Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Nonlinear Parameter and State Estimation Approach in End-stage Kidney Disease Patients

View ORCID ProfileRammah M. Abohtyra, View ORCID ProfileTyrone L. Vincent
doi: https://doi.org/10.1101/2022.04.02.486844
Rammah M. Abohtyra
1Department of Engineering Science and Mechanics, The Pennsylvania State University, University Park, State College, 16802, Pennsylvania, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Rammah M. Abohtyra
  • For correspondence: rammah.abohtyra@gmail.com
Tyrone L. Vincent
2Department of Electrical Engineering, Colorado School of Mines, 1500 Illinois St, Golden, 80401, Colorado, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Tyrone L. Vincent
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

Abstract

Background Blood and fluid volume management in End-stage Kidney Disease (ESKD) patients plays an essential role in dialysis therapy to replace kidney function. Reliable knowledge of blood and fluid volumes before and during dialysis could be used to improve treatment outcomes significantly.

Objective This study aims to develop an estimation approach providing predictable information on blood and fluid volumes before and during a regular dialysis routine.

Methods A new approach is developed to estimate blood volume, fluid overload, and vascular refilling parameters from dialysis data. The method utilizes a nonlinear fluid volume model, an optimization technique, and the Unscented Kalman Filter (UKF) incorporated with data. This method does not rely on restricted ultrafiltration (UF) and dilution protocols and uses the Fisher information matrix to quantify error estimation.

Results Accurate estimations for blood volumes (5.9±0.07L and 4.8±0.03L) and interstitial fluid volumes (18.81±0.15L and 12.19±0.03) were calculated from dialysis data consisting of constant and stepwise UF profiles. We demonstrated that by implementing the estimated parameters into the model, a precise prediction of the measured hematocrit (HCT) can be achieved during the treatment.

Conclusion We showed that the result does not depend highly on initial conditions and can be accurately estimated from a short data segment. A new method, applicable to the current dialysis routine, is now available for ESKD patients to be implemented within the dialysis machines.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • Updated version 1-20-2023

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
Back to top
PreviousNext
Posted January 21, 2023.
Download PDF
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Nonlinear Parameter and State Estimation Approach in End-stage Kidney Disease Patients
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Nonlinear Parameter and State Estimation Approach in End-stage Kidney Disease Patients
Rammah M. Abohtyra, Tyrone L. Vincent
bioRxiv 2022.04.02.486844; doi: https://doi.org/10.1101/2022.04.02.486844
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
Nonlinear Parameter and State Estimation Approach in End-stage Kidney Disease Patients
Rammah M. Abohtyra, Tyrone L. Vincent
bioRxiv 2022.04.02.486844; doi: https://doi.org/10.1101/2022.04.02.486844

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Bioengineering
Subject Areas
All Articles
  • Animal Behavior and Cognition (4095)
  • Biochemistry (8787)
  • Bioengineering (6493)
  • Bioinformatics (23393)
  • Biophysics (11766)
  • Cancer Biology (9170)
  • Cell Biology (13292)
  • Clinical Trials (138)
  • Developmental Biology (7423)
  • Ecology (11388)
  • Epidemiology (2066)
  • Evolutionary Biology (15121)
  • Genetics (10414)
  • Genomics (14025)
  • Immunology (9150)
  • Microbiology (22110)
  • Molecular Biology (8793)
  • Neuroscience (47455)
  • Paleontology (350)
  • Pathology (1423)
  • Pharmacology and Toxicology (2485)
  • Physiology (3712)
  • Plant Biology (8068)
  • Scientific Communication and Education (1433)
  • Synthetic Biology (2216)
  • Systems Biology (6021)
  • Zoology (1251)