Comparative effectiveness of aggressive intravenous fluid resuscitation with lactated Ringer’s solution and rectal indomethacin therapy in the prevention of pancreatitis after endoscopic retrograde cholangiopancreatography: a double blind randomised controlled clinical trial

Introduction : There is growing evidence indicating the aggressive intravenous fluid resuscitation (IVFR) can decrease the rate of pancreatitis; however, to the best of our knowledge it has not been well studied in a post-endoscopic retrograde cholangiopancreatography (post-ERCP) setting. Aim : To compare the effects of aggressive IVFR and rectal indomethacin (RI) in preventing pancreatitis after ERCP. Material and methods : This is a double blind randomised controlled clinical trial on 186 patients undergoing ERCP in Ahvaz, Iran. The inclusion criteria were ERCP for standard clinical indications such as choledocholithiasis, bile duct leak, and biliary obstruction. The IVFR group (n = 62) received a bolus of 20 ml/kg of body weight lactated Ringer’s solution (LRS) immediately after ERCP, followed by 3 ml/kg/h maintenance for 8 h. The RI group (n = 62) received 50 mg rectal indomethacin immediately before procedure and 12 h after ERCP. The control group (n = 62) did not receive any treatment. Results : Post-ERCP pancreatitis in IVFR, rectal indomethacin, and control groups occurred in 8 (12.9%), 16 (25.8%), and 20 (32.3%) patients (p = 0.036). Pancreatic pain was reported in 13 (21%), 21 (33.9%), and 27 (43.5%) patients in the IVFR, RI, and control group (p = 0.046). The serum amylase level increased over 24 h after intervention in all three groups. The mean serum amylase level 8 h after intervention in the IVFR patients was lower than the RI and control groups. Conclusions : Intravenous fluid resuscitation with LRS was more effective in preventing post-ERCP pancreatitis in comparison to the rectal indomethacin and control group

A linearized energy hub operation model at the presence of uncertainties: An adaptive robust solution approach

Summary This paper presents a new adaptive robust operation optimization approach for energy hub (EH) to identify the optimal decisions on purchased energy carriers, upstream network interactions, and storing/conversion of the energy resources considering uncertainties. In this regard, a linearized framework for EH operation is first introduced. The proposed model is used to develop an EH including electrical energy, natural gas, and direct heat as inputs and electricity and heat demands as outputs. The electrical input energy is provided considering both purchased energy from upstream market and a photovoltaic (PV) generation, operated by the EH operator (EHO). The proposed approach characterizes the uncertain nature of loads, energy prices, and PV generations through polyhedral uncertainty sets, while the robustness of the proposed model can be controlled using the budget of uncertainty. The proposed adaptive robust model is formulated as a min‐max‐min optimization problem, which cannot be solved directly through an off‐the‐shelf optimization package. Thus, a new method, consisting decomposition + primal cutting plane + duality theory + exact linearization + post‐optimization analysis, is introduced to determine the EH optimal solution. The performance of the proposed approach is evaluated through a comprehensive case study