scholarly journals Estimating Ectopic Beat Probability with Simplified Statistical Models that Account for Experimental Uncertainty

2021 ◽  
Author(s):  
Qingchu Jin ◽  
Joseph L. Greenstein ◽  
Raimond L. Winslow
Keyword(s):  
Sensitivity Analysis ◽  
Cardiac Myocyte ◽  
Special Property ◽  
Biophysical Model ◽  
Ectopic Beat ◽  
Model Parameters ◽  
Computational Burden ◽  
Simplified Approach ◽  
Ectopic Beats ◽  
The Relationship

AbstractEctopic 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 diastolic cytosolic Ca2+ concentration ([Ca2+]i), sarcoplasmic reticulum (SR) Ca2+ load, 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+]SR uncertainty, we show a special property of the uncertainty in P(EB), where with increasing [Ca2+]SR 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).Author summaryAn ectopic beat is an abnormal cellular electrical event which can trigger dangerous arrhythmias in the heart. Complex biophysical models of the cardiac myocyte can be used to reveal how cell properties affect the probability of ectopic beats. However, such analyses can pose a huge computational burden. We develop a simplified approach that enables a highly complex biophysical model to be reduced to a rather simple statistical model from which the functional relationship between myocyte model parameters and the probability of an ectopic beat is determined. We refer to this approach as arrhythmia sensitivity analysis. Given the efficiency of our approach, we also use it to demonstrate how uncertainties in experimentally measured myocyte model parameters determine the uncertainty in ectopic beat probability. We find that, with increasing model parameter uncertainty, the uncertainty in probability of ectopic beat first increases and then decreases. In general, our approach can efficiently analyze the relationship between cardiac myocyte parameters and the probability of ectopic beats and can be used to study how uncertainty of these cardiac myocyte parameters influences the ectopic beat probability.

scholarly journals Estimating the Probability of Cellular Arrhythmias with Simplified Statistical Models that Account for Experimentally Observed Uncertainty

2020 ◽  
Author(s):  
Qingchu Jin ◽  
Joseph L. Greenstein ◽  
Raimond L. Winslow
Keyword(s):  
Long Qt Syndrome ◽  
Cardiac Myocyte ◽  
Delayed Rectifier ◽  
Model Parameters ◽  
Parameter Uncertainties ◽  
Long Qt ◽  
Simplified Approach ◽  
Logistic Regression Models ◽  
Delayed Rectifier Current ◽  
Qt Syndrome

AbstractEarly after-depolarizations (EADs) are action potential (AP) repolarization abnormalities that can trigger lethal arrhythmias in, for example, Long QT Syndrome and heart failure. Simulations using biophysically-detailed cardiac myocyte models can reveal how model parameters influence the probability of these cellular arrhythmias, however such analyses often 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 EADs. Specifically, we develop an LRM for predicting the probability of EADs (P(EAD)) as a function of slow-activating delayed rectifier current (IKs) parameters, and for identifying those parameters with greatest influence on P(EAD). This LRM, which requires negligible computational resources, is also used to demonstrate how uncertainties in experimentally measured values of IKs model parameters influence P(EAD). We refer to this as arrhythmia sensitivity analysis. In the investigation of five different IKs parameters associated with Long QT syndrome 1 (LQTS1) mutations, the predicted P(EAD) when rank ordered for 6 LQTS1 mutations matches the trend in risk from patients with the same mutations as measured by clinical cardiac event rates. We also demonstrate the degree to which parameter uncertainties map to uncertainty of P(EAD), with IKs conductance having the greatest impact. These results demonstrate the potential for arrhythmia risk prediction using model-based approaches for estimation of P(EAD).

scholarly journals Comparative hydrology: relationships among physical characteristics, hydrological behavior, and results of the SWAT model in different regions of Brazil (Hidrologia comparativa: relações entre características físicas, comportamento hidrológico e ....)

2015 ◽  
Vol 7 (6) ◽  
pp. 1187
Author(s):  
Jorge Enoch Furquim Werneck Lima ◽  
Suzana Montenegro ◽  
Abelardo Antônio De Assunção Montenegro ◽  
Sergio Koide
Keyword(s):  
Land Use ◽  
Sensitivity Analysis ◽  
Model Calibration ◽  
Swat Model ◽  
Physical Characteristics ◽  
Model Parameters ◽  
Caatinga Biome ◽  
Comparative Hydrology ◽  
The Relationship ◽  
Semi Arid

Comparative hydrology studies, either by the similarities or the differences in the obtained data and results, represent an important tool for advancing knowledge of cause-effect relationships between the physical characteristics of the basins and their hydrological behavior. The objective of this study was to present a comparative analysis of measured and simulated characteristics of experimental and representative basins in different regions of Brazil. The SWAT model was used. Four catchments were evaluated: Alto Ipanema, located in the Caatinga biome, with semi-arid climate; Tapacurá, in the transition zone between the Caatinga and Atlantic Forest biomes, with hot and humid tropical climate; and Lago Descoberto and Alto Jardim, both in the Cerrado biome and with tropical altitude climate. The catchments were compared with respect to their physical characteristics (climate, soil, altitude, and land use). Using sensitivity analysis, it was found which of the SWAT model parameters best explain the hydrological behavior of the study regions. Considering its characteristics, the parameters values obtained in each catchment after model calibration were analyzed and compared, indicating the possibility of using these values as reference for their regions. The results indicate a clear relationship between the physical characteristics of watersheds, their respective hydrological behavior, and the values of two SWAT model parameters, CN2 and SOL_K. For other parameters, the relationship between the obtained values do not reflected adequately the characteristics of the catchment, indicating a need for improvement in the physical basis of the calibrated model.

scholarly journals Statistical Approach to Incorporating Experimental Variability into a Mathematical Model of the Voltage-Gated Na+ Channel and Human Atrial Action Potential

Cells ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 1516
Author(s):  
Daniel Gratz ◽  
Alexander J Winkle ◽  
Seth H Weinberg ◽  
Thomas J Hund
Keyword(s):  
Action Potential ◽  
Mathematical Models ◽  
Cardiac Myocyte ◽  
Population Level ◽  
Na Channel ◽  
Model Parameters ◽  
Healthy Population ◽  
Experimental Measurements ◽  
Voltage Gated ◽  
Experimental Variability

The voltage-gated Na+ channel Nav1.5 is critical for normal cardiac myocyte excitability. Mathematical models have been widely used to study Nav1.5 function and link to a range of cardiac arrhythmias. There is growing appreciation for the importance of incorporating physiological heterogeneity observed even in a healthy population into mathematical models of the cardiac action potential. Here, we apply methods from Bayesian statistics to capture the variability in experimental measurements on human atrial Nav1.5 across experimental protocols and labs. This variability was used to define a physiological distribution for model parameters in a novel model formulation of Nav1.5, which was then incorporated into an existing human atrial action potential model. Model validation was performed by comparing the simulated distribution of action potential upstroke velocity measurements to experimental measurements from several different sources. Going forward, we hope to apply this approach to other major atrial ion channels to create a comprehensive model of the human atrial AP. We anticipate that such a model will be useful for understanding excitability at the population level, including variable drug response and penetrance of variants linked to inherited cardiac arrhythmia syndromes.

scholarly journals A Sensitivity Analysis of the SPACSYS Model

Agriculture ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 624
Author(s):  
Yan Shan ◽  
Mingbin Huang ◽  
Paul Harris ◽  
Lianhai Wu
Keyword(s):  
Sensitivity Analysis ◽  
Wheat Yield ◽  
Climatic Conditions ◽  
Water Dynamics ◽  
Ecological Modelling ◽  
Soil Conditions ◽  
Model Parameters ◽  
Nutrient Inputs ◽  
Nutrient Pool ◽  
Wheat Field

A sensitivity analysis is critical for determining the relative importance of model parameters to their influence on the simulated outputs from a process-based model. In this study, a sensitivity analysis for the SPACSYS model, first published in Ecological Modelling (Wu, et al., 2007), was conducted with respect to changes in 61 input parameters and their influence on 27 output variables. Parameter sensitivity was conducted in a ‘one at a time’ manner and objectively assessed through a single statistical diagnostic (normalized root mean square deviation) which ranked parameters according to their influence of each output variable in turn. A winter wheat field experiment provided the case study data. Two sets of weather elements to represent different climatic conditions and four different soil types were specified, where results indicated little influence on these specifications for the identification of the most sensitive parameters. Soil conditions and management were found to affect the ranking of parameter sensitivities more strongly than weather conditions for the selected outputs. Parameters related to drainage were strongly influential for simulations of soil water dynamics, yield and biomass of wheat, runoff, and leaching from soil during individual and consecutive growing years. Wheat yield and biomass simulations were sensitive to the ‘ammonium immobilised fraction’ parameter that related to soil mineralization and immobilisation. Simulations of CO2 release from the soil and soil nutrient pool changes were most sensitive to external nutrient inputs and the process of denitrification, mineralization, and decomposition. This study provides important evidence of which SPACSYS parameters require the most care in their specification. Moving forward, this evidence can help direct efficient sampling and lab analyses for increased accuracy of such parameters. Results provide a useful reference for model users on which parameters are most influential for different simulation goals, which in turn provides better informed decision making for farmers and government policy alike.

scholarly journals Global Sensitivity Analysis of a Homogenized Constrained Mixture Model of Arterial Growth and Remodeling

2021 ◽  
Author(s):  
Sebastian Brandstaeter ◽  
Sebastian L. Fuchs ◽  
Jonas Biehler ◽  
Roland C. Aydin ◽  
Wolfgang A. Wall ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Global Sensitivity Analysis ◽  
Model Parameters ◽  
Computational Studies ◽  
Growth And Remodeling ◽  
Global Sensitivity ◽  
Output Variability ◽  
Constrained Mixture ◽  
The One ◽  
Influential Parameters

AbstractGrowth and remodeling in arterial tissue have attracted considerable attention over the last decade. Mathematical models have been proposed, and computational studies with these have helped to understand the role of the different model parameters. So far it remains, however, poorly understood how much of the model output variability can be attributed to the individual input parameters and their interactions. To clarify this, we propose herein a global sensitivity analysis, based on Sobol indices, for a homogenized constrained mixture model of aortic growth and remodeling. In two representative examples, we found that 54–80% of the long term output variability resulted from only three model parameters. In our study, the two most influential parameters were the one characterizing the ability of the tissue to increase collagen production under increased stress and the one characterizing the collagen half-life time. The third most influential parameter was the one characterizing the strain-stiffening of collagen under large deformation. Our results suggest that in future computational studies it may - at least in scenarios similar to the ones studied herein - suffice to use population average values for the other parameters. Moreover, our results suggest that developing methods to measure the said three most influential parameters may be an important step towards reliable patient-specific predictions of the enlargement of abdominal aortic aneurysms in clinical practice.

scholarly journals Neural network-based modeling of the number of microbubbles generated with four circulation factors in cardiopulmonary bypass

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Satoshi Miyamoto ◽  
Zu Soh ◽  
Shigeyuki Okahara ◽  
Akira Furui ◽  
Taiichi Takasaki ◽  
...  
Keyword(s):  
Cardiopulmonary Bypass ◽  
Flow Rate ◽  
Neurological Complications ◽  
Estimation Accuracy ◽  
Model Parameters ◽  
Perfusion Flow ◽  
Postsurgical Complication ◽  
Tenfold Cross Validation ◽  
Suction Flow ◽  
The Relationship

AbstractThe need for the estimation of the number of microbubbles (MBs) in cardiopulmonary bypass surgery has been recognized among surgeons to avoid postoperative neurological complications. MBs that exceed the diameter of human capillaries may cause endothelial disruption as well as microvascular obstructions that block posterior capillary blood flow. In this paper, we analyzed the relationship between the number of microbubbles generated and four circulation factors, i.e., intraoperative suction flow rate, venous reservoir level, continuous blood viscosity and perfusion flow rate in cardiopulmonary bypass, and proposed a neural-networked model to estimate the number of microbubbles with the factors. Model parameters were determined in a machine-learning manner using experimental data with bovine blood as the perfusate. The estimation accuracy of the model, assessed by tenfold cross-validation, demonstrated that the number of MBs can be estimated with a determinant coefficient R2 = 0.9328 (p < 0.001). A significant increase in the residual error was found when each of four factors was excluded from the contributory variables. The study demonstrated the importance of four circulation factors in the prediction of the number of MBs and its capacity to eliminate potential postsurgical complication risks.

scholarly journals Gaussian Processes Proxy Model with Latent Variable Models and Variogram-Based Sensitivity Analysis for Assisted History Matching

Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4290
Author(s):  
Dongmei Zhang ◽  
Yuyang Zhang ◽  
Bohou Jiang ◽  
Xinwei Jiang ◽  
Zhijiang Kang
Keyword(s):  
Sensitivity Analysis ◽  
Gaussian Processes ◽  
Latent Variable ◽  
History Matching ◽  
Latent Variable Models ◽  
High Dimensional ◽  
Model Parameters ◽  
Variable Model ◽  
Assisted History Matching ◽  
Proxy Models

Reservoir history matching is a well-known inverse problem for production prediction where enormous uncertain reservoir parameters of a reservoir numerical model are optimized by minimizing the misfit between the simulated and history production data. Gaussian Process (GP) has shown promising performance for assisted history matching due to the efficient nonparametric and nonlinear model with few model parameters to be tuned automatically. Recently introduced Gaussian Processes proxy models and Variogram Analysis of Response Surface-based sensitivity analysis (GP-VARS) uses forward and inverse Gaussian Processes (GP) based proxy models with the VARS-based sensitivity analysis to optimize the high-dimensional reservoir parameters. However, the inverse GP solution (GPIS) in GP-VARS are unsatisfactory especially for enormous reservoir parameters where the mapping from low-dimensional misfits to high-dimensional uncertain reservoir parameters could be poorly modeled by GP. To improve the performance of GP-VARS, in this paper we propose the Gaussian Processes proxy models with Latent Variable Models and VARS-based sensitivity analysis (GPLVM-VARS) where Gaussian Processes Latent Variable Model (GPLVM)-based inverse solution (GPLVMIS) instead of GP-based GPIS is provided with the inputs and outputs of GPIS reversed. The experimental results demonstrate the effectiveness of the proposed GPLVM-VARS in terms of accuracy and complexity. The source code of the proposed GPLVM-VARS is available at https://github.com/XinweiJiang/GPLVM-VARS.

scholarly journals Influence of Selected Model Parameters on the Electromagnetic Levitation Melting Efficiency

2021 ◽  
Vol 11 (9) ◽  
pp. 3827
Author(s):  
Blazej Nycz ◽  
Lukasz Malinski ◽  
Roman Przylucki
Keyword(s):  
Electromagnetic Levitation ◽  
Optimization Methods ◽  
Calculation Model ◽  
Model Parameters ◽  
Starting Point ◽  
Low Efficiency ◽  
The Relationship ◽  
Reactive Metals ◽  
Electromagnetic Levitation Melting ◽  
Metal Melting

The article presents the results of multivariate calculations for the levitation metal melting system. The research had two main goals. The first goal of the multivariate calculations was to find the relationship between the basic electrical and geometric parameters of the selected calculation model and the maximum electromagnetic buoyancy force and the maximum power dissipated in the charge. The second goal was to find quasi-optimal conditions for levitation. The choice of the model with the highest melting efficiency is very important because electromagnetic levitation is essentially a low-efficiency process. Despite the low efficiency of this method, it is worth dealing with it because is one of the few methods that allow melting and obtaining alloys of refractory reactive metals. The research was limited to the analysis of the electromagnetic field modeled three-dimensionally. From among of 245 variants considered in the article, the most promising one was selected characterized by the highest efficiency. This variant will be a starting point for further work with the use of optimization methods.

scholarly journals Cost-effectiveness of TAS-102 plus bevacizumab versus TAS-102 monotherapy in patients with metastatic colorectal cancer

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Kiyoaki Sugiura ◽  
Yuki Seo ◽  
Takayuki Takahashi ◽  
Hideyuki Tokura ◽  
Yasuhiro Ito ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Health Care ◽  
Sensitivity Analysis ◽  
Cost Effectiveness ◽  
Combination Therapy ◽  
Metastatic Colorectal Cancer ◽  
Cost Effective ◽  
Model Parameters ◽  
Combination Regimen ◽  
The Cost

Abstract Background TAS-102 plus bevacizumab is an anticipated combination regimen for patients who have metastatic colorectal cancer. However, evidence supporting its use for this indication is limited. We compared the cost-effectiveness of TAS-102 plus bevacizumab combination therapy with TAS-102 monotherapy for patients with chemorefractory metastatic colorectal cancer. Method Markov decision modeling using treatment costs, disease-free survival, and overall survival was performed to examine the cost-effectiveness of TAS-102 plus bevacizumab combination therapy and TAS-102 monotherapy. The Japanese health care payer’s perspective was adopted. The outcomes were modeled on the basis of published literature. The incremental cost-effectiveness ratio (ICER) between the two treatment regimens was the primary outcome. Sensitivity analysis was performed and the effect of uncertainty on the model parameters were investigated. Results TAS-102 plus bevacizumab had an ICER of $21,534 per quality-adjusted life-year (QALY) gained compared with TAS-102 monotherapy. Sensitivity analysis demonstrated that TAS-102 monotherapy was more cost-effective than TAS-102 and bevacizumab combination therapy at a willingness-to-pay of under $50,000 per QALY gained. Conclusions TAS-102 and bevacizumab combination therapy is a cost-effective option for patients who have metastatic colorectal cancer in the Japanese health care system.

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