A mathematical model to investigate the effects of intravenous fluid administration and fluid loss

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

The optimal fluid administration protocol for critically ill perioperative patients is hard to estimate due to the lack of tools to directly measure the patient fluid status. This results in the suboptimal clinical outcome of interventions. Previously developed predictive mathematical models focus on describing the fluid exchange over time but they lack clinical applicability, since they do not allow prediction of clinically measurable indices. The aim of this study is to make a first step towards a model predictive clinical decision support system for fluid administration, by extending the current fluid exchange models with a regulated cardiovascular circulation, to allow prediction of these indices. The parameters of the model were tuned to correctly reproduce experimentally measured changes in arterial pressure and heart rate, observed during infusion of normal saline in healthy volunteers. With the resulting tuned model, a different experiment including blood loss and infusion could be reproduced as well. These results show the potential of using this model as a basis for a decision support tool in a clinical setting.

LanguageEnglish
Pages4-11
Number of pages8
JournalJournal of Biomechanics
Volume88
DOIs
StatePublished - May 2019

Fingerprint

Intravenous Administration
Theoretical Models
Clinical Decision Support Systems
Mathematical models
Fluids
Critical Illness
Healthy Volunteers
Arterial Pressure
Heart Rate
Decision support systems
Blood
Experiments

Keywords

  • Fluid administration
  • Mathematical models
  • Model assisted decision support
  • Transcapillary fluid exchange

Cite this

@article{ff8387da947042c3bfe2c4569f5b3fb2,
title = "A mathematical model to investigate the effects of intravenous fluid administration and fluid loss",
abstract = "The optimal fluid administration protocol for critically ill perioperative patients is hard to estimate due to the lack of tools to directly measure the patient fluid status. This results in the suboptimal clinical outcome of interventions. Previously developed predictive mathematical models focus on describing the fluid exchange over time but they lack clinical applicability, since they do not allow prediction of clinically measurable indices. The aim of this study is to make a first step towards a model predictive clinical decision support system for fluid administration, by extending the current fluid exchange models with a regulated cardiovascular circulation, to allow prediction of these indices. The parameters of the model were tuned to correctly reproduce experimentally measured changes in arterial pressure and heart rate, observed during infusion of normal saline in healthy volunteers. With the resulting tuned model, a different experiment including blood loss and infusion could be reproduced as well. These results show the potential of using this model as a basis for a decision support tool in a clinical setting.",
keywords = "Fluid administration, Mathematical models, Model assisted decision support, Transcapillary fluid exchange",
author = "Rosalina, {Tila{\"i} T.} and Bouwman, {R. Arthur} and {van Sambeek}, {Marc R.H.M.} and {van de Vosse}, {Frans N.} and Bovendeerd, {Peter H.M.}",
year = "2019",
month = "5",
doi = "10.1016/j.jbiomech.2019.03.002",
language = "English",
volume = "88",
pages = "4--11",
journal = "Journal of Biomechanics",
issn = "0021-9290",
publisher = "Elsevier",

}

TY - JOUR

T1 - A mathematical model to investigate the effects of intravenous fluid administration and fluid loss

AU - Rosalina,Tilaï T.

AU - Bouwman,R. Arthur

AU - van Sambeek,Marc R.H.M.

AU - van de Vosse,Frans N.

AU - Bovendeerd,Peter H.M.

PY - 2019/5

Y1 - 2019/5

N2 - The optimal fluid administration protocol for critically ill perioperative patients is hard to estimate due to the lack of tools to directly measure the patient fluid status. This results in the suboptimal clinical outcome of interventions. Previously developed predictive mathematical models focus on describing the fluid exchange over time but they lack clinical applicability, since they do not allow prediction of clinically measurable indices. The aim of this study is to make a first step towards a model predictive clinical decision support system for fluid administration, by extending the current fluid exchange models with a regulated cardiovascular circulation, to allow prediction of these indices. The parameters of the model were tuned to correctly reproduce experimentally measured changes in arterial pressure and heart rate, observed during infusion of normal saline in healthy volunteers. With the resulting tuned model, a different experiment including blood loss and infusion could be reproduced as well. These results show the potential of using this model as a basis for a decision support tool in a clinical setting.

AB - The optimal fluid administration protocol for critically ill perioperative patients is hard to estimate due to the lack of tools to directly measure the patient fluid status. This results in the suboptimal clinical outcome of interventions. Previously developed predictive mathematical models focus on describing the fluid exchange over time but they lack clinical applicability, since they do not allow prediction of clinically measurable indices. The aim of this study is to make a first step towards a model predictive clinical decision support system for fluid administration, by extending the current fluid exchange models with a regulated cardiovascular circulation, to allow prediction of these indices. The parameters of the model were tuned to correctly reproduce experimentally measured changes in arterial pressure and heart rate, observed during infusion of normal saline in healthy volunteers. With the resulting tuned model, a different experiment including blood loss and infusion could be reproduced as well. These results show the potential of using this model as a basis for a decision support tool in a clinical setting.

KW - Fluid administration

KW - Mathematical models

KW - Model assisted decision support

KW - Transcapillary fluid exchange

UR - http://www.scopus.com/inward/record.url?scp=85063132270&partnerID=8YFLogxK

U2 - 10.1016/j.jbiomech.2019.03.002

DO - 10.1016/j.jbiomech.2019.03.002

M3 - Article

VL - 88

SP - 4

EP - 11

JO - Journal of Biomechanics

T2 - Journal of Biomechanics

JF - Journal of Biomechanics

SN - 0021-9290

ER -