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Evidence based general kasr einy
Evidence based general kasr einy
Evidence based general kasr einy
Evidence based general kasr einy
Evidence based general kasr einy
Evidence based general kasr einy
Evidence based general kasr einy
Evidence based general kasr einy
Evidence based general kasr einy
Evidence based general kasr einy
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Evidence based general kasr einy

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  • 1. Good clinical practice
    • Evidence-based medicine
    • Biological knowledge of health and disease (Rational of clinical judgment).
    • Awareness of social and cultural values.
  • 2. Clinical Reasoning
    • Evidence
    • Doctor
    • Patient
  • 3. Clinical reasoning: different scenarios 1 Cancer treatment 2 Infertility treatment
  • 4. Problems With Evidence-Based Medicine in Infertility
    • Insufficient evidence to support
    • some diagnostic tests.
    • Many treatment modalities.
  • 5. Problems with Evidence Based Infertility Treatment Problems of Diagnosis (Example) Semen analysis: Count : 80,60,40,20, less Motility Abnormal forms
  • 6. Problems with evaluating evidence Errors
    • Type I error:
      • P<0.05: we accept this chance of error (5%). The error could be inflated by a subgroup analysis.
    • Type II error: (more common)
      • Investigators did not detect a difference when a difference actualy exists.
      • We accept 20% error = power of the study is 80%.
  • 7. Problems with evaluating evidence
    • Confounding factor:
    • Factor associated with both treatment (as risk factor) and the outcome under study.
    • e.g.: low dose contraceptive pills.
  • 8. Problems with evaluating evidence
    • Bias: is systematic error in collection or interpretation of study information.
      • Selection bias:
        • Dissimilar selection criteria.
      • Information bias:
        • IUI*PID
  • 9. Problems with evaluating evidence Number needed to treat
    • Until recently, it was acceptable to look for (P values) in the results and the difference is considered significant if P <0.05.
    • The magnitude of the effect of the intervention is of utmost clinical importance to evaluate the implications of this significance.
  • 10. we should remember that what is statistically significant might not always be clinically relevant

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