Pre-test probability assessment

Pre-test probability assessment

Pre-test probability assessment

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Pre-Test Probability - The Educated Guess

  • The likelihood of a specific disease before a diagnostic test result is known. It's your clinical intuition quantified.
  • Calculated based on:
    • Patient demographics (age, sex)
    • History and physical examination findings
    • Local disease prevalence
  • Crucial for deciding if a test is necessary and for interpreting the result.
  • Categorized as low, intermediate, or high. This guides your next step: test, treat, or reassure.
  • Helps avoid over-investigation in low-probability scenarios.

⭐ A test's utility is highest when the pre-test probability is intermediate (~50%). In very low or very high probability, the test result is less likely to change management.

Pre-test vs. Post-test Probability and Treatment Decisions

Likelihood Ratios - Test Power-Ups

Likelihood Ratios (LRs) quantify a test's power to change diagnostic certainty, being more clinically useful than sensitivity or specificity alone.

  • Positive LR (LR+): Multiplies the odds of disease given a positive test.

    • Formula: $LR+ = Sensitivity / (1 - Specificity)$
    • >10 → Strong evidence to RULE IN disease.
    • 5-10 → Moderate evidence.
  • Negative LR (LR-): Multiplies the odds of disease given a negative test.

    • Formula: $LR- = (1 - Sensitivity) / Specificity$
    • <0.1 → Strong evidence to RULE OUT disease.
    • 0.1-0.2 → Moderate evidence.

Fagan's Nomogram for Pre-test and Post-test Probability

⭐ A test with an LR of 1 is uninformative. LRs of 0.2 and 5 correspond to changes in probability of approximately -30% and +30% respectively.

Post-Test Probability - The Probability Flip

  • Post-test probability (PTP) is the probability of a patient having the disease after a test result is known. It quantifies the "probability flip".

  • It is calculated by converting pre-test probability to odds, multiplying by the Likelihood Ratio (LR), and converting post-test odds back to probability.

    • $Pre-Test Odds \times Likelihood Ratio = Post-Test Odds$
    • $Odds = P / (1 - P)$
  • 📌 SPIN & SNOUT

    • A SPecific test, when Positive, helps Rule IN (High LR+).
    • A SNensitive test, when Negative, helps Rule OUT (Low LR-).

⭐ A test with an LR+ > 10 or an LR- < 0.1 is considered very strong, causing a large and often conclusive shift in post-test probability.

Fagan's Nomogram for Pre-test and Post-test Probability

Testing & Treatment Thresholds - The Action Points

  • Testing Threshold (TT): The probability below which the possibility of disease is so low, no test is ordered. Action: Withhold test & treatment.
  • Treatment Threshold (TxT): The probability above which the disease is likely enough to start treatment without further testing. Action: Treat empirically.
  • The zone between TT and TxT is the testing zone, where diagnostic tests are most useful.

⭐ In suspected DVT, a low Wells score (low PTP) might lead to a D-dimer test (ruling out), while a high score (high PTP) can justify proceeding directly to Doppler US, effectively raising the testing threshold.

High-Yield Points - ⚡ Biggest Takeaways

  • Pre-test probability (PTP) is the clinical suspicion of a disease before testing, based on history, examination, and local prevalence.
  • Diagnostic tests are most useful when the PTP is intermediate, as this is the zone of maximum uncertainty.
  • In cases of very high PTP, it may be appropriate to start empirical treatment without further testing.
  • For very low PTP, the best course is often watchful waiting, avoiding unnecessary tests and false positives.

Practice Questions: Pre-test probability assessment

Test your understanding with these related questions

A scientist is studying the characteristics of a newly discovered infectious disease in order to determine its features. He calculates the number of patients that develop the disease over several months and finds that on average 75 new patients become infected per month. Furthermore, he knows that the disease lasts on average 2 years before patients are either cured or die from the disease. If the population being studied consists of 7500 individuals, which of the following is the prevalence of the disease?

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