Objective To approach the effect of ulinastatin (UTI) on protection of vascular endothelial cells in rats with sepsis and its mechanism.Methods Fifty-two Sprague-Dawley (SD) male rats were randomly divided into a normal saline pretreatment group (control group) and a UTI pretreatment group (UTI group), each groupn = 26. The rats in two groups were given lipopolysaccharide (LPS, 10 mg/kg) intra-peritoneal injection for the establishment of rat septic models. In UTI group, 18 hours before LPS injection, intraperitoneal injection of UTI 100 kU/kg dissolved in 5 mL normal saline was given, while in the control group, 3 hours before LPS injection, intraperitoneal injection of 5 mL normal saline was given to the rats for pretreatment. Respectively, at 0.5, 2, 4, 12, 24, 72 hours after model establishment, tail venous blood and myocardial tissue were taken. The levels of tumor necrosis factor-α (TNF-α), interleukins (IL-6, IL-10), vascular cell adhesion molecule (VCAM) and intercellular adhesion molecule-1 (ICAM-1) were detected by enzyme-linked immunosorbent assay (ELISA); the correlation between TNF-α and ICAM-1 was analyzed; the expression of ICAM-1 in myocardial cell was determined by immunohistochemistry.Results After model establishment, the levels of TNF-α, IL-6, IL-10, ICAM and VCAM in two groups were gradually increased, reaching the peaks at 24, 12, 12, 72, 72 hours, respectively. Compared with control group, the levels of TNF-α, IL-6, ICAM-1, VCAM of UTI group were significantly lower at various time points [24 hours TNF-α (ng/L): 119.8±28.9 vs. 190.2±30.4, 12 hours IL-6 (ng/L): 327.8±26.9 vs. 948.7±63.8, 72 hours VCAM (ng/L): 36.3±3.2 vs. 68.8±2.4, 72 hours ICAM-1 (ng/L): 115.6±11.6 vs. 129.4±8.2,P < 0.05 orP < 0.01], IL-10 was significantly increased [12 hours (ng/L): 80.7±1.9 vs. 42.3±4.9,P < 0.01]. TNF-αwas positively correlated to ICAM significantly (UTI group:r = 0.907,P = 0.050; control group:r = 0.961, P = 0.010). Immunohistochemistry showed that after modeling for 0.5 hour, basically no positive expression of ICAM-1 in myocardial cells was found in the two groups; in the control group, at 12 hours the positive expression of ICAM-1 was increased, and in UTI group, a little expression of ICAM-1 was seen; at 72 hours, the expression of ICAM-1 was significantly increased in both groups.Conclusion UTI can protect the function of endothelial cells in rats with sepsis by regulating the expressions of proinflammatory cytokine, anti-inflammatory cytokine, adhesion molecules, and improving the microvascular permeability.

Objective To investigate whether early goal-directed therapy ( EGDT ) could lower the mortality rate in patients with severe sepsis and septic shock. Methods Articles with items sepsis, severe sepsis, septic shock, EGDT were retrieved from MEDLINE, EMBASE, Cochrane, Wanfang Data and CNKI. Inclusion criteria included randomized controlled trial, subjects concerning patients with severe sepsis or septic shock, endpoints with short-term mortality [ in-hospital, intensive care unit ( ICU ) or 28-day ] and long-term mortality ( 60-day or 90-day ). Related risk ( RR ) and 95% confidence interval ( 95%CI ) were used as indices to judge the difference in mortality rate between EGDT group and standard treatment group. RevMan 5.2 software was used for Meta analysis. Results There were 8 studies meeting inclusive criteria with a total of 4 853 patients. For patients with severe sepsis and septic shock, compared with the group with routine treatment, EGDT showed a decrease in the short-term mortality ( RR = 0.74, 95%CI=0.66-0.82, P<0.000 01 ), but did not decrease the long-term mortality ( RR=0.99, 95%CI=0.92-1.06, P=0.81 ). Conclusion EGDT strategy may decrease the short-term mortality in patients with severe sepsis and septic shock, but it showed no influence on the long-term mortality.

0.05) between two groups.After EGDT,the level of cTnI in EGDT group was obviously dowered on the 7th day (0.16?0.22?g/L) and 14th day (0.09?0.13?g/L) compared with those in control group (0.39?0.43,0.29?0.29?g/L,P

Objective To investigate the clinical values of central venous pressure (CVP) versus stroke volume variation (SVV) in patients with severe sepsis after early goal-directed therapy (EGDT).Methods Totally 30 mechanically ventilated patients with severe sepsis who underwent goal-achieved EGDT were enrolled and randomly divided into CVP group (study group) and SVV group (control group) according to the data detected by pulse contour continuous cardiac output (PiCCO) analysis device.The differences in 28-day survival,3-day APACHE Ⅱ score,time of ICU stay,duration of mechanical ventilation,number that need CRRT,entral venous pressure (CVP),heart end-diastolic volume index (GEDVI),intrathoracic blood volume index (ITBVI),extravascular lung water index (EVLWI),cardiac index (CI),central venous oxygen saturation (ScvO2),lactate clearance rate and APACHE Ⅱ score were compared between the 2 groups.Results The death rate had no difference between the 2 groups(x2=0.240,P=0.624).Among survival patients in the CVP group,the time of ICU stay and duration of mechanical ventilation were shorter in study group than in control group(t=2.166,P=0.041;t=2.104,P=0.046),APACHE Ⅱ score at 3th day was decreased(t=2.20,P =0.038).The values of ITBVI,GEDVI,CI,lactate clearance rate were higher in study group than in control group (t=2.759,2.146,2.199,2.654,3.362,P=0.011,0.043,0.038,0.014,0.003).EVLWI and APACHE Ⅱ score were not different (P＞0.05) between the two groups.Conclusions SVV as a recovery target for fluid resuscitation can reach a better recovery results and improvement of prognosis than CVP goal-achieved EGDT.

Objective To investigate the prognostic value of stroke volume variation (SVV) in patients with severe sepsis after early goal-directed therapy (EGDT). Method Thirty-eight mechanically ventilated patients with severe sepsis underwent EGTD were divided into high SVV (≥10%) group and low SW (< 10%) group according to the data obtained from pulse contour continuous cardiac output (PiCCO) analysis device. The differ-enees in the rate of 28-day survival, length of ICU stay, duration of meehanical ventilation and eomplieation of in-fection between two groups of patients were compared. The rate of 28-day survival of patients was analyzed by using Kaplain-Meier survival analysis, and the relationship between SVV and mortality within 28 days was analyzed by using logistic regression model. Results In comparison with low SVV group, the rate of 28-day survival of high SVV group was signifieantly increased (87.5 % vs. 57.1%, P = 0.032), the length of ICU stay was significantly shortened (27.1±9.2) vs. (41.6±10.0) (P = 0. 004) and duration of mechanical ventilation was significantly more brief (20.4±7.3) vs. (28.5±8.3) (P = 0.038). The rate of cumulative survival of patients in high SVV group was higher than that in low SVV group. In addition, logistie analysis showed SW < 10% increased the risk of 28-day mortality (OR = 3.97; 95% CI 1.63 - 9.21, P = 0. 014). Conclusions The SVV can be served as a prognostic indicator in patients with severe sepsis after EGDT.

Objective: To investigate the endothelial protective effects of simvastatin on the coagulation system in septic rats. Methods: A total of 54 SD male rats were divided into 3 groups. Six healthy rats were intraperitoneally injected with normal salineas control group. Twenty-four rats in septic group were intraperitoneally injected with normal saline followed by lipopolysaccharide 2.5 mg. Study group had 24 rats intraperitoneally injected with simvastatin followed by lipopolysaccharide. Plasma von Willebrand factor (vWF), thrombomodulin (TM), platelet activating factor (PAF) and antithrombin-Ⅲ (AT-Ⅲ) were tested at 1 h, 3 h, 6 h and 12 h after treatment. Scanning electron microscopy and transmission electron microscopy were used to observe the morphology and apoptosis of rat aorta endothelial cells. Results: Compared with healthy control group, vWF [(68.3±4.8) ng/ml, (59.2±5.1) ng/ml, (74.2±20.1) ng/ml, (53.5±4.0)ng/ml, respectively], TM [(1.4±0.3) ng/ml, (1.6±0.4) ng/ml, (2.8±0.9) ng/ml, (1.4±0.5) ng/ml, respectively], PAF [(29.1±6.5) pg/ml, (28.6±1.5) pg/ml, (28.7±2.7) pg/ml, (18.2±4.1) pg/ml, respectively] and AT-Ⅲ [(262.2±38.1)μg/ml, (233.0±70.4) μg/ml, (218.7±54.7) μg/ml, (162.2±37.2) μg/ml, respectively] were significantly increased in the sepsis group at 1 h, 3 h, 6 h and 12 h (P<0.05). Compared with the sepsis group, the plasma levels of PAF in simvastatin intervention group at 1 h [(15.6±2.5) pg/ml, 3 h(10.4±5.3) pg/ml, 6 h (9.3±1.4) pg/ml, 12 h(11.0±2.7) pg/ml] were significantly decreased, so were the TM level at 6 h (1.6±0.9) ng/ml, and the AT-Ⅲ levels at 1 h[(190.3±29.2) μg/ml],6 h [(104.4±33.6) μg/ml] and 12 h [(73.6±39.0) μg/ml, P<0.05]. Conclusion In the condition of sepsis, toxins and over-activated inflammatory factors damage the vascular endothelium. A large amount of circulating vWF, TM, PAF, and AT-Ⅲ cause early hypercoagulability. Simvastatin significantly reduces plasma amount of these procoagulants, suggesting it smodification of coagulopathy and vascular protective effectsin a septic rat model.

Aiming at the problem that the small samples of critical disease in clinic may lead to prognostic models with poor performance of overfitting, large prediction error and instability, the long short-term memory transferring algorithm (transLSTM) was proposed. Based on the idea of transfer learning, the algorithm leverages the correlation between diseases to transfer information of different disease prognostic models, constructs the effictive model of target disease of small samples with the aid of large data of related diseases, hence improves the prediction performance and reduces the requirement for target training sample quantity. The transLSTM algorithm firstly uses the related disease samples to pretrain partial model parameters, and then further adjusts the whole network with the target training samples. The testing results on MIMIC-Ⅲ database showed that compared with traditional LSTM classification algorithm, the transLSTM algorithm had 0.02-0.07 higher AUROC and 0.05-0.14 larger AUPRC, while its number of training iterations was only 39%-64% of the traditional algorithm. The results of application on sepsis revealed that the transLSTM model of only 100 training samples had comparable mortality prediction performance to the traditional model of 250 training samples. In small sample situations, the transLSTM algorithm has significant advantages with higher prediciton accuracy and faster training speed. It realizes the application of transfer learning in the prognostic model of critical disease with small samples.