Vasopressin compared with norepinephrine augments the decline of plasma cytokine levels in septic shock.

RATIONALE: Changes in plasma cytokine levels may predict mortality, and therapies (vasopressin versus norepinephrine) could change plasma cytokine levels in early septic shock. OBJECTIVES: Our hypotheses were that changes in plasma cytokine levels over 24 hours differ between survivors and nonsurvivors, and that there are different effects of vasopressin and norepinephrine on plasma cytokine levels in septic shock. METHODS: We studied 394 patients in a randomized, controlled trial of vasopressin versus norepinephrine in septic shock. We used hierarchical clustering and principal components analysis of the baseline cytokine concentrations to subgroup cytokines; we then compared survivors to nonsurvivors (28 d) and compared vasopressin- versus norepinephrine-induced changes in cytokine levels over 24 hours. MEASUREMENTS AND MAIN RESULTS: A total of 39 plasma cytokines were measured at baseline and at 24 hours. Hierarchical clustering and principal components analysis grouped cytokines similarly. Survivors (versus nonsurvivors) had greater decreases of overall cytokine levels (P < 0.001). Vasopressin decreased overall 24-hour cytokine concentration compared with norepinephrine (P = 0.037). In less severe septic shock, the difference in plasma cytokine reduction over 24 hours between survivors and nonsurvivors was less pronounced than that seen in more severe septic shock. Furthermore, vasopressin decreased interferon-inducible protein 10 and granulocyte colony-stimulating factor more than did norepinephrine in less severe septic shock, whereas vasopressin decreased granulocyte-macrophage colony-stimulating factor in patients who had more severe shock. CONCLUSIONS: Survivors of septic shock had greater decreases of cytokines, chemokines and growth factors in early septic shock. Vasopressin decreased 24-hour plasma cytokine levels more than did norepinephrine. The vasopressin-associated decrease of cytokines differed according to severity of shock. Clinical trial registered with www.controlled-trials.com (ISRCTN94845869).

Cytokines and signaling molecules predict clinical outcomes in sepsis.

INTRODUCTION: Inflammatory response during sepsis is incompletely understood due to small sample sizes and variable timing of measurements following the onset of symptoms. The vasopressin in septic shock trial (VASST) compared the addition of vasopressin to norepinephrine alone in patients with septic shock. During this study plasma was collected and 39 cytokines measured in a 363 patients at both baseline (before treatment) and 24 hours. Clinical features relating to both underlying health and the acute organ dysfunction induced by the severe infection were collected during the first 28 days of admission. HYPOTHESIS: Cluster analysis of cytokines identifies subgroups of patients at differing risk of death and organ failure. METHODS: Circulating cytokines and other signaling molecules were measured using a Luminex multi-bead analyte detection system. Hierarchical clustering was performed on plasma values to create patient subgroups. Enrichment analysis identified clinical outcomes significantly different according to these chemically defined patient subgroups. Logistic regression was performed to assess the importance of cytokines for predicting patient subgroups. RESULTS: Plasma levels at baseline produced three subgroups of patients, while 24 hour levels produced two subgroups. Using baseline cytokine data, one subgroup of 47 patients showed a high level of enrichment for severe septic shock, coagulopathy, renal failure, and risk of death. Using data at 24 hours, a larger subgroup of 81 patients that largely encompassed the 47 baseline subgroup patients had a similar enrichment profile. Measurement of two cytokines, IL2 and CSF2 and their product were sufficient to classify patients into these subgroups that defined clinical risks. CONCLUSIONS: A distinct pattern of cytokine levels measured early in the course of sepsis predicts disease outcome. Subpopulations of patients have differing clinical outcomes that can be predicted accurately from small numbers of cytokines. Design of clinical trials and interventions may benefit from consideration of cytokine levels.