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The Conductivity-based Peritoneal Equilibration Test - A mathematical modeling assessment

Bergling, Karin LU (2020) In Master's Theses in Mathematical Sciences FMNM01 20182
Mathematics (Faculty of Engineering)
Abstract
Sufficient solute and water removal are crucial for adequate peritoneal dialy-
sis (PD) treatment. However, present clinical tests for peritoneal membrane trans-
port characteristics are cumbersome and time consuming. Here, a mathematical
model consisting of linear differential equations aiming to describe the complex
process of solute and water transport accross the peritoneal membrane, in order
to evaluate a novel membrane evaluation method called the Conductivity-based
Peritoneal Equilibration Test (CondPET). By non-linear regression analysis, wa-
ter and solute membrane permeability in terms of the ultrafiltration coefficient
LpS (mL/min/mmHg) and diffusion capacity of glucose PSg (mL/min) was dif-
ferentiated. Parameter... (More)
Sufficient solute and water removal are crucial for adequate peritoneal dialy-
sis (PD) treatment. However, present clinical tests for peritoneal membrane trans-
port characteristics are cumbersome and time consuming. Here, a mathematical
model consisting of linear differential equations aiming to describe the complex
process of solute and water transport accross the peritoneal membrane, in order
to evaluate a novel membrane evaluation method called the Conductivity-based
Peritoneal Equilibration Test (CondPET). By non-linear regression analysis, wa-
ter and solute membrane permeability in terms of the ultrafiltration coefficient
LpS (mL/min/mmHg) and diffusion capacity of glucose PSg (mL/min) was dif-
ferentiated. Parameter estimations was conducted on the basis of dialysate con-
ductivity simulations using an extended Three-pore model in 19 fictive patients
during a single dwell of PD. The accuracy of the parameter estimation in com-
parison to the true parameter values were determined by linear regression and
Bland-Altman analysis. Using 3 dialysate samples drawn after 30, 40 and 90 min,
with addition of a random measurement error, LpS was estimated with a mean er-
ror of 7 · 10−4 mL/min/mmHg (95% CI -0.01 - 0.01) and PSg with a mean error of
0.1 mL/min (95% CI -1.37 - 1.58). The CondPET parameter estimation accuracy is
hard to compare to existing methods as it includes quantification of ultrafiltration capacity. However, the CondPET results were promising. The model was successfully set up and despite in need of further refinements due to many assumptions considered versatile. (Less)
Please use this url to cite or link to this publication:
author
Bergling, Karin LU
supervisor
organization
course
FMNM01 20182
year
type
H2 - Master's Degree (Two Years)
subject
keywords
Peritoneal dialysis, membrane filtration, mathematical modeling
publication/series
Master's Theses in Mathematical Sciences
report number
LUTFNA-3050-2020
ISSN
1404-6342
other publication id
2020:E79
language
English
id
9030485
date added to LUP
2021-03-01 16:08:26
date last changed
2021-03-01 16:08:26
@misc{9030485,
  abstract     = {{Sufficient solute and water removal are crucial for adequate peritoneal dialy-
sis (PD) treatment. However, present clinical tests for peritoneal membrane trans-
port characteristics are cumbersome and time consuming. Here, a mathematical
model consisting of linear differential equations aiming to describe the complex
process of solute and water transport accross the peritoneal membrane, in order
to evaluate a novel membrane evaluation method called the Conductivity-based
Peritoneal Equilibration Test (CondPET). By non-linear regression analysis, wa-
ter and solute membrane permeability in terms of the ultrafiltration coefficient
LpS (mL/min/mmHg) and diffusion capacity of glucose PSg (mL/min) was dif-
ferentiated. Parameter estimations was conducted on the basis of dialysate con-
ductivity simulations using an extended Three-pore model in 19 fictive patients
during a single dwell of PD. The accuracy of the parameter estimation in com-
parison to the true parameter values were determined by linear regression and
Bland-Altman analysis. Using 3 dialysate samples drawn after 30, 40 and 90 min,
with addition of a random measurement error, LpS was estimated with a mean er-
ror of 7 · 10−4 mL/min/mmHg (95% CI -0.01 - 0.01) and PSg with a mean error of
0.1 mL/min (95% CI -1.37 - 1.58). The CondPET parameter estimation accuracy is
hard to compare to existing methods as it includes quantification of ultrafiltration capacity. However, the CondPET results were promising. The model was successfully set up and despite in need of further refinements due to many assumptions considered versatile.}},
  author       = {{Bergling, Karin}},
  issn         = {{1404-6342}},
  language     = {{eng}},
  note         = {{Student Paper}},
  series       = {{Master's Theses in Mathematical Sciences}},
  title        = {{The Conductivity-based Peritoneal Equilibration Test - A mathematical modeling assessment}},
  year         = {{2020}},
}