Week 9

Question 1

Define prognosis

Answer 1

Question 2

What questions can be asked to identify a prognosis set up?

Answer 2

Examine selected predictive
variables and assess their influence
on some future outcome.

Question 3

How do prognosis studies guide clinical decisions?

Answer 3

Question 4

How are prognostic studies interpreted?

Answer 4

Question 5

Find the probability of red balls if there is a total of 12 balls with 3 red

Answer 5

Question 6

Find the odds of red balls if there is a total of 12 balls with 3 red

Answer 6

Question 7

What are the study designs associated with prognostic studies?

Answer 7

Question 8

Explain prospective cohort studies

Answer 8

Question 9

What type of study?

Answer 9

prospective cohort

Question 10

Assess

Answer 10

Question 11

What is used to assess the magnitude of association in prognostic studies?

Answer 11

Question 12

Explain retrospective case control studies

Answer 12

Question 13

What type of EBP question, research design, statistically significant/not?

Answer 13

Question 14

What type of study?

Answer 14

Retrospective case control

Question 15

Explain the difference in time direction, outcome measurement, cost & time, and bias risk in prospective cohort vs retrospective case control

Answer 15

Question 16

Create a PICO, search string, EBP question type, and research design

Answer 16

Question 17

Explain odds ratio

Answer 17

Question 18

How is the odds ratio interpreted?

Answer 18

Question 19

Explain statistical significance vs magnitude of effect

Answer 19

Question 20

List formula of RR and OR

Answer 20

Question 21

Assess the OR

Answer 21

Question 22

Assess OR and what it means

Answer 22

*86%

Question 23

Explain how OR is interpreted

Answer 23

Question 24

Explain confidence intervals

Answer 24

Question 25

What does it mean to have a 95% confidence interval?

Answer 25

Question 26

Explain

Answer 26

* Age (OR = 1.198, p = 0.102) * A 1-year increase in age is associated with a 19.8% higher likelihood of reinjury. * However, the p-value is not statistically significant (p > 0.05), meaning this relationship may be due to chance. * Body Mass Index >30 kg/m² (OR = 2.398, p = 0.031) * Individuals with a BMI over 30 are 2.4 times more likely to experience reinjury. * The p-value is significant (p < 0.05), suggesting a meaningful relationship. * The 95% confidence interval (1.79 – 3.56) does not include 1.0, further supporting significance. * Smoker (OR = 1.475, p = 0.070) * Smokers are 1.48 times more likely to experience reinjury. * The p-value is not statistically significant (p > 0.05), so the relationship is uncertain. * The confidence interval (0.93 – 4.05) includes 1.0, meaning the effect could be negligible. * Prior Injury (OR = 6.739, p = 0.005) * Having a prior injury is strongly associated with reinjury, with a 6.74 times higher likelihood. * The p-value is significant (p < 0.05), confirming its predictive importance. * The 95% CI (4.32 – 7.23) does not include 1.0, reinforcing statistical significance. * Job Satisfaction (OR = 0.790, p = 0.022) * Higher job satisfaction is protective, as it reduces the odds of reinjury by 21% (OR < 1). * The p-value is significant (p < 0.05), indicating a meaningful association. * The confidence interval (0.69 – 0.98) does not include 1.0, supporting the significance of the finding. Key Takeaways * Significant Predictors of Reinjury: High BMI, prior injury, and low job satisfaction. * Non-Significant Predictors: Age and smoking (p > 0.05). * Largest Risk Factor: Prior injury (OR = 6.739), meaning those with a prior injury are at the highest risk for reinjury. * Protective Factor: Job satisfaction (OR = 0.790), suggesting that job satisfaction plays a role in reducing reinjury risk.

Question 27

Create a PICO, search string, type of EBP question, statistically significant/not, and research design

Answer 27

Question 28

Explain OR vs RR

Answer 28

Question 29

If a race horse runs 100 races and wins 25 times and loses the other 75 times, what is the probability of winning?

Answer 29

Question 30

Explain RR and list formula

Answer 30

Question 31

What are the value ranges for RR?

Answer 31

Question 32

Calculate RR and OR

Answer 32

Question 33

Explain OR vs RR in practice

Answer 33

Question 34

Explain hazard ratio

Answer 34

Question 35

What is hazard ratio used for?

Answer 35

Question 36

How does HR differ from a risk?

Answer 36

Question 37

What are the value ranges of HR?

Answer 37

Question 38

Give example values of HR study reports

Answer 38

Question 39

Explain

Answer 39

Question 40

How do prognostic studies assess credibility?

Answer 40

Question 41

Under which conditions does the OR closely approximate RR?

Answer 41

when the disease is rare

Question 42

How is CI and statistical significance related?

Answer 42

Question 43

What are the limitations of OR?

Answer 43

Question 44

From this lesson, what can be applied to PT practice?

Answer 44