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Crit Care. 2012 Oct 22;16(5):R204. doi: 10.1186/cc11816.

Whole blood impedance aggregometry as a biomarker for the diagnosis and prognosis of severe sepsis.

Abstract

INTRODUCTION:

Sepsis leads to an activation of the immune system and hemostatis. However, studies on platelet aggregation in severe sepsis using impedance aggregometry have not been performed and the diagnostic and prognostic capabilities are unknown. In the present study we hypothesized that impedance aggregometry findings might serve as a biomarker for the diagnosis and prognosis of severe sepsis.

METHODS:

Eighty patients with severe sepsis and 50 postoperative patients were included in the prospective observational study. Platelet function was determined at the first day of severe sepsis and surgery, respectively, using impedance aggregometry (Multiplate®). Moreover, platelet count, procalcitonin, interleukin 6, C-reactive protein and 30-day mortality were determined.

RESULTS:

Compared to postoperative patients, platelet aggregation was significantly reduced in patients with severe sepsis (collagen-test: 70.8 (44.4, 83.2) arbitrary units (A.U.) vs. 26.8 (12.7, 45.8) A.U.; P <0.001; median and quartiles). Furthermore, marked differences in platelet function were observed in survivors and non-survivors of severe sepsis (collagen-test: 33.4 (10.9, 48.8) A.U. vs. 12.4 (6.5, 25.0) A.U.; P = 0.001). Kaplan-Meier analysis demonstrated that higher platelet function was associated with a mortality of 10%, while mortality was 40% when platelet function was low (collagen-test; P = 0.002). The odds ratio was 6.0. In both univariate and multivariate analyses (including procalcitonin, IL6, C-reactive protein and platelet count) impedance aggregometry using collagen as the activator proved to be the best and an independent predictor for the diagnosis and prognosis of severe sepsis in critical illness.

CONCLUSIONS:

In severe sepsis, impedance aggregometry allows better prediction of diagnosis and survival than conventional biomarkers and platelet count.

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