Computer simulations of peritoneal fluid transport in CAPD.
To model the changes in intraperitoneal dialysate volume (IPV) occurring over dwell time under various conditions in continuous ambulatory peritoneal dialysis (CAPD), we have, using a personal computer (PC), numerically integrated the phenomenological equations that describe the net ultrafiltration (UF) flow existing across the peritoneal membrane in every moment of a dwell. Computer modelling was performed according to a three-pore model of membrane selectivity as based on current concepts in capillary physiology. This model comprises small "paracellular" pores (radius approximately 47 A) and "large" pores (radius approximately 250 A), together accounting for approximately 98% of the total UF-coefficient (LpS), and also "transcellular" pores (pore radius approximately 4 to 5 A) accounting for 1.5% of LpS. Simulated curves made a good fit to IPV versus time data obtained experimentally in adult patients, using either 1.36 or 3.86% glucose dialysis solutions, under control conditions; when the peritoneal UF-coefficient was set to 0.082 ml/min/mm Hg, the glucose reflection coefficient was 0.043 and the peritoneal lymph flow was set to 0.3 ml/min. Also, theoretical predictions regarding the IPV versus time curves agreed well with the computer simulated results for perturbed values of effective peritoneal surface area, LpS, glucose permeability-surface area product (PS or "MTAC"), intraperitoneal dialysate volume and dialysate glucose concentration. Thus, increasing the peritoneal surface area caused the IPV versus time curves to peak earlier than during control, while the maximal volume ultrafiltered was not markedly affected. However, increasing the glucose PS caused both a reduction in the IPV versus time curve "peak time" and in the "peak height" of the curves. The latter pattern was also seen when the dialysate volume was reduced. It is suggested that computer modelling based on a three-pore model of membrane selectivity may be a useful tool for describing the IPV versus time relationships under various conditions in CAPD.
Rippe
B
B
Department of Nephrology, University Hospital of Lund, Sweden.
Stelin
G
G
Haraldsson
B
B
D001202:Ascitic Fluid / Q000503:physiopathology*; D001693:Biological Transport, Active; D003198:Computer Simulation; D015314:Dialysis Solutions; D005947:Glucose / Q000378:metabolism; D006801:Humans; D008196:Lymph / Q000502:physiology; D008954:Models, Biological; D010531:Peritoneal Dialysis, Continuous Ambulatory; D012964:Sodium / Q000378:metabolism
D015314:Dialysis Solutions; D012964:Sodium; D005947:Glucose