Corticosteroid resistance in sepsis is influenced by microRNA-124–induced downregulation of glucocorticoid receptor-α*
Carola Ledderose, Patrick Möhnle, Elisabeth Limbeck, Stefanie Schütz, Florian Weis, Jessica Rink, Josef Briegel, Simone Kreth
Critical Care Medicine
Critical Care 2012, 16(Suppl 3):P1 Background: Most clinical trials of sepsis treatment modalities fail at their primary objective of establishing superiority over placebo when added to background standard of care. While there is no definitive explanation for the high failure rate, it might be stated that our attempts to insert a new therapeutic agent into standard of care encounters severe problems with definition of exactly what stage is ongoing, and what are the criteria for progression or
... solution from that time point onwards. Clearly there is need for a means of defining steps in the septic process that would apply to individuals, and to better define the course of sepsis in each patient after they are enrolled in a trial. Methods: For core model development, 30 septic patients were studied for time-related progression in relation to biomarkers, employing a Load Model in a neural net algorithm in MatLab. Causative bacterial infections were linked to primary infection sites. In order to minimize overparameterization, the model was allowed to estimate outputs using the best three input parameters. Bacterial load was tracked from origin using clinical and microbiologic data to provide an estimate at the start of sepsis. The bacterial load as well as clinical and laboratory parameters were model inputs with the output parameter being organ failures and/ or mortality. Results: At onset of sepsis, human bacterial load estimates ranged from between 10 8 and 10 11 CFU, which is consistent with inocula in animal models of sepsis. Sepsis proceeds to organ failures and mortality in a series of steps that are initially linked to bacterial load and inflammatory response, followed by coagulopathy, ischemia, oxygen deprivation in organs and tissues, and culminating in organ failures. The later stages of sepsis are all driven by metabolic parameters, and there seems to be little benefit to blocking inflammation at later stages. Substrate and oxygen deficiencies must be addressed first. Conclusion: Neural net progression models based on biomarkers and physiological markers are able to describe the evolution of sepsis to septic shock, organ failures, and provide some evidence that mortality may be a consequence of the stages of sepsis. Overall, these models appear useful to the task of sorting out organ failure endpoints and mechanisms in individual patients with sepsis progression across sepsis to septic shock. P2 Extracellular matrix turnover, angiogenesis and endothelial function in acute lung injury: relationship to pulmonary dysfunction and outcome Critical Care 2012, 16(Suppl 3):P2 Background: Acute lung injury (ALI) is a syndrome with a diagnostic criteria based on hypoxemia and a classical radiological appearance, with acute respiratory distress syndrome at the severe end of the disease. Facts recommended the occurrence of rupture of the basement membranes and interstitial matrix remodeling during ALI. Matrix metalloproteinases (MMPs) participate in tissue remodeling related with pathological conditions such as ALI. We hypothesized the interrelationships between extracellular matrix (ECM) turnover as MMP-9 and indicator of angiogenesis such as angiopoietin-2 (Ang-2) as well as plasma von Willebrand factor (vWF) and their correlation with arterial partial pressure of oxygen (PaO 2 ), oxygen saturation (SaO 2 ) and mortality in ALI/ARDS. Methods: Eighty-eight mechanically ventilated patients (68 male, mean (SD) age 61 (10) years) were compared with 40 healthy controls (36 male, mean (SD) age 57 (10)). All biomarkers were measured by ELISA. Oxygenation, body temperature, leucocytes, and platelet counts were noted. Results: Plasma levels of all biomarkers were significantly different among ALI/ARDS subjects (P < 0.001) and they inversely related to PaO 2 and SaO 2 and positively related to mortality. Plasma levels of MMP-9 were negatively correlated with PaO 2 and SaO 2 % in ALI/ARDS patients (r = -0.75, P < 0.0001 and r = -0.81, P < 0.0001) respectively. Plasma level of Ang-2 was negatively correlated with PaO 2 and SaO 2 % in ALI/ARDS patients (r = -0.68, P < 0.0001 and r = -0.63, P < 0.0001) respectively. Plasma levels of vWF were negatively correlated with PaO 2 and SaO 2 % in ALI/ARDS patients (r = -0.76, P < 0.0001 and r = -0.69, P < 0.001) respectively. Elevated plasma levels of all indices were interrelated at the first day of admission. Conclusion: The observed diversity in plasma levels of MMP-9, Ang-2 and vWF in ALI/ARDS patients (Table 1) revealed the activity and severity of the disease, shedding more light on the pathogenesis and/or presentation of ARDS.