Bedside visualisation tool for prediction of deviation from intended dosage in multi-infusion therapy.

Background: In multi-infusion therapy, multiple infusion pumps are connected to one single vascular access point. Interaction between pressure changes from different pumps may result in temporary dosing errors, which can be very harmful to the patient. It is known that these dosing errors occur.

Unexpected dosing errors due to air bubbles in infusion lines with and without air filters.

The effect of the presence of an air bubble, inside an infusion line, on the time (Tnew) needed for a new medication to reach the patient after a syringe exchange was studied in this paper. If an air bubble escapes through an air filter, then a sudden drop in pressure occurs, causing a relaxation of the compressible part of the syringe, followed by a gradual restoration of the flow rate in the line. We modeled this phenomenon mathematically and measured it experimentally .

Effect of non-return valves on the time-of-arrival of new medication in a patient after syringe exchange in an infusion set-up.

The presence of a non-return valve in an infusion set-up is expected to affect the time-of-arrival of new medication in a patient after syringe exchange. Using Computational Fluid Dynamics (CFD) we have studied the flow through a typical non-return valve, focusing on two separate effects: (A) the overall delay in the time-of-arrival, and (B) timing effects due to the distortion of the Poiseuille flow profile in the non-return valve. The results show that (A) the additional delay in time-of-arrival of new medication, caused by the non-return valve alone, corresponds to the delay that would be caused by 11.

Contemporary management of patients with atrial fibrillation in the Netherlands and Belgium: a report from the EORP-AF long-term general registry.

Background: Contemporary data regarding the characteristics, treatment and outcomes of patients with atrial fibrillation (AF) are needed. We aimed to assess these data and guideline adherence in the EURObservational Research Programme on Atrial Fibrillation (EORP-AF) long-term general registry.

Methods: We analysed 967 patients from the EORP-AF long-term general registry included in the Netherlands and Belgium from 2013 to 2016.

Industry 4.0 Lean Shopfloor Management Characterization Using EEG Sensors and Deep Learning.

Achieving the shift towards Industry 4.0 is only feasible through the active integration of the shopfloor into the transformation process. Several shopfloor management (SM) systems can aid this conversion.