Evidence based paediatrics

Question 1

Describe a crossover study and what is more ‘powerful’ than it.

Answer 1

Variation of RCT. All patients recieve treatments, but order is randomised and blinded.
RCT

Question 2

Describe a RCT and what is more powerful than it

Answer 2

Subjects are randomly assigned to one of two groups (experimental versus control) with the only expected difference being the outcome studied

Question 3

Describe a case-control study and what is more powerful than it.

Answer 3

Retrospective. Not conducted over time.
Researchers choose individuals with a particular characteristic (the cases) and compare features of interest with a control group of individuals who do not have the characteristic. This type of study is required for questions around causation.
Cohort, RCTs ,Crossover

Question 4

Describe a cohort study and what is more powerful than it

Answer 4

follow individuals with a particular condition or who receive a particular treatment and they are compared with another group of people who are not affected by the condition or who did not receive the treatment.
Crossover, RCTs

Question 5

Describe a cross-sectional study and what is more powerful than it

Answer 5

defined population is observed at a single point in time or at certain time intervals
case-control, Cohort, crossover RCTs

Question 6

Define Selection bias

Answer 6

is linked to the recruitment of patients; a cohort of individuals deciding not to participate in the study could lead to under- or overestimation of a particular effect or risk. Patients lost to follow-up, self-selection into a study and lack of randomisation are further examples.

Question 7

Define information bias

Answer 7

Occurs when patients are misclassified, for example, when individuals with a particular disease or exposure are classified as nondiseased or nonexposed due to an inaccuracy of diagnostic tests. Such a problem will invalidate outcomes.

Question 8

Define confounding variable

Answer 8

are variables that influence both the dependent variable and independent variable, causing a spurious association. Confounding variables are those that may compete with the exposure of interest (e.g. treatment)
in explaining the outcome of a study. For example, in a study about whether a lack of exercise (independent variable) leads to weight gain (dependent variable) in children, the number of calories consumed would be a confounding variable. Identifying possible confounders early on and controlling for them will assist in eliminating bias.

Question 9

Define number needed to treat

Answer 9

number of patients that need to be treated in order for one to benefit. For example, an NNT of 20 would be interpreted as ‘20 patients need to be treated to avoid one additional death’.

Question 10

Give an example of when a Chi squared test would be used

Answer 10

Chi-squared tests are commonly performed on 2 x 2 data, for example, to investigate if there is an association between maternal smoking (yes or no) and child’s asthma status (asthmatic or not asthmatic) in a given population

Question 11

What is the null hypothesis?

Answer 11

That we accept that there is no significant differeence between results. IF P value is <0.05, then we say it is significant and thus we REJECT the null hypothesis.

Question 12

What does a 95% confidence interval (95% CI) mean?

Answer 12

there is a 5% chance that the ‘true’ population mean lies outside the quoted range.

Question 13

How do you determine if there is significant result in confidence intervals following a given intervention?

Answer 13

95% CI do not overlap
e.g daily steps undertaken by the teenagers increased from 12.3k (95% confidence intervals (CI) 7.5 to 14.1) to 17.7k (95% CI 15.2 to 20.3) after the exercise programme

Question 14

When interpreting confidence intervals between means, the confidence interval crossing 0 means what?

Answer 14

the studied effect is not significant as zero indicates no difference between means

Question 15

When interpreting confidence intervals between means, the confidence interval being entierly negative or positive numbers means what?

Answer 15

the studied effect is significant as the 95% confidence interval does not cross zero

Question 16

When Interpreting a 95% CI for ratios (OR, RR etc), what does it mean if the CI crosses 1?

Answer 16

There is no difference between arms of the study and the outcome of the study can be interpreted as not statistically significant

Question 17

When Interpreting a 95% CI for ratios (OR, RR etc), what does it mean if the CI is <1 but does not cross it?

Answer 17

the intervention is likely to be less effective and, as the ratio does not cross 1, the findings are statistically significant

Question 18

When Interpreting a 95% CI for ratios (OR, RR etc), what does it mean if the CI is >1 and does not cross it?

Answer 18

the intervention is likely to be more effective and, as the ratio does not cross 1, the findings are statistically significant

Question 19

What does an odds ratio do?

Answer 19

Determine whether a particular exposure is a risk factor for a particular outcome and to compare the magnitude of various risk factors for that outcome.

Question 20

What does OR = 1 mean?

Answer 20

Observed outcome is the same in the two groups

Question 21

What does OR = <1 mean?

Answer 21

Intervention provides a poorer outcome

Question 22

What does OR = >1 mean?

Answer 22

Intervention provides a better outcome

Question 23

Describe relative risk

Answer 23

the probability that an event will occur, whether it be a desirable or undesirable event. It explains how many times more likely that an event will occur in the treatment/intervention/exposure group, relative to the control group.

Question 24

What does RR = 1 mean?

Answer 24

No difference in given event occuring between two groups

Question 25

What does RR <1 mean?

Answer 25

Given even less likely to occur with exposure

Question 26

What does RR > 1 mean?

Answer 26

Given event more likely to occur with exposure

Question 27

Define risk difference (RD)

Answer 27

The difference in risk of a condition, such as a disease, between an exposed group and an unexposed group.
If RR1 is the disease risk in an exposed population and RR2 is the disease risk in a nonexposed population then the risk difference (RD) equals RR1–RR2. RD can therefore be a number between -1 and +1.

Question 28

What does RD = >0 mean?

Answer 28

Increased risk in exposed group

Question 29

What does RD = 0 mean?

Answer 29

No difference in risk between groups

Question 30

What does RD =<0 mean?

Answer 30

Decreased risk in exposed group

Question 31

Define Specificity

Answer 31

Probability test is negative when disease is absent

Question 32

Define Sensitivity

Answer 32

Probability test is positiive when disease is present

Question 33

Define positive predicitive value

Answer 33

Probability Test is postitive when disease is absent

Question 34

Define negative predicitive value

Answer 34

Probability test is negative when disease is absent