BACKGROUND: The Genius single-pass batch system, using a closed dialysate container, is increasingly applied for dialysis treatment. Although fluid separation between fresh and spent dialysate is maintained in the container during standard dialysis, dialysate mixing may occur under certain clinical conditions. An in vitro study showed that differences in dialysate temperature and solute content between fresh and spent dialysate determine the occurrence and moment of dialysate mixing. METHODS: To better understand the maintenance of separation of fresh and spent dialysate in the prevention of mixing, a mathematical model of the 75 l Genius container was developed and the general fluid, mass and heat transfer equations were solved, simulating a dialysis session of 300 min with 1 g/l urea as starting 'blood' urea concentration and 36.2 degrees C starting dialysate temperature. Boundary and initial conditions were chosen according to two different strategies applied in previous in vitro tests, with spontaneous cooling of the reservoir on the one hand and heating of the spent dialysate to maintain an equal temperature as the fresh dialysate on the other. RESULTS: Our simulation data show that dialysate inside the container is cooling down near the container wall in both scenarios and near the central glass tube in the setup with spontaneous cooling. In the setup with heating of spent dialysate, the upper layers are heated near the central tube. Since density stratification is maintained at each time point, solutes will rise towards warmer zones. This is halfway between the container axis and wall for spontaneous cooling and, even to a larger extent, near the central tube for simulations with heated spent dialysate. Hence, the contaminated volume in the case of heating is much larger than theoretically supposed. CONCLUSIONS: These computer simulations unravel temperature and concentration distribution inside the container, offering insight into the complicated mixing phenomenon and indicate that temperature is a major impacting factor.
BACKGROUND: The Genius single-pass batch system, using a closed dialysate container, is increasingly applied for dialysis treatment. Although fluid separation between fresh and spent dialysate is maintained in the container during standard dialysis, dialysate mixing may occur under certain clinical conditions. An in vitro study showed that differences in dialysate temperature and solute content between fresh and spent dialysate determine the occurrence and moment of dialysate mixing. METHODS: To better understand the maintenance of separation of fresh and spent dialysate in the prevention of mixing, a mathematical model of the 75 l Genius container was developed and the general fluid, mass and heat transfer equations were solved, simulating a dialysis session of 300 min with 1 g/l urea as starting 'blood' urea concentration and 36.2 degrees C starting dialysate temperature. Boundary and initial conditions were chosen according to two different strategies applied in previous in vitro tests, with spontaneous cooling of the reservoir on the one hand and heating of the spent dialysate to maintain an equal temperature as the fresh dialysate on the other. RESULTS: Our simulation data show that dialysate inside the container is cooling down near the container wall in both scenarios and near the central glass tube in the setup with spontaneous cooling. In the setup with heating of spent dialysate, the upper layers are heated near the central tube. Since density stratification is maintained at each time point, solutes will rise towards warmer zones. This is halfway between the container axis and wall for spontaneous cooling and, even to a larger extent, near the central tube for simulations with heated spent dialysate. Hence, the contaminated volume in the case of heating is much larger than theoretically supposed. CONCLUSIONS: These computer simulations unravel temperature and concentration distribution inside the container, offering insight into the complicated mixing phenomenon and indicate that temperature is a major impacting factor.
Authors: Verônica Torres da Costa E Silva; Elerson C Costalonga; Ana Paula Leandro Oliveira; James Hung; Renato Antunes Caires; Ludhmila Abrahão Hajjar; Julia T Fukushima; Cilene Muniz Soares; Juliana Silva Bezerra; Luciane Oikawa; Luis Yu; Emmanuel A Burdmann Journal: PLoS One Date: 2016-03-03 Impact factor: 3.240