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An Agent-Based Modeling Template for a Cohort of Veterans with Diabetic Retinopathy

BACKGROUND: Agent-based models are valuable for examining systems where large numbers of discrete individuals interact with each other, or with some environment. Diabetic Veterans seeking eye care at a Veterans Administration hospital represent one such cohort. OBJECTIVE: The objective of this study...

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Autores principales: Day, Theodore Eugene, Ravi, Nathan, Xian, Hong, Brugh, Ann
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3689690/
https://www.ncbi.nlm.nih.gov/pubmed/23805280
http://dx.doi.org/10.1371/journal.pone.0066812
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author Day, Theodore Eugene
Ravi, Nathan
Xian, Hong
Brugh, Ann
author_facet Day, Theodore Eugene
Ravi, Nathan
Xian, Hong
Brugh, Ann
author_sort Day, Theodore Eugene
collection PubMed
description BACKGROUND: Agent-based models are valuable for examining systems where large numbers of discrete individuals interact with each other, or with some environment. Diabetic Veterans seeking eye care at a Veterans Administration hospital represent one such cohort. OBJECTIVE: The objective of this study was to develop an agent-based template to be used as a model for a patient with diabetic retinopathy (DR). This template may be replicated arbitrarily many times in order to generate a large cohort which is representative of a real-world population, upon which in-silico experimentation may be conducted. METHODS: Agent-based template development was performed in java-based computer simulation suite AnyLogic Professional 6.6. The model was informed by medical data abstracted from 535 patient records representing a retrospective cohort of current patients of the VA St. Louis Healthcare System Eye clinic. Logistic regression was performed to determine the predictors associated with advancing stages of DR. Predicted probabilities obtained from logistic regression were used to generate the stage of DR in the simulated cohort. RESULTS: The simulated cohort of DR patients exhibited no significant deviation from the test population of real-world patients in proportion of stage of DR, duration of diabetes mellitus (DM), or the other abstracted predictors. Simulated patients after 10 years were significantly more likely to exhibit proliferative DR (P<0.001). CONCLUSIONS: Agent-based modeling is an emerging platform, capable of simulating large cohorts of individuals based on manageable data abstraction efforts. The modeling method described may be useful in simulating many different conditions where course of disease is described in categorical stages.
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spelling pubmed-36896902013-06-26 An Agent-Based Modeling Template for a Cohort of Veterans with Diabetic Retinopathy Day, Theodore Eugene Ravi, Nathan Xian, Hong Brugh, Ann PLoS One Research Article BACKGROUND: Agent-based models are valuable for examining systems where large numbers of discrete individuals interact with each other, or with some environment. Diabetic Veterans seeking eye care at a Veterans Administration hospital represent one such cohort. OBJECTIVE: The objective of this study was to develop an agent-based template to be used as a model for a patient with diabetic retinopathy (DR). This template may be replicated arbitrarily many times in order to generate a large cohort which is representative of a real-world population, upon which in-silico experimentation may be conducted. METHODS: Agent-based template development was performed in java-based computer simulation suite AnyLogic Professional 6.6. The model was informed by medical data abstracted from 535 patient records representing a retrospective cohort of current patients of the VA St. Louis Healthcare System Eye clinic. Logistic regression was performed to determine the predictors associated with advancing stages of DR. Predicted probabilities obtained from logistic regression were used to generate the stage of DR in the simulated cohort. RESULTS: The simulated cohort of DR patients exhibited no significant deviation from the test population of real-world patients in proportion of stage of DR, duration of diabetes mellitus (DM), or the other abstracted predictors. Simulated patients after 10 years were significantly more likely to exhibit proliferative DR (P<0.001). CONCLUSIONS: Agent-based modeling is an emerging platform, capable of simulating large cohorts of individuals based on manageable data abstraction efforts. The modeling method described may be useful in simulating many different conditions where course of disease is described in categorical stages. Public Library of Science 2013-06-21 /pmc/articles/PMC3689690/ /pubmed/23805280 http://dx.doi.org/10.1371/journal.pone.0066812 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration, which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.
spellingShingle Research Article
Day, Theodore Eugene
Ravi, Nathan
Xian, Hong
Brugh, Ann
An Agent-Based Modeling Template for a Cohort of Veterans with Diabetic Retinopathy
title An Agent-Based Modeling Template for a Cohort of Veterans with Diabetic Retinopathy
title_full An Agent-Based Modeling Template for a Cohort of Veterans with Diabetic Retinopathy
title_fullStr An Agent-Based Modeling Template for a Cohort of Veterans with Diabetic Retinopathy
title_full_unstemmed An Agent-Based Modeling Template for a Cohort of Veterans with Diabetic Retinopathy
title_short An Agent-Based Modeling Template for a Cohort of Veterans with Diabetic Retinopathy
title_sort agent-based modeling template for a cohort of veterans with diabetic retinopathy
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3689690/
https://www.ncbi.nlm.nih.gov/pubmed/23805280
http://dx.doi.org/10.1371/journal.pone.0066812
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