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EVIDENCE BASED MEDICINE

This article delves into the critical appraisal of therapy papers, focusing on the validity of results and their applicability in patient care. It provides a methodology to assess the study design and addresses key questions to determine the credibility of the findings.

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EVIDENCE BASED MEDICINE

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  1. EVIDENCE BASED MEDICINE Effectiveness of therapy Ross Lawrenson

  2. Critically appraising a therapy paper

  3. Critical Appraisal of a therapy paper - methodology • When critically appraising a paper ask yourself three questions: • Are the results valid? • What are the results? • Will the results help me in caring for my patients? • Go to the therapy worksheet for the complete list of questions

  4. I. Are the results valid? • In other words was this a well designed study in a relevant population. The best study design to answer a therapy question is a randomised controlled trial. • Go through the worksheet questions 1- 6 to help you decide whether you are likely to believe the results of the paper you are considering.

  5. 1. Did the study address a clearly focused question? • Can you define • The population they studied • The intervention • The comparison group • The outcomes

  6. 2. Was the assignment of patients randomised?

  7. Efficacy versus effectiveness

  8. Efficacy versus effectiveness • Efficacy - does receiving treatment work under ideal conditions?

  9. Efficacy versus effectiveness • Efficacy - does receiving treatment work under ideal conditions? • Effectiveness - does offering treatment help under ordinary circumstances?

  10. Observation versus experimental studies.

  11. Observation versus experimental studies • A study population of 2000 patients with acute coronary heart disease of whom half receive a certain intervention and the other half do not. Of the 2000 patients, 700 have arrhythmia "X" and 1300 do not.

  12. Observation versus experimental studies • A study population of 2000 patients with acute coronaries of whom half receive a certain intervention and the other half do not. Of the 2000 patients, 700 have arrhythmia "X" and 1300 do not. • X(+) = Patients with arrhythmia "X" have a mortality of 50% • X(-) = Patients without arrhythmia have a mortality of 10%.

  13. Observational study No intervention Intervention X(-) X(+) X(-) X(+) 800 200 500 500 300 Deaths 180 Relative risk = 0.6

  14. Randomised controlled trial No intervention Intervention X(-) X(+) X(-) X(+) 650 350 650 350 240 Deaths 240 Relative risk = 1

  15. Absolute risk • Incidence rate of the outcome in the population (can be the treated or the untreated population).

  16. Relative risk • Relative risk (RR) is the absolute risk in the treated group divided by the absolute risk in the untreated group (or vice versa)

  17. Randomised controlled trials • Because the randomised trial removes selection bias the result of the study should be believed over the evidence from the observational study i.e. the Relative risk is 1 (no difference in treatment) not 0.6 (which suggested a benefit from treatment.) • An example of this would be the use of HRT and the reduction in cardiovascular risk. Observational studies have shown a 50% reduction in CHD but the RCT showed no benefit. (References)

  18. 3. Were all patients who entered the trial properly accounted for and attributed at its conclusion? (a) Was the follow up complete? - selection bias (b) Were the patients analysed in the groups to which they were randomised? - intention to treat analysis.

  19. Selection bias Randomised controlled trials Sample Population Treatment 1 Treatment 2 Outcomes Outcomes

  20. (a) Selection of study population

  21. (Should be representative of the general population to ensure external validity) trial sample population unsuitable (excluded)

  22. Sources of selection bias Non random sample is selected. e.g. Volunteers. Healthy worker. Hospital patients.

  23. Sources of selection bias Non random sample is selected. e.g. Volunteers. Healthy worker. Hospital patients. Unsuitable patients excluded

  24. Sources of selection bias Non random sample is selected. Volunteers. Healthy worker. Hospital patients. Unsuitable patients excluded Hard to trace people are omitted.

  25. Sources of selection bias Non random sample is selected. Volunteers. Healthy worker. Hospital patients. Unsuitable patients excluded Hard to trace people are omitted. Large number of refusals in the selected population.

  26. Sources of selection bias Non random sample is selected. Volunteers. Healthy worker. Hospital patients. Unsuitable patients excluded Hard to trace people are omitted. Large number of refusals in the selected population. Large number of people dropping out of the study or lost to follow up.

  27. (b) Intention to treat analysis.

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