Format

Send to

Choose Destination
Crit Care Med. 2018 Sep;46(9):1421-1429. doi: 10.1097/CCM.0000000000003206.

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.

Author information

1
Unit of Internal Medicine, Department of Medical Surgical and Health Sciences, University of Trieste, Trieste, Italy.
2
Biostatistics Unit, Department of Medical Sciences, University of Trieste, Trieste, Italy.
3
Unit of Emergency Medicine, Department of Translational Medicine, Eastern Piedmont University, Novara, Italy.
4
Unit of Internal Medicine, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy.
5
Unit of Emergency Medicine, Department of Medical Surgery Sciences and Translational medicine, University "Sapienza" of Rome, Rome, Italy.
6
Unit of Internal Medicine, General Hospital of Susa, Susa (TO), Italy.
7
Unit of Nephrology, Department of Nephrology, Dialysis and Transplantation International Renal Research Institute St Bortolo Hospital, Vicenza, Italy.
8
Unit of Emergency Medicine, Department of Medical Sciences, University of Turin, Turin, Italy.

Abstract

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 phospholipase 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 phospholipase 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 Content

Full text links

Icon for Wolters Kluwer
Loading ...
Support Center