Big-data analysis: A clinical pathway on endoscopic retrograde cholangiopancreatography for common bile duct stones

BACKGROUND A clinical pathway(CP)is a standardized approach for disease management.However,big data-based evidence is rarely involved in CP for related common bile duct(CBD)stones,let alone outcome comparisons before and after CP implementation.AIM To investigate the value of CP implementation in patients with CBD stones undergoing endoscopic retrograde cholangiopancreatography(ERCP).METHODS This retrospective study was conducted at Nanjing Drum Tower Hospital in patients with CBD stones undergoing ERCP from January 2007 to December 2017.The data and outcomes were compared by using univariate and multivariable regression/linear models between the patients who received conventional care(non-pathway group,n=467)and CP care(pathway group,n=2196).RESULTS At baseline,the main differences observed between the two groups were the percentage of patients with multiple stones(P<0.001)and incidence of cholangitis complication(P<0.05).The percentage of antibiotic use and complications in the CP group were significantly less than those in the nonpathway group[adjusted odds ratio(OR)=0.72,95%confidence interval(CI):0.55-0.93,P=0.012,adjusted OR=0.44,95%CI:0.33-0.59,P<0.001,respectively].Patients spent lower costs on hospitalization,operation,nursing,medication,and medical consumable materials(P<0.001 for all),and even experienced shorter length of hospital stay(LOHS)(P<0.001)after the CP implementation.No significant differences in clinical outcomes,readmission rate,or secondary surgery rate were presented between the patients in the non-pathway and CP groups.CONCLUSION Implementing a CP for patients with CBD stones is a safe mode to reduce the LOHS,hospital costs,antibiotic use,and complication rate.

Novel roles of lipopolysaccharide and TLR4/NF-κB signaling pathway in inflammatory response to liver injury in Budd-Chiari syndrome

BACKGROUND Budd-Chiari syndrome(BCS)is an uncommon disorder characterized by obstruction of hepatic venous outflow.To date,the exact mechanism underlying hepatic injury derived from the hepatic venous outflow obstruction in BCS remains largely unknown.AIM To assess the role of NF-κB-mediated inflammation in BCS-induced liver injury in humans and rats.METHODS A total of 180 rats were randomly assigned into nine groups,including four BCS model groups(1,3,6 and 12 wk),four sham-operated groups(1,3,6 and 12 wk),and a control group.Lipopolysaccharide(LPS)levels in each group were detected by the Tachypleus Amebocyte Lysate assay.The mRNA and protein levels of TLR4,NF-κB,tumor necrosis factor(TNF)-α,interleukin(IL)-2 and interferon(IFN)-γwere quantified.In addition,60 patients with BCS and 30 healthy controls were enrolled,and their blood samples were analyzed.RESULTS Hepatic and plasma LPS levels were significantly increased in rats.The mRNA and protein expression levels of TLR4,NF-κB and inflammatory cytokines(TNF-α,IL-2 and IFN-γ)in liver tissues were significantly higher in the BCS model groups compared with the other two groups.In addition,the model groups(1,3,6 and 12 wk after BCS induction)showed significant differences in the levels of LPS,TLR4,NF-κB,TNF-α,IL-2 and IFN-γ.Notably,there was a significant correlation between the LPS concentrations and mRNA and protein levels of TLR4,NF-κB and inflammatory cytokines.Importantly,it was revealed that the levels of LPS,TLR4,NF-κB and inflammatory cytokines were significantly greater in chronic BCS patients than healthy controls and acute BCS patients.CONCLUSION LPS level is markedly elevated in BCS,in turn activating the TLR4/NF-κB signaling pathway,leading to induction of inflammatory cytokines(TNF-α,IL-2 and IFN-γ)in response to BCS-induced liver injury.

Congestion avoidance, detection and alleviation in wireless sensor networks

Congestion in wireless sensor networks (WSNs) not only causes severe information loss but also leads to excessive energy consumption. To address this problem, a novel scheme for congestion avoidance, detection and alleviation (CADA) in WSNs is proposed in this paper. By exploiting data characteristics, a small number of representative nodes are chosen from those in the event area as data sources, so that the source traffic can be suppressed proactively to avoid potential congestion. Once congestion occurs inevitably due to traffic mergence, it will be detected in a timely way by the hotspot node based on a combination of buffer occupancy and channel utilization. Congestion is then alleviated reactively by either dynamic traffic multiplexing or source rate regulation in accordance with the specific hotspot scenarios. Extensive simulation results under typical congestion scenarios are presented to illuminate the distinguished performance of the proposed scheme.