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

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Abstract

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.

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