How circadian variability of the heart rate and plasma electrolytes concentration influence the cardiac electrophysiology – model-based case study

Figures

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  Fig. 1. Simulated diurnal variation of the heart rate, presented as RR interval length [s] at all hours of day and night, in the virtual population

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  Fig. 2. Simulated diurnal variation of QT interval length values [ms] in the virtual population. Data are presented as the mean values with a standard deviation of the mean. The blue dots represent the mean QT values when the HR circadian changes alone were accounted for in the simulation scenario. Orange triangles represent the mean QT values when both, the HR circadian changes and plasma ion concentrations changes were accounted for in the simulation scenario

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  Fig. 3. A relationship between QT/QTcI [ms] and RR [s] values extracted from pseudoECG signals simulated for the healthy virtual population. The orange line represents the relationship between native QT values [ms] and the corresponding RR [s] values (orange triangles). Blue line represents the relationship between individually corrected QT values for the heart rate (QTcI [ms]) and the corresponding RR [s] values (blue squares)

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  Fig. 4. The mean and individual QTcI values [ms] over a 24-h period simulated in CSS and observed by Smetana et al. [12]. Blue dots represent individual simulated QTcI [ms], orange diamonds represent mean simulated QTcI [ms], and grey squares represent mean QTcI [ms] observed by Smetana et al. [12]

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  Fig. 5. Simulated circadian changes of plasma concentrations of potassium, sodium, or calcium ions and the relationship between ion concentrations and QTcI values. Plots on the left illustrate the diurnal fluctuations of potassium (top panel), sodium (middle panel), and calcium (bottom panel) plasma concentrations [mM] showed as the mean values and standard deviation around a mean. The scatter plots on the right illustrate the relationship between QTcI [ms] values and plasma concentrations of potassium (top panel), sodium (middle panel), and calcium (bottom panel) concentrations [mM]

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  Fig. 6. Simulated diurnal changes in QTcI [ms] values in the virtual population when neither the HR circadian changes nor plasma ion concentrations changes were accounted for in the simulation scenario. Blue dots represent individual QTcI values, orange dots represent mean QTcI values

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  Fig. 7. The time-plasma concentration profiles of tolterodine after its administration in a therapeutic dose of 2 mg bid (on the left) or in the supratherapeutic dose of 4 mg bid (on the right). Model-predicted [22] concentrations [ng/mL] are shown as the mean (in green) and 5th and 95th percentile (in grey) and compared with the data observed by Malhotra et al. [21]

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  Fig. 8. The simulated (orange dots) and the observed, either auto-read (black squares) or manual-read (blues squares) time-matched changes from baseline QTc values (ddQtcS) [ms] on day 4 of tolterodine administration in dose 2 mg bid (on the left) or 4 mg bid (on the right). The data are shown as the mean values, for simulated data with SD

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  Fig. 9. Mean of predicted QTcS values [ms] in time after administration of tolterodine if the HR circadian changes and plasma ion concentrations changes were accounted for in the simulation scenario (orange dots), neither of circadian changes were accounted for in the simulation (grey dots) or in the situation without a drug (blue squares)

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  Fig. 10. A relationship between simulated individual QTcS [ms] values and tolterodine concentrations [nM]. Orange line represents the relationship between QTcS [ms] and the corresponding tolterodine concentrations [nM] achieved when the HR circadian changes and plasma ion concentrations changes were accounted for in the simulation scenario (orange diamonds). Blue line represents the relationship between QTcS [ms] and the corresponding tolterodine concentrations [nM] achieved when neither of the circadian changes were accounted for in the simulation (grey dots)