Derivation and Validation of a Biomarker-Based Clinical Algorithm to Rule Out Sepsis From Noninfectious Systemic Inflammatory Response Syndrome at Emergency Department Admission: A Multicenter Prospective Study

Objectives: To derive and validate a predictive algorithm integrating a nomogram-based prediction of the pretest probability of infection with a panel of serum biomarkers, which could robustly differentiate sepsis/septic shock from noninfectious systemic inflammatory response syndrome. Design: Multicenter prospective study. Setting: At emergency department admission in five University hospitals. Patients: Nine-hundred forty-seven adults in inception cohort and 185 adults in validation cohort. Interventions: None. Measurements and Main Results: A nomogram, including age, Sequential Organ Failure Assessment score, recent antimicrobial therapy, hyperthermia, leukocytosis, and high C-reactive protein values, was built in order to take data from 716 infected patients and 120 patients with noninfectious systemic inflammatory response syndrome to predict pretest probability of infection. Then, the best combination of procalcitonin, soluble phospholypase A2 group IIA, presepsin, soluble interleukin-2 receptor α, and soluble triggering receptor expressed on myeloid cell-1 was applied in order to categorize patients as "likely" or "unlikely" to be infected. The predictive algorithm required only procalcitonin backed up with soluble phospholypase A2 group IIA determined in 29% of the patients to rule out sepsis/septic shock with a negative predictive value of 93%. In a validation cohort of 158 patients, predictive algorithm reached 100% of negative predictive value requiring biomarker measurements in 18% of the population. Conclusions: We have developed and validated a high-performing, reproducible, and parsimonious algorithm to assist emergency department physicians in distinguishing sepsis/septic shock from noninfectious systemic inflammatory response syndrome. Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's website (https://ift.tt/29S62lw). Supported, in part, by the Italian Ministry of Health. Drs. Mearelli, Fiotti, Giansante, Casarsa, De Helmersen, Altamura, Barbati, and Bregnocchi disclosed government work. Dr. Orso received support for article research from the Italian Ministry of Education, Universities and Research. The remaining authors have disclosed that they do not have any potential conflicts of interest. For information regarding this article, E-mail: filippome@libero.it Copyright © by 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.

https://ift.tt/2rwV9ee