Acute Care Diagnostic Collaboration: Bayesian modeling comparative diagnostic assessment of lactate, procalcitonin and CRP in risk stratified population by Mortality in ED (MEDS) score

Objective To assess and compare the diagnostic value of lactate, procalcitonin (PCT) and C-reactive protein (CRP) in low, moderate, and high-risk stratified population applying Mortality in Emergency Department (MEDS) risk score using Bayesian statistical modeling. Methods MEDS criteria was used to risk stratify into low, moderate and high risk. Each population was attributed a percentage risk, and used as pre-test probability in the Bayesian nomogram. Sensitivity and specificity lactate, PCT and CRP were attained from pooled meta-analysis data. Absolute and relative diagnostic gains were calculated. Results Pooled diagnostic quality data obtained from a meta-analysis reflected sensitivity for PCT of 77% and specificity of 79%, for lactate sensitivity 49.1% and specificity 74.3% and CRP yielded a sensitivity of 75% and specificity 67%. likelihood ratios (LR) calculations for PCT were LR + 3.67 and LR − 0.29; for lactate LR + 1.88 and LR − 0.69; CRP LR + 2.27 and LR − 0.37. When computed in Bayesian nomogram post-test probabilities for LR + were as follows: for PCT low risk absolute gain of 11.7% and relative gain of 220%; moderate absolute gain 25.7% relative gain 148.5%; for high risk absolute gain 25.1% and relative gain 42.6%. Lactate LR + results for low risk absolute gain of 4.7% and relative gain of 88.6%; moderate absolute gain 10.7% and relative gain 61.8%; high risk relative gain 14.1% and relative gain 23.9%. CRP results for low population and LR + absolute gain 5.7% and relative gain 107.5%; moderate risk 14.7% absolute gain and 84.9% relative gain; high risk 77% post-test 18.1% absolute gain and 30.7% relative gain. Conclusion Bayesian statistical model demonstrated the superior diagnostic quality of PCT. For ruling out severe disease, lactate yielded a higher benefit with increased relative gain with negative LR.