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Diagnostic Reasoning and Evidence-Based Medicine Flashcards

6 cards from real DO practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.

Read the first 6 Diagnostic Reasoning and Evidence-Based Medicine flashcards as text

  1. Bayes' theorem in clinical medicine states that the post-test probability of disease depends on which two factors?

    Answer: Pre-test probability and test likelihood ratio

    Post-test probability integrates the pre-test probability (prevalence/clinical suspicion) with the test's likelihood ratio to determine how much a result changes disease probability.

  2. When a test has high specificity, a positive result is most useful for:

    Answer: Ruling IN disease (SpPin)

    A highly specific test has few false positives, so a positive result strongly indicates true disease and is used to rule IN the diagnosis (SpPin mnemonic).

  3. A 55-year-old male smoker presents with hemoptysis and a new lung mass on CXR. The pre-test probability for lung cancer is estimated at 60%. The CT-guided biopsy has a sensitivity of 95% and specificity of 99%. A positive biopsy result essentially:

    Answer: Confirms the diagnosis (very high post-test probability)

    With high pre-test probability and a highly specific test showing a positive result, the post-test probability of malignancy approaches near certainty.

  4. Which statistical measure describes the strength of association between an exposure and outcome in a case-control study?

    Answer: Odds ratio (OR)

    Case-control studies calculate the odds ratio because they sample based on outcome (case/control), making it impossible to calculate true incidence rates needed for relative risk.

  5. Confirmation bias in clinical diagnosis refers to:

    Answer: Seeking information that confirms an initial diagnosis while ignoring contradictory evidence

    Confirmation bias leads physicians to favor data supporting their initial hypothesis and discount findings that suggest an alternative diagnosis.

  6. A 95% confidence interval (CI) for a relative risk that does NOT cross 1.0 indicates:

    Answer: The result is statistically significant at the p < 0.05 level

    When a 95% CI for RR excludes 1.0 (no effect), the finding is statistically significant at the corresponding p < 0.05 threshold.

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