR > 1.00
  • Pooled estimate OR = 1.11 (95% CI: 1.04 to 1.19) leads to the conclusion that aspirin increases the chance of surviving after a MI (p<0.05)

Year 3 Exams (25 decks)

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