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REVISION BDS > evidence based dentistry p162 > Flashcards

evidence based dentistry p162 Flashcards

1
Q

PICO

A

Participants - who is the review interested in studying
Intervention (Exposure) - what is the intervention(s) of interest
Comparison - what will the interventions be compared to
Outcome - which outcomes will tell you which intervention is most effective

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2
Q

what is CASP

A

Critical Appraisal Skills Programme

for RCTs and separate checklist of systematic review and meta analysis

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3
Q

section A in CASP

A

Are the results of the study valid?

  1. Did the review ask a clearly focused question
  2. Did the authors look for the right type of papers
  3. Did you think all the important relevant studies were included
  4. Did the review’s authors do enough to assess quality of the included studies
  5. If the results of the review have been combined was it reasonable to do so
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4
Q

Section B in CASP

A

What are the results?

  1. What are the results of the review
  2. How precise are the results
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5
Q

Section C in CASP

A

Will the results help locally?

  1. Can the results be applied to the local population
  2. Were all the important outcomes considered
  3. Are the benefits worth the harms and costs
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6
Q

prevalence

A

related to a specific point in time

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7
Q

incidence

A

is the rate something in a period of time

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8
Q

risk

A

what are the chances

outcome - something that might happen

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9
Q

risk =

A

number of events of interest / total number of observations

e.g. 24 people ski down a slope, 6 fall
6/24
risk of falling = 0.25 -> 25%

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10
Q

odds =

A

number of events of interest / number without the event

e.g. 24 people ski down a slope, 6 fall
6 fall/18 didnt fall = 0.33 odds of falling (usually not %)

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11
Q

why be wary of risk reduction

A

e.g new drug reduces prevalence of disease from 4.9% to 0.8%

Small difference

but as a risk reduction that is 84% reduction (false view given)

RELATIVE RISKS THAT SEEM LARGE MIGHT NOT MEAN MUCH IF STARTING RISK IS SMALL

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12
Q

absolute risk difference

A

Difference between groups
- Risk of group 1 = 63%
- Risk of group 2 = 18%
- ARD = 63-18 = 45%
If no benefit then ARD = 0

ARD = RISK 1 (%) - RISK 2 (%)

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13
Q

number needed to treat

A

is the number of patients youd need to treat to prevent one from developing disease/condition/outcome

NNT = 1/ARD

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14
Q

risk ratio

A

risk 1 / risk 2

e.g 63% and 18%
63/18 = 3.42
so person 3.42x more likely to get pain relief than someone in the placebo group

Can’t get 0 value for this, so if the answer comes to 1 then there is no difference in risk ratio between the two criteria

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15
Q

relevant risk reduction

A

RRR = RISK1 - RISK2 / RISK 1

e.g 63% and 18%
63-18/63
45/63
= 71% risk reduction

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16
Q

odds ratio

A

Ratio of odds of pain relief in the both groups (usually intervention/control studies)

Work out odds for each group, Then divide odds over one another

OR = ODDS 1/ ODDS 2
e.g
O1 -> 40/23 = 1.74
O2 -> 5/22 = 0.23

1.74/0.23 = 7.56
*Remember odds not in %!

17
Q

confidence intervals

A

quantify level of uncertainty of risk ratios etc

For a ratio where value of no difference is 1

  • If the confidence interval (contains/overlaps/straddles 1)
    • Insufficient evidence = that there is a difference between e.g paracetomol and placebo
  • if this interval does not (contain/overlaps/straddles 1)
    • Sufficient evidence to say there is a difference
    • i.e if value > 1
18
Q

CI straddles 1

A

Insufficient evidence = that there is a difference between e.g paracetomol and placebo

19
Q

CI doesn’t straddle 1

A

Sufficient evidence to say there is a difference
• i.e if value > 1

20
Q

systemic review process

A

1. Well formulated question
Using PICO

  • How effective is paracetamol (I) for pain relief (O) compared to placebo (C ) after surgical removal of lower wisdom teeth in adults (P)?

2. Comprehensive data search
• Medline
• Reference lists
• Hand Searching
• Multiple languages
• being aware of reporting bias
➡ Publication bias
➡ Time lag bias
➡ Language bias
➡ Citation bias

3. Unbiased selection and abstraction process
• Selection of relevant papers
• Data extraction to a predefined data extraction form
• Process should be conducted independently by >2 reviewers
• Clear reasons described for why papers were excluded

4. Assessment of papers
• Look at methodology
➡ How well the studies have been designed and conducted
• Process should be conducted by at least >2 reviewers
• Results of the reflection should be used in the analysis

5. Synthesis of data
• Pooling process
‣ Qualitative - narrative
‣ Quantitive - meta-analysis
➡ Using statistical methods to combine the results of different studies
➡ Integrate findings
➡ Pool data
➡ Identify overall trend

21
Q

tools for assessing quality of papers

A

comoposite scales

component approach

22
Q

adv of metal analysis

A

Increase in power

More precise

ability to answer questions not posed by individual studies

23
Q

disadv of meta analysis

A

Can be misleading

Should only be done when
✓Minimal differences across studies
✓Same outcome measure
✓Data in each study are available

24
Q

discontinuous (biniary) data

A

e.g illness or not/death or not/ birth or not

Odds ratio (OR)

Risk ratio (RR)

Percent risk reduction, or relative risk reduction (RRR)

Risk difference, or absolute risk reduction (RD)

Number needed to treat (NNT) (1/RD)

25
Q

continous data

A

e.g Blood pressure, weight, amount of pain

Weighted mean difference

  • can only be used when all the outcomes are using the same scale

Standardised mean difference

  • For when all the studies are assessing the exact same outcome but do it in a variety of ways
    e. g example of depressed patients but using varied psychometric scales to calculate it
26
Q

forest plot

A

Vertical line divides the graph - called the line of no effect

LHS - New treatment that has been more beneficial
RHS - No Tx or that a standard Tx has been more beneficial

the further to the left or further to the right it was, the more pronounced the benefit was found to be

If results close to or on the line = no effect

Boxes - size of study - bigger the box the bigger the study

Line through box - confidence interval

  • narrower the line the narrower the confidence interval
  • the wider the line = less certain

If the CI line touches the line of no effect when crossing the box then it means = no statistical signficance

Diamond = combined studies
height = combined study size
width = combined confidence interval
27
Q

clincal heterogenity

A
  • Variation in participants
  • Interventions
  • Outcomes
  • Study design
28
Q

metholodigical heterogeneity

A

Variation in methods used in studies e.g quality of allocation concealment

29
Q

statistical heterogeneity

A

Excessive variation in the results of studies
- Variation in treatment effects above that expected by chance

*Statistical heterogeneity = poor overlap of confidence intervals - i.e outliers whose horiztontal lines don’t overlap others vertically

If P<0.1 then stats are too heterogenous so should probably not pool together

30
Q

sub group analyses when

A

Where it is expected in advance that certain features may alter the effects of an intervention
e.g Gender, age groups, specific disease subtypes

31
Q

evaluating results of meta analysis (Cochrane)

A

G - grading of
R - Recommendations
A - Assessment
D - Development and
E - Evaluation

32
Q

factors that lower quality in a study (5)

A

High or unclear risk of bias

  • Due to design issues or poor conduct of studies

Inconsistency between studies

  • Heterogeneity

Indirectness

  • PICO- were all studies similar?

Imprecision

  • Numbers and CIs

Publication bias

  • Likely that negative/null results not published?
33
Q

summary of findings table

A

Summary of the key findings from a systematic review
It presents

  • Quality of the evidence
  • Magnitude of the effect
  • Reasons behind judgements

Format

  1. PICO
  2. Outcomes
  3. Results
    - No. studies and participants
    - Relative and Absolute effects
    - Certainty and quality of evidence
    - Notes

REVISION BDS (43 decks)

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