Alejandro Baez – A Bayesian Approach to Clinical Decision Making

Dr. Amado Alejandro Baez is the Emergency Medicine Program Director at the Jackson Memorial Hospital/ University of Miami Miller School of Medicine and has published extensively in Emergency Medicine, Trauma and Critical Care. He is a rock star – in fact, one of his research collaboratives is the ACDC project whose goal is to incorporate bayesian statistical modeling into clinical practice by using some of the most commonly used clinical scoring systems we use on a daily basis…. ROCK ON.

In this lecture, Dr Baez discusses the application of Bayesian statistics to everyday clinical decisions and some of the work done by his ACDC project.

Review and summary by Dr. Rabin Shrestha 

Bayes’ Theorem




  • P(A) is the prior probability of A (that is before there we know that event B occurred)
  • P(A/B) is the posterior probability of A (given that event B has occurred)

Determining the pretest probability of a disease

  • Clinical decision rules like the Wells’s criteria for pulmonary embolism held guide the expected probability prior to a test being done
  • Other scientific evidence from prior studies
  • Experience or expert opinion (gut feeling) – if nothing else is available

Determining the probability of finding in diseased and healthy persons

  • Test characteristics – sensitivity and specificity of diagnostic tests
  • Clinical studies and meta-analysis

Clinical application

  • You can develop a post-test probability for detecting a disease by combining pre-test probability and likelihood ratios of a given diagnostic test
  • Likelihood ratio – Probability of the finding in diseased persons/probability of finding in non-diseased personsLR
  • Post test odds = [Pretest odds * likelihood ratio] (Odds ratio form of Bayes Theorem)
  • We can use Bayes’ nomogram to predict the post-test probability


  • Bayes Nomogram

Applications in the ACDC project

  • CT scan vs Ultrasonography in the assessment of acute appendicitis after the application of the Alvarado scoring system
  • Does VQ or CT scan add incremental gain of probability of PE after the Wells criteria
  • Comparative diagnostic assessment of lactate, CRP and procalcitonin for patients with sepsis
  • Comparison of lactate and procalcitonin with CURB 65 risk score as predictor of ICU admission
  • Diagnostic gain with a combined aortic dissection detection risk score and D-Dimer


Suggested Readings

  1. Kalil AC, Sun J. Bayesian methodology for the design and interpretation of clinical trials in critical care medicine: a primer for clinicians. Crit Care Med. 2014;42(10):2267-77. [PubMed]
  2. O’connor GT, Sox HC. Bayesian reasoning in medicine: the contributions of Lee B. Lusted, MD. Med Decis Making. 1991;11(2):107-11. [PubMed]
  3. Ashby D, Smith AF. Evidence-based medicine as Bayesian decision-making. Stat Med. 2000;19(23):3291-305. [PubMed]

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