47 research outputs found
The Impact of Goal-Directed Fluid Therapy in Prolonged Major Abdominal Surgery on Extravascular Lung Water and Oxygenation: A Randomized Controlled Trial
BACKGROUND: A growing interest had been paid to goal-directed fluid therapy (GDT) in abdominal surgery; however, its impact on the respiratory profile was not well investigated.
AIM: We evaluated the impact of GDT on postoperative extravascular lung water and oxygenation after prolonged major abdominal surgery.
METHODS: A randomised, controlled study was conducted in Kasr Alainy hospital from April 2016 till December 2017 including 120 adult patients scheduled for prolonged major abdominal surgery. Patients were randomised into either GDT group (n = 60) who received baseline restricted fluid therapy (2 mL/Kg/hour) which is guided by stroke volume variation, or control group (n = 60) who received standard care. Both study groups were compared according to hemodynamic data, fluid requirements, lung ultrasound score, and PaO2/fraction of inspired oxygen ratio (P/F ratio),
RESULTS: Intraoperatively, GDT group received less volume of fluids and showed higher intraoperative mean arterial pressure compared to the control group. Postoperatively, lung ultrasound score was lower, and P/F ratio was higher in the GDT group compared to the control group. The number of patients who showed a significant postoperative increase in LUS was higher in the control group 44 (73%) patients versus 14 (23%) patients, P < 0.001).
CONCLUSIONS: Using stroke volume variation for guiding fluid therapy in prolonged, major abdominal operations were associated with better hemodynamic profile, less intraoperative fluid administration, lower extravascular lung water and better oxygenation compared to standard care
The road from development to approval: evaluating the body of evidence to confirm biosimilarity
Biosimilars are products that contain a similar version of the active substance of an already authorized
original biologic medicinal product (reference medicinal product). Their development requires special consideration,
as similarity to the reference agent needs to be established through a comprehensive comparability
exercise. Given the complex nature of these agents, minor structural differences may emerge,
but the process of biosimilarity determination is designed to ascertain that the nature and impact of these
differences are not clinically significant. Determination of biosimilarity should follow quality-by-design principles,
which provide a deep understanding of the product development process, guided by pre-defined
objectives, process control and risk management. Compared with novel biologic development, biosimilar
development places greater emphasis on establishing preclinical quality characteristics. Determination of
comparability of quality characteristics includes assessment of physicochemical properties, biological
activity, immunochemical properties, purity, impurity and quantity, with appropriate in vivo pharmacology
studies being conducted thereafter. Head-to-head comparisons are then conducted to determine pharmacokinetic
and pharmacodynamic characteristics, and efficacy, safety and tolerability in phase I and
phase III clinical studies. Post-approval risk management requirements include implementation of pharmacovigilance
systems and risk management through, for example, the conduct of pharmacoepidemiological
studies. There are several biosimilars used in the field of rheumatology that are available in the
European Union, or in development, that offer the potential to increase affordability/accessibility of biological
treatment. The role of these agents in rheumatology will be determined by the confidence placed in
them by rheumatologists. These prescribers should expect high-quality data evaluated by an extensive
assessment process.status: publishe
Heuristic algorithms for two-machine job shop problem under availability constraints on one machine: makespan minimization
International audienceWe discuss the two-machine job shop scheduling problem with availability constraints on one machine for maximum completion time (makespan) minimization. We consider the problem when unavailability periods are planned in advance and operations are non-preemptive. Firstly, some propositions considering Jackson’s rule under availability constraints are introduced. Then, we provide polynomial-time algorithm based on Jackson’s rule and an iterated local search tabu based algorithm exploiting the optimality of Jackson’s rule between each two consecutive availability periods to solve the problem. Finally, we present some experimental results
MIND: An approach to optimize communication time via middleware tuning
International audienc
Two-machine job shop problem under availability constraints on one machine: Makespan minimization
International audienceThis paper considers a two-machine job shop scheduling problem with availability constraints on one machine in order to minimize makespan. We consider the problem when unavailability periods are known in advance and operations are non-preemptive. First, two mixed integer linear programming models MILP1, MILP2 are presented. Secondly, we introduce some properties concerning the optimality of Jackson’s algorithm under availability constraints. Consequently, new lower bounds are provided and an upper bound is obtained using heuristics based on Jackson’s rule. Then, a branch and bound algorithm (B&B) incorporating these bounds is proposed to solve the problem. The performances of the proposed approaches are evaluated by comparing their solutions through well known benchmarks. Computational results prove the efficiency of the proposed B&B
Complexity results of a chain chain reentrante shop with an exact time lag
International audienc
Minimising the makespan in the two-machine job shop problem under availability constraints
International audienceClassical scheduling problem assumes that machines are available during the scheduling horizon. This assumption may be justified in some situations but it does not apply if maintenance requirements, machine breakdowns or other availability constraints have to be considered. In this paper, we treat a two-machine job shop scheduling problem with one availability constraint on each machine to minimise the maximum completion time (makespan). The unavailability periods are known in advance and the processing of an operation cannot be interrupted by an unavailability period (non-preemptive case). We present in our approach properties dealing with permutation dominance and the optimality of Jackson's rule under availability constraints. In order to evaluate the effectiveness of the proposed approach, we develop two mixed integer linear programming models and two schemes for a branch and bound method to solve the tackled problem. Computational results validate the proposed approach and prove the efficiency of the developed methods
Two-machine job shop problem for makespan minimization under availability constraint
International audienceWe treat a two-machine job shop scheduling problem with availability constraint on one machine to minimize the makespan. We consider the deterministic case where the unavailability period, corresponding to preventive maintenance tasks, is known in advance and fixed. We assume that jobs are non-preemptive. First, two mixed-integer programming (MIP) models are first presented. Some propositions concerning the optimality of Jackson’s algorithm when availability constraint exists is provided. Then a branch and bound (B&B) method is developed to solve the problem. The obtained results prove the efficiency of the proposed B&B