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Decision making in situations of uncertainty

Decision making in situations of uncertainty. 1. 65 yr male presents with UGI bleed. He had angioplasty and stenting two months ago. Should he continue antiplatelet agents? 2. 85 yr male presents with acute inferior MI to hospital in Dawson Creek. Should he be given thrombolysis?

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Decision making in situations of uncertainty

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  1. Decision making in situations of uncertainty

  2. 1. 65 yr male presents with UGI bleed. He had angioplasty and stenting two months ago. Should he continue antiplatelet agents? • 2. 85 yr male presents with acute inferior MI to hospital in Dawson Creek. Should he be given thrombolysis? • 3. At what level should anti retroviral therapy be initiated for HIV infection? CD 200? CD 350? CD 500?

  3. IN EACH SCENARIO THERE IS • 1. Uncertainty • 2. Tension between Risks and Benefits: a “trade off” • 3. A specific decision is identified.

  4. MEDICAL DECISION ANALYSIS

  5. Patient • 76 yr female with chronic renal failure. She presented with volume overload/CHF and had to start hemodialysis. • While getting her hemodialysis she had several episodes of atrial fibrillation. • Hx of DM, Hypertension;

  6. Anti Coagulate?

  7. RISK OF STROKE IN AF • RR 2.4 in men and 3.0 in women.

  8. CHADS SCORE • CHF 1 point • Hypertension 1 point • Age>75 1 point • DM 1 point • Stroke or TIA history 2 points

  9. CHAD score = 4 • Her risk of stroke without anticoagulation = 6% • Her risk of stroke WITH anticoagulation = 2.2% • With ASA somewhere in the middle

  10. WHat is her risk of Major Bleeding? • How do we determine it?

  11. HemorR2hages risk index • Hepatic or renal disease • ethanol abuse • malignancy • older age • decreased platelets/or asa • prior bleed (2 points)

  12. hypertension • anemia • genetic factors • excessive fall risk • stroke • with greater than 5 points the risk of major bleeding was greater than 12.3%

  13. 4 points = 10.4% chance

  14. Hemodialysis? • Traditionally anticoagulants felt to be a contraindication to hemodialysis. • Now - not as much of an issue

  15. 2. Risk of Anticoagulation in dialysis patients • Division of Nephrology, Queen's University, Kingston, Ontario, Canada. • Studies of full-intensity anticoagulation and the 1 randomized controlled trial of low-intensity anticoagulation showed major bleeding episode rates ranging from 0.1 to 0.54 events/patient-year of warfarin exposure. These rates are approximately twice as high as those of HD patients receiving either no warfarin or subcutaneous heparin. LIMITATIONS: This review is based largely on data from observational studies in which bleeding rates may be confounded by comorbidity. Relatively small sample sizes may provide imprecise estimates of rates. • CONCLUSION: Low- and full-intensity anticoagulation use in HD patients is associated with a significant bleeding risk, which has to be balanced against any potential benefit of therapy. This has to be considered carefully when prescribing warfarin to HD patients.

  16. Increase risk of Intracranial Hemorrage with anticoagulation? • Use of Long-Term Anticoagulation is Associated With Traumatic Intracranial Hemorrhage and Subsequent Mortality in Elderly Patients Hospitalized After Falls: Analysis of the New York State Administrative Database. • Controlling for age, gender, and comorbidity, patients on LTA were 50% more likely to sustain a traumatic ICH after a fall (odds ratio 1.50; 95% confidence interval, 1.23–1.81; p < 0.0001). Furthermore, among patients who sustained an ICH, mortality was 1.57-fold greater in patients on LTA (odds ratio 1.57; 95% confidence interval, 1.02–2.45; p 0.04). Conclusions: These data indicate that use of LTA is independently associated with traumatic ICH and subsequent mortality in elderly patients hospitalized after a fall. • J Trauma. 2007;63:519 –524.

  17. benefits of warfarin in This patient ? • Decreased risk of stroke.

  18. risks • Major Bleeding including ICH

  19. What are the strategic options?

  20. 1. Do nothing • 2. Anticoagulate with warfarin • 3. Take a middle ground • 4. Rythm control?

  21. Decision factors - patient • Risk taking behaviour • Specific aversions • eg. Aversion to bleed, or to stroke • Quality of Life factors • weekly blood tests • Worry.

  22. Decision factors - Physician • Biases • Framing

  23. Who makes the decision? • An Authority? • The Attending physician? • The Patient Family in consultation?

  24. Is there a Best decision? • This is a situation of uncertainty. We are faced with these decisions in circumstances like these every day in medicine. • Is there a way of determining the “best” decision? • What kinds of approaches can be used?

  25. MEDICAL DECISION ANALYSIS • A quantitative evaluation of outcomes that result from a set of choices. • A formal modeling of the process clinicians go through every day. • Decision Analysis (DA) makes the process explicit and amenable to examination, discussion and challenge.

  26. Problems appropriate for DA • Focus on a specific decision that must be made. • A trade off • Uncertainty

  27. USES of DA • SPECIFIC: Exploring strategies for Specific patient problems • GENERAL: Exploring Strategies for a class of patients.

  28. Steps in the Process • Frame the question and model the problem by creating a Decision Tree. • Estimate the relevant probabilities • Estimate the value of the outcomes • Analyze the tree by the calculating expected values. • Test the Model’s assumptions with Sensitivity Analysis.

  29. A Simple Decision Tree

  30. ASSUMPTIONS • Probability of winning • Black jack - .20 • Slot Machine - .01 • Winnings • Black Jack - $200 • Slot Machine - $1000

  31. Tension • Black Jack - Greater chance of success but the reward is less • Slot Machine - Less chance of winning but a bigger pot.

  32. Expected Value = • P(event) X Value + (1-P(event))X value

  33. Some basis principles • The tree must have balance. • Only two branches after each chance node • No embedded decisions • Symmetry • Order doesnt matter

  34. WHY DA? • Modeling of the problem sometimes helps to identify the best strategy • Symmetry of the model encourages us to identify new strategies we might not have considered • Challenging our assumptions. • Identifying essential probabilities we need to know. • Directing research in clinical useful ways.

  35. Helpful technique for explaining a complex situation to a family • Involving the patient and family directly in the decision making process through UTILITY ANALYSIS

  36. Sources of data

  37. THROMBOLYSIS IN THE ELDERLY

  38. Base line Probabilities

  39. Decision tree for thrombolysis in the elderly

  40. ANalysis of decision tree

  41. Sensitivity analysis

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