EPIdemiology of Surgery-Associated Acute Kidney Injury (EPIS-AKI) : Study protocol for a multicentre, observational trial

More than 300 million surgical procedures are performed each year. Acute kidney injury (AKI) is a common complication after major surgery and is associated with adverse short-term and long-term outcomes. However, there is a large variation in the incidence of reported AKI rates. The establishment of an accurate epidemiology of surgery-associated AKI is important for healthcare policy, quality initiatives, clinical trials, as well as for improving guidelines. The objective of the Epidemiology of Surgery-associated Acute Kidney Injury (EPIS-AKI) trial is to prospectively evaluate the epidemiology of AKI after major surgery using the latest Kidney Disease: Improving Global Outcomes (KDIGO) consensus definition of AKI. EPIS-AKI is an international prospective, observational, multicentre cohort study including 10 000 patients undergoing major surgery who are subsequently admitted to the ICU or a similar high dependency unit. The primary endpoint is the incidence of AKI within 72 hours after surgery according to the KDIGO criteria. Secondary endpoints include use of renal replacement therapy (RRT), mortality during ICU and hospital stay, length of ICU and hospital stay and major adverse kidney events (combined endpoint consisting of persistent renal dysfunction, RRT and mortality) at day 90. Further, we will evaluate preoperative and intraoperative risk factors affecting the incidence of postoperative AKI. In an add-on analysis, we will assess urinary biomarkers for early detection of AKI. EPIS-AKI has been approved by the leading Ethics Committee of the Medical Council North Rhine-Westphalia, of the Westphalian Wilhelms-University Münster and the corresponding Ethics Committee at each participating site. Results will be disseminated widely and published in peer-reviewed journals, presented at conferences and used to design further AKI-related trials. Trial registration number NCT04165369

Effect of a hypertonic balanced ketone solution on plasma, CSF and brain beta-hydroxybutyrate levels and acid-base status

Purpose: Although glucose is the main source of energy for the human brain, ketones play an important role during starvation or injury. The purpose of our study was to investigate the metabolic effects of a novel hypertonic sodium ketone solution in normal animals. Methods: Adult Sprague-Dawley rats (420-570 g) were divided into three groups of five, one control and two study arms. The control group received an intravenous infusion of 3 % NaCl at 5 ml/kg/h. The animals in the two study arms were assigned to receive one of the two formulations of ketone solutions, containing hypertonic saline with 40 and 120 mmol/l beta-hydroxybutyrate, respectively. This was infused for 6 h and then the animal was euthanized and brains removed and frozen. Results: Both blood and cerebrospinal fluid (CSF) levels of beta-hydroxybutyrate (BHB) demonstrated strong evidence of a change over time (p < 0.0001). There was also strong evidence of a difference between groups (p < 0.0001). Multiple comparisons showed all these means were statistically different (p < 0.05). Measurement of BHB levels in brain tissue found strong evidence of a difference between groups (p < 0.0001) with control: 0.15 mmol/l (0.01), BHB 40: 0.19 mmol/l (0.01), and BHB 120: 0.28 mmol/l (0.01). Multiple comparisons showed all these means were statistically different (p < 0.05). There were no differences over time (p = 0.31) or between groups (p = 0.33) or an interaction between groups and time (p = 0.47) for base excess. Conclusion: The IV infusions of hypertonic saline/BHB are feasible and lead to increased plasma, CSF and brain levels of BHB without significant acid/base effects

Modeling and control of switching max-plus-linear systems with random and deterministic switching

Switching max-plus-linear (SMPL) systems are discrete-event systems that can switch between different modes of operation. In each mode the system is described by a max-plus-linear state equation and a max-plus-linear output equation, with different system matrices for each mode. The switching may depend on the inputs and the states, or it may be a stochastic process. In this paper two equivalent descriptions for switching max-plus-linear systems will be discussed. We will also show that a switching max-plus-linear system can be written as a piecewise affine system or as a constrained max-min-plus-scaling system. The last translation can be established under (rather mild) additional assumptions on the boundedness of the states and the inputs. We also develop a stabilizing model predictive controller for SMPL systems with deterministic and/or stochastic switching. In general, the optimization in the model predictive control approach then boils down to a nonlinear nonconvex optimization problem, where the cost criterion is piecewise polynomial on polyhedral sets and the inequality constraints are linear. However, in the case of stochastic switching that depends on the previous mode only, the resulting optimization problem can be solved using linear programming algorithms.Delft Center for Systems and ControlMechanical, Maritime and Materials Engineerin