Sepsis mortality score for the prediction of mortality in septic patients

To derive a prediction equation for 30-day mortality in sepsis using a multi-marker approach and compare its performance to the Sequential Organ Failure Assessment (SOFA) score. This study included 159 septic patients admitted to an intensive care unit. Leukocytes count, procalcitonin (PCT), interleukin-6 (IL-6), and paraoxonase (PON) and arylesterase (ARE) activities of PON-1 were assayed from blood obtained on ICU presentation. Logistic regression was used to derive sepsis mortality score (SMS), a prediction equation describing the relationship between biomarkers and 30-day mortality. The 30-day mortality rate was 28.9%. The SMS was [еlogit(p)/(1+еlogit(p))]×100; logit(p)=0.74+(0.004×PCT)+(0.001×IL-6)−(0.025×ARE)−(0.059×leukocytes count). The SMC had higher area under the receiver operating characteristic curve (95% Cl) than SOFA score [0.814 (0.736–0.892) vs. 0.767 (0.677–0.857)], but is not statistically significant. When the SMS was added to the SOFA score, prediction of 30-day mortality improved compared to SOFA score used alone [0.845 (0.777–0.899), p=0.022]. A sepsis mortality score using baseline leukocytes count, PCT, IL-6 and ARE was derived, which predicted 30-day mortality with very good performance and added significant prognostic information to SOFA score. •A sepsis mortality score to predict 30-day mortality in critically ill patients is proposed from five biomarkers.•Logistic regression was used to create the Sepsis Mortality Score.•Leukocytes count, procalcitonin, interleukin-6, arylesterase and paraoxonase activities of paraoxonase-1 were used.•This multi-marker approach predicted 30-day mortality with very good performance in our sepsis cohort.•This added significant prognostic information to the Sequential Organ Failure Assessment score.