Kota Hoshino

1056: THE EFFICACY OF THE POLIMYXIN B IMMOBILIZED FIBER COLUMN DIRECT HEMOPERFUSION FOR SEPTIC SHOCK

Crit Care Med 2015 • Volume 43 • Number 12 (Suppl.) baseline and after CSE exposure. The NALP3-ubiquitin binding was increased by more than 50% after CSE exposure when densitometrically controlled for input loading. Conclusions: CSE decreases NALP3 protein levels by increasing its degradation, not by decreasing new protein synthesis. The underlying mechanism is most likely increased ubiquitin-mediated proteasomal processing. Our findings provide potential mechanistic insights for smoking-related immunosuppression, and this may uncover unique opportunities to develop therapeutic strategies to modulate cytokine signaling, and subsequently, inflammation associated with sepsis development.

Comparison of accuracy of presepsin and procalcitonin concentrations in diagnosing sepsis in patients with and without acute kidney injury

BACKGROUND Levels of the biomarkers presepsin and procalcitonin are affected by renal function. We evaluated the accuracies of presepsin and procalcitonin levels for diagnosing sepsis in patients with and without acute kidney injury (AKI). METHODS We evaluated patients with presepsin and procalcitonin data, and classified them into AKI and non-AKI groups based on the Kidney Disease Improving Global Outcomes criteria. Each group was then subdivided according to sepsis status for each stage of AKI. Receiver operating characteristic curve analyses were used to investigate the accuracies of biomarker levels for diagnosing sepsis. RESULTS In the non-AKI group, the area under the curves (AUCs) for procalcitonin and presepsin levels were 0.897 and 0.880, respectively (p = .525) and optimal cut-off values were 0.10 ng/ml (sensitivity: 85.1%, specificity: 79.1%) and 240 pg/ml (sensitivity: 80.9%, specificity: 83.2%), respectively. In the stage 3 subgroup, the AUC for procalcitonin (0.946) was significantly higher than that for presepsin (0.768, p < .001). The optimal cut-off values for diagnosing sepsis were 4.07 ng/ml (sensitivity: 87.2%, specificity: 93.5%) for procalcitonin and 500 pg/ml (sensitivity: 89.7%, specificity: 59.7%) for presepsin. CONCLUSIONS In patients with severe AKI, the accuracy of the diagnosis of sepsis with procalcitonin was significantly higher than with presepsin.

1398: PLASMINOGEN ACTIVATOR INHIBITOR-1 IS THE MOST PREDICTIVE MARKER OF MORTALITY IN SEPSIS.

Learning Objectives: Sepsis has poor outcome, and the mortality rate is 30%50% in patients with septic shock. Early diagnosis and treatment of sepsis are important for improving the prognosis. Sepsis is the most common disease associated with coagulopathy. Approximately 20%-40% of all sepsis patients are complicated with disseminated intravascular coagulation (DIC). Therefore, inflammation and coagulation are closely interrelated in sepsis. In 2016, new sepsis definition named SEPSIS-3 was published. We aimed to identify the most predictive marker of 28-day mortality using inflammation and coagulation markers. Methods: This was a single-center retrospective study and included 186 patients with sepsis from January 2013 to September 2015. The definition of sepsis was used according to SEPSIS-3. Inflammatory markers [C-reactive protein (CRP), procalcitonin (PCT), and presepsin (PSEP)] and coagulation markers [platelet count, prothrombin time-international normalized ratio (PT-INR), activated partial thromboplastin time (APTT), antithrombin (AT), D-dimer, thrombin-antithrombin complex (TAT), plamin-2 plasmin inhibitor complex (PIC), protein C (PC), soluble fibrin (SF), and plasminogen activator inhibitor (PAI)-1] were assayed on ED admission. Univariate and multivariate logistic regression analyses were performed to identify independent predictive markers of 28-day mortality. The area under the curve (AUC) and the optimal cut-off value of the most predictive marker were examined. Results:The 28-day mortality rate was 19% (36/186). PSEP, TAT, PC, SF, and PAI-1 were found to be significant predictive markers of 28-day mortality according to univariate analysis. Subsequently, we performed multivariate logistic regression analysis using these five markers as explanatory variables. PAI-1 was found to be the only independent predictive marker of 28-day mortality (P <0.05). AUC of PAI-1 was 0.72, and the optimal cut-off value was 83 ng/ml, with sensitivity and specificity of 75% and 61%, respectively. Conclusions: In conclusion, PAI-1 may be a useful predictive marker of 28-day mortality for sepsis.