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5 Written questions

5 Multiple choice questions

  1. - greatest when pre-test likelihood is intermediate to high probability of CAD
    - Little value in testing individuals who are asymptomatic
  2. 12 lead ECG monitored at:
    - rest
    - last minute of each stage
    - each minute during recovery)
    BP monitored at:
    - rest
    - last minute of each stage unless response is abnormal
    - each minute during recovery
    RPE monitored at:
    - last minute of each stage
    - ask more often towards end of test
    Symptoms:
    - include angina or chest pain
    - dyspnea or SOB
    - ask about other discomforts
  3. 1) Determine # of ppl in population w/ disease
    2) Determine # w/ disease that will have '+' testing (# w/ disease x 0.7)
    3) Determine # w/ disease that will have '-' test (Total diseased # - # w/ '+' test)
    4) Do the same for those w/o disease
  4. Absolute:
    - potential serious medical complications of ETT is completed
    - risks of performing ETT outweigh benefits
    Relative:
    - a potential medical concern is present
    - benefit vs. risk of performing ETT should be evaluated
  5. - unstable angina
    - acute infection
    - uncontrolled arrhythmia

5 True/False questions

  1. List some indicators for stopping an ETT.- treadmill
    - leg ergometer
    - arm ergometer

          

  2. What factors do you look at when determining the pretest likelihood of CAD?- Age - as you age, pretest likelihood increases
    - Gender - women have lower pretest likelihood than men
    - Symptoms - those w/ symptoms have much higher pretest likelihood

          

  3. Describe the sensitivity, specificity of exercise testing diagnostics with ECG. What is a better method?- Sensitivity = 70% (7 of 10 patients w/ CAD will have '+' test)
    - Specificity = 90% (9 of 10 patients w/o CAD will have '-' test)

          

  4. What is pretest likelihood?- treadmill
    - leg ergometer
    - arm ergometer

          

  5. What is the formula used to determine positive predictive value and negative predictive value1) Determine # of ppl in population w/ disease
    2) Determine # w/ disease that will have '+' testing (# w/ disease x 0.7)
    3) Determine # w/ disease that will have '-' test (Total diseased # - # w/ '+' test)
    4) Do the same for those w/o disease

          

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