Estimating ectopic beat probability with simplified statistical models that account for experimental uncertainty.

Ectopic beats (EBs) are cellular arrhythmias that can trigger lethal arrhythmias. Simulations using biophysically-detailed cardiac myocyte models can reveal how model parameters influence the probability of these cellular arrhythmias, however such analyses can pose a huge computational burden. Here,...

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Autores principales: Qingchu Jin, Joseph L Greenstein, Raimond L Winslow
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Lenguaje:EN
Publicado: Public Library of Science (PLoS) 2021
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Acceso en línea:https://doaj.org/article/477112a02f4f479683219e2e669f6343
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spelling oai:doaj.org-article:477112a02f4f479683219e2e669f63432021-12-02T19:57:37ZEstimating ectopic beat probability with simplified statistical models that account for experimental uncertainty.1553-734X1553-735810.1371/journal.pcbi.1009536https://doaj.org/article/477112a02f4f479683219e2e669f63432021-10-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1009536https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Ectopic beats (EBs) are cellular arrhythmias that can trigger lethal arrhythmias. Simulations using biophysically-detailed cardiac myocyte models can reveal how model parameters influence the probability of these cellular arrhythmias, however such analyses can pose a huge computational burden. Here, we develop a simplified approach in which logistic regression models (LRMs) are used to define a mapping between the parameters of complex cell models and the probability of EBs (P(EB)). As an example, in this study, we build an LRM for P(EB) as a function of the initial value of diastolic cytosolic Ca2+ concentration ([Ca2+]iini), the initial state of sarcoplasmic reticulum (SR) Ca2+ load ([Ca2+]SRini), and kinetic parameters of the inward rectifier K+ current (IK1) and ryanodine receptor (RyR). This approach, which we refer to as arrhythmia sensitivity analysis, allows for evaluation of the relationship between these arrhythmic event probabilities and their associated parameters. This LRM is also used to demonstrate how uncertainties in experimentally measured values determine the uncertainty in P(EB). In a study of the role of [Ca2+]SRini uncertainty, we show a special property of the uncertainty in P(EB), where with increasing [Ca2+]SRini uncertainty, P(EB) uncertainty first increases and then decreases. Lastly, we demonstrate that IK1 suppression, at the level that occurs in heart failure myocytes, increases P(EB).Qingchu JinJoseph L GreensteinRaimond L WinslowPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 10, p e1009536 (2021)
institution DOAJ
collection DOAJ
language EN
topic Biology (General)
QH301-705.5
spellingShingle Biology (General)
QH301-705.5
Qingchu Jin
Joseph L Greenstein
Raimond L Winslow
Estimating ectopic beat probability with simplified statistical models that account for experimental uncertainty.
description Ectopic beats (EBs) are cellular arrhythmias that can trigger lethal arrhythmias. Simulations using biophysically-detailed cardiac myocyte models can reveal how model parameters influence the probability of these cellular arrhythmias, however such analyses can pose a huge computational burden. Here, we develop a simplified approach in which logistic regression models (LRMs) are used to define a mapping between the parameters of complex cell models and the probability of EBs (P(EB)). As an example, in this study, we build an LRM for P(EB) as a function of the initial value of diastolic cytosolic Ca2+ concentration ([Ca2+]iini), the initial state of sarcoplasmic reticulum (SR) Ca2+ load ([Ca2+]SRini), and kinetic parameters of the inward rectifier K+ current (IK1) and ryanodine receptor (RyR). This approach, which we refer to as arrhythmia sensitivity analysis, allows for evaluation of the relationship between these arrhythmic event probabilities and their associated parameters. This LRM is also used to demonstrate how uncertainties in experimentally measured values determine the uncertainty in P(EB). In a study of the role of [Ca2+]SRini uncertainty, we show a special property of the uncertainty in P(EB), where with increasing [Ca2+]SRini uncertainty, P(EB) uncertainty first increases and then decreases. Lastly, we demonstrate that IK1 suppression, at the level that occurs in heart failure myocytes, increases P(EB).
format article
author Qingchu Jin
Joseph L Greenstein
Raimond L Winslow
author_facet Qingchu Jin
Joseph L Greenstein
Raimond L Winslow
author_sort Qingchu Jin
title Estimating ectopic beat probability with simplified statistical models that account for experimental uncertainty.
title_short Estimating ectopic beat probability with simplified statistical models that account for experimental uncertainty.
title_full Estimating ectopic beat probability with simplified statistical models that account for experimental uncertainty.
title_fullStr Estimating ectopic beat probability with simplified statistical models that account for experimental uncertainty.
title_full_unstemmed Estimating ectopic beat probability with simplified statistical models that account for experimental uncertainty.
title_sort estimating ectopic beat probability with simplified statistical models that account for experimental uncertainty.
publisher Public Library of Science (PLoS)
publishDate 2021
url https://doaj.org/article/477112a02f4f479683219e2e669f6343
work_keys_str_mv AT qingchujin estimatingectopicbeatprobabilitywithsimplifiedstatisticalmodelsthataccountforexperimentaluncertainty
AT josephlgreenstein estimatingectopicbeatprobabilitywithsimplifiedstatisticalmodelsthataccountforexperimentaluncertainty
AT raimondlwinslow estimatingectopicbeatprobabilitywithsimplifiedstatisticalmodelsthataccountforexperimentaluncertainty
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