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Masè M, Cristoforetti A, Pelloni S, Ravelli F. Systematic in-silico evaluation of fibrosis effects on re-entrant wave dynamics in atrial tissue. Sci Rep 2024; 14:11427. [PMID: 38763959 DOI: 10.1038/s41598-024-62002-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 05/13/2024] [Indexed: 05/21/2024] Open
Abstract
Despite the key role of fibrosis in atrial fibrillation (AF), the effects of different spatial distributions and textures of fibrosis on wave propagation mechanisms in AF are not fully understood. To clarify these aspects, we performed a systematic computational study to assess fibrosis effects on the characteristics and stability of re-entrant waves in electrically-remodelled atrial tissues. A stochastic algorithm, which generated fibrotic distributions with controlled overall amount, average size, and orientation of fibrosis elements, was implemented on a monolayer spheric atrial model. 245 simulations were run at changing fibrosis parameters. The emerging propagation patterns were quantified in terms of rate, regularity, and coupling by frequency-domain analysis of correspondent synthetic bipolar electrograms. At the increase of fibrosis amount, the rate of reentrant waves significantly decreased and higher levels of regularity and coupling were observed (p < 0.0001). Higher spatial variability and pattern stochasticity over repetitions was observed for larger amount of fibrosis, especially in the presence of patchy and compact fibrosis. Overall, propagation slowing and organization led to higher stability of re-entrant waves. These results strengthen the evidence that the amount and spatial distribution of fibrosis concur in dictating re-entry dynamics in remodeled tissue and represent key factors in AF maintenance.
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Affiliation(s)
- Michela Masè
- Laboratory of Biophysics and Translational Cardiology, Department of Cellular, Computational and Integrative Biology-CIBIO, University of Trento, Via Sommarive 18, 38123, Povo, Trento, Italy.
| | - Alessandro Cristoforetti
- Laboratory of Biophysics and Translational Cardiology, Department of Cellular, Computational and Integrative Biology-CIBIO, University of Trento, Via Sommarive 18, 38123, Povo, Trento, Italy
| | - Samuele Pelloni
- Laboratory of Biophysics and Translational Cardiology, Department of Cellular, Computational and Integrative Biology-CIBIO, University of Trento, Via Sommarive 18, 38123, Povo, Trento, Italy
| | - Flavia Ravelli
- Laboratory of Biophysics and Translational Cardiology, Department of Cellular, Computational and Integrative Biology-CIBIO, University of Trento, Via Sommarive 18, 38123, Povo, Trento, Italy
- CISMed-Centre for Medical Sciences, University of Trento, 38122, Trento, Italy
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Plappert F, Engström G, Platonov PG, Wallman M, Sandberg F. ECG-based estimation of respiration-induced autonomic modulation of AV nodal conduction during atrial fibrillation. Front Physiol 2024; 15:1281343. [PMID: 38779321 PMCID: PMC11110927 DOI: 10.3389/fphys.2024.1281343] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 04/08/2024] [Indexed: 05/25/2024] Open
Abstract
Introduction: Information about autonomic nervous system (ANS) activity may offer insights about atrial fibrillation (AF) progression and support personalized AF treatment but is not easily accessible from the ECG. In this study, we propose a new approach for ECG-based assessment of respiratory modulation in atrioventricular (AV) nodal refractory period and conduction delay. Methods: A 1-dimensional convolutional neural network (1D-CNN) was trained to estimate respiratory modulation of AV nodal conduction properties from 1-minute segments of RR series, respiration signals, and atrial fibrillatory rates (AFR) using synthetic data that replicates clinical ECG-derived data. The synthetic data were generated using a network model of the AV node and 4 million unique model parameter sets. The 1D-CNN was then used to analyze respiratory modulation in clinical deep breathing test data of 28 patients in AF, where an ECG-derived respiration signal was extracted using a novel approach based on periodic component analysis. Results: We demonstrated using synthetic data that the 1D-CNN can estimate the respiratory modulation from RR series alone with a Pearson sample correlation of r = 0.805 and that the addition of either respiration signal (r = 0.830), AFR (r = 0.837), or both (r = 0.855) improves the estimation. Discussion: Initial results from analysis of ECG data suggest that our proposed estimate of respiration-induced autonomic modulation, a resp, is reproducible and sufficiently sensitive to monitor changes and detect individual differences. However, further studies are needed to verify the reproducibility, sensitivity, and clinical significance of a resp.
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Affiliation(s)
- Felix Plappert
- Department of Biomedical Engineering, Lund University, Lund, Sweden
| | - Gunnar Engström
- Department of Clinical Sciences, Cardiovascular Research–Epidemiology, Malmö, Sweden
| | - Pyotr G. Platonov
- Department of Cardiology, Clinical Sciences, Lund University, Lund, Sweden
| | - Mikael Wallman
- Fraunhofer-Chalmers Centre, Department of Systems and Data Analysis, Gothenburg, Sweden
| | - Frida Sandberg
- Department of Biomedical Engineering, Lund University, Lund, Sweden
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Karlsson M, Platonov PG, Ulimoen SR, Sandberg F, Wallman M. Model-based estimation of AV-nodal refractory period and conduction delay trends from ECG. Front Physiol 2024; 14:1287365. [PMID: 38283279 PMCID: PMC10811553 DOI: 10.3389/fphys.2023.1287365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Accepted: 12/18/2023] [Indexed: 01/30/2024] Open
Abstract
Introduction: Atrial fibrillation (AF) is the most common arrhythmia, associated with significant burdens to patients and the healthcare system. The atrioventricular (AV) node plays a vital role in regulating heart rate during AF by filtering electrical impulses from the atria. However, it is often insufficient in regards to maintaining a healthy heart rate, thus the AV node properties are modified using rate-control drugs. Moreover, treatment selection during permanent AF is currently done empirically. Quantifying individual differences in diurnal and short-term variability of AV-nodal function could aid in personalized treatment selection. Methods: This study presents a novel methodology for estimating the refractory period (RP) and conduction delay (CD) trends, and their uncertainty in the two pathways of the AV node during 24 h using non-invasive data. This was achieved by utilizing a network model together with a problem-specific genetic algorithm and an approximate Bayesian computation algorithm. Diurnal variability in the estimated RP and CD was quantified by the difference between the daytime and nighttime estimates, and short-term variability was quantified by the Kolmogorov-Smirnov distance between adjacent 10-min segments in the 24-h trends. Additionally, the predictive value of the derived parameter trends regarding drug outcome was investigated using several machine learning tools. Results: Holter electrocardiograms from 51 patients with permanent AF during baseline were analyzed, and the predictive power of variations in RP and CD on the resulting heart rate reduction after treatment with four rate control drugs was investigated. Diurnal variability yielded no correlation to treatment outcome, and no prediction of drug outcome was possible using the machine learning tools. However, a correlation between the short-term variability for the RP and CD in the fast pathway and resulting heart rate reduction during treatment with metoprolol (ρ = 0.48, p < 0.005 in RP, ρ = 0.35, p < 0.05 in CD) were found. Discussion: The proposed methodology enables non-invasive estimation of the AV node properties during 24 h, which-indicated by the correlation between the short-term variability and heart rate reduction-may have the potential to assist in treatment selection.
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Affiliation(s)
- Mattias Karlsson
- Department of Systems and Data Analysis, Fraunhofer-Chalmers Centre, Gothenburg, Sweden
- Department of Biomedical Engineering, Lund University, Lund, Sweden
| | - Pyotr G. Platonov
- Department of Cardiology, Clinical Sciences, Lund University, Lund, Sweden
| | - Sara R. Ulimoen
- Department of Medical Research, Vestre Viken Hospital Trust, Bærum Hospital, Drammen, Norway
| | - Frida Sandberg
- Department of Biomedical Engineering, Lund University, Lund, Sweden
| | - Mikael Wallman
- Department of Systems and Data Analysis, Fraunhofer-Chalmers Centre, Gothenburg, Sweden
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Karlsson M, Wallman M, Platonov PG, Ulimoen SR, Sandberg F. ECG based assessment of circadian variation in AV-nodal conduction during AF—Influence of rate control drugs. Front Physiol 2022; 13:976526. [PMID: 36267586 PMCID: PMC9577140 DOI: 10.3389/fphys.2022.976526] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Accepted: 09/05/2022] [Indexed: 11/13/2022] Open
Abstract
The heart rate during atrial fibrillation (AF) is highly dependent on the conduction properties of the atrioventricular (AV) node. These properties can be affected using β-blockers or calcium channel blockers, mainly chosen empirically. Characterization of individual AV-nodal conduction could assist in personalized treatment selection during AF. Individual AV nodal refractory periods and conduction delays were characterized based on 24-hour ambulatory ECGs from 60 patients with permanent AF. This was done by estimating model parameters from a previously created mathematical network model of the AV node using a problem-specific genetic algorithm. Based on the estimated model parameters, the circadian variation and its drug-dependent difference between treatment with two β-blockers and two calcium channel blockers were quantified on a population level by means of cosinor analysis using a linear mixed-effect approach. The mixed-effects analysis indicated increased refractoriness relative to baseline for all drugs. An additional decrease in circadian variation for parameters representing conduction delay was observed for the β-blockers. This indicates that the two drug types have quantifiable differences in their effects on AV-nodal conduction properties. These differences could be important in treatment outcome, and thus quantifying them could assist in treatment selection.
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Affiliation(s)
- Mattias Karlsson
- Department of Systems and Data Analysis, Fraunhofer-Chalmers Centre, Gothenburg, Sweden
- Department of Biomedical Engineering, Lund University, Lund, Sweden
| | - Mikael Wallman
- Department of Systems and Data Analysis, Fraunhofer-Chalmers Centre, Gothenburg, Sweden
| | - Pyotr G. Platonov
- Department of Cardiology, Clinical Sciences, Lund University, Lund, Sweden
| | - Sara R. Ulimoen
- Vestre Viken Hospital Trust, Department of Medical Research, Bærum Hospital, Drammen, Norway
| | - Frida Sandberg
- Department of Biomedical Engineering, Lund University, Lund, Sweden
- *Correspondence: Frida Sandberg,
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Masè M, Cristoforetti A, Del Greco M, Ravelli F. A Divergence-Based Approach for the Identification of Atrial Fibrillation Focal Drivers From Multipolar Mapping: A Computational Study. Front Physiol 2021; 12:749430. [PMID: 35002755 PMCID: PMC8740027 DOI: 10.3389/fphys.2021.749430] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 11/30/2021] [Indexed: 11/13/2022] Open
Abstract
The expanding role of catheter ablation of atrial fibrillation (AF) has stimulated the development of novel mapping strategies to guide the procedure. We introduce a novel approach to characterize wave propagation and identify AF focal drivers from multipolar mapping data. The method reconstructs continuous activation patterns in the mapping area by a radial basis function (RBF) interpolation of multisite activation time series. Velocity vector fields are analytically determined, and the vector field divergence is used as a marker of focal drivers. The method was validated in a tissue patch cellular automaton model and in an anatomically realistic left atrial (LA) model with Courtemanche-Ramirez-Nattel ionic dynamics. Divergence analysis was effective in identifying focal drivers in a complex simulated AF pattern. Localization was reliable even with consistent reduction (47%) in the number of mapping points and in the presence of activation time misdetections (noise <10% of the cycle length). Proof-of-concept application of the method to human AF mapping data showed that divergence analysis consistently detected focal activation in the pulmonary veins and LA appendage area. These results suggest the potential of divergence analysis in combination with multipolar mapping to identify AF critical sites. Further studies on large clinical datasets may help to assess the clinical feasibility and benefit of divergence analysis for the optimization of ablation treatment.
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Affiliation(s)
- Michela Masè
- Laboratory of Biophysics and Translational Cardiology, Department of Cellular, Computational and Integrative Biology – CIBIO, University of Trento, Trento, Italy
- Institute of Mountain Emergency Medicine, EURAC Research, Bolzano, Italy
| | - Alessandro Cristoforetti
- Laboratory of Biophysics and Translational Cardiology, Department of Cellular, Computational and Integrative Biology – CIBIO, University of Trento, Trento, Italy
| | - Maurizio Del Greco
- Division of Cardiology, Santa Maria del Carmine Hospital, Rovereto, Italy
| | - Flavia Ravelli
- Laboratory of Biophysics and Translational Cardiology, Department of Cellular, Computational and Integrative Biology – CIBIO, University of Trento, Trento, Italy
- CISMed – Centre for Medical Sciences, University of Trento, Trento, Italy
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Masè M, Ravelli F. Understanding the effects of heartbeat irregularity on ventricular function in human atrial fibrillation: simulation models may help to untie the knot. Europace 2021; 23:1868. [PMID: 34160027 DOI: 10.1093/europace/euab143] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Accepted: 05/15/2021] [Indexed: 11/13/2022] Open
Affiliation(s)
- Michela Masè
- Institute of Mountain Emergency Medicine, EURAC Research, Via Druso n.1, 39100 Bolzano, Italy
| | - Flavia Ravelli
- Department of Cellular, Computational and Integrative Biology-CIBIO, University of Trento, Trento, Italy
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Computational Simulation of Cardiac Function and Blood Flow in the Circulatory System under Continuous Flow Left Ventricular Assist Device Support during Atrial Fibrillation. APPLIED SCIENCES-BASEL 2020. [DOI: 10.3390/app10030876] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Prevalence of atrial fibrillation (AF) is high in heart failure patients supported by a continuous flow left ventricular assist device (CF-LVAD); however, the long term effects remain unclear. In this study, a computational model simulating effects of AF on cardiac function and blood flow for heart failure and CF-LVAD support is presented. The computational model describes left and right heart, systemic and pulmonary circulations and cerebral circulation, and utilises patient-derived RR interval series for normal sinus rhythm (SR). Moreover, AF was simulated using patient-derived unimodal and bimodal distributed RR interval series and patient specific left ventricular systolic functions. The cardiovascular system model simulated clinically-observed haemodynamic outcomes under CF-LVAD support during AF, such as reduced right ventricular ejection fraction and elevated systolic pulmonary arterial pressure. Moreover, relatively high aortic peak pressures and middle arterial peak flow rates during AF with bimodal RR interval distribution, reduced to similar levels as during normal SR and AF with unimodal RR interval distribution under CF-LVAD support. The simulation results suggest that factors such as distribution of RR intervals and systolic left ventricular function may influence haemodynamic outcome of CF-LVAD support during AF.
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Mase M, Marsili IA, Nollo G, Ravelli F. Modeling Framework for the Generation of Synthetic RR Series during Atrial Arrhythmias .. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2019:6347-6350. [PMID: 31947294 DOI: 10.1109/embc.2019.8857842] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
We introduced a modeling framework for the generation of realistic ventricular interval (RR) series to be used in the validation of atrial arrhythmia detection algorithms. The framework included three previously proposed models, which reproduced the specific variability properties of RR series in normal sinus rhythm, atrial flutter (AFL) and atrial fibrillation (AF). Transitions between the three rhythms were governed by a three-state continuous-time Markov chain model, which could be tuned to obtain arrhythmic episodes of the requested length. As a representative application, the modeling framework was used to generate a database of RR series for the validation of a previously proposed AF detection algorithm, which was based on RR pattern similarity. The validation showed the deterioration of detector performance in presence of simulated AFL episodes. Thanks to the detailed reproduction of the specific features of the two most common atrial arrhythmias, our modeling framework may constitute a novel tool for the assessment and comparison of detection algorithm performance.
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Petrenas A, Marozas V, Sološenko A, Kubilius R, Skibarkiene J, Oster J, Sörnmo L. Electrocardiogram modeling during paroxysmal atrial fibrillation: application to the detection of brief episodes. Physiol Meas 2017; 38:2058-2080. [PMID: 28980979 DOI: 10.1088/1361-6579/aa9153] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
OBJECTIVE A model for simulating multi-lead ECG signals during paroxysmal atrial fibrillation (AF) is proposed. SIGNIFICANCE The model is of particular significance when evaluating detection performance in the presence of brief AF episodes, especially since annotated databases with such episodes are lacking. APPROACH The proposed model accounts for important characteristics such as switching between sinus rhythm and AF, varying P-wave morphology, repetition rate of f-waves, presence of atrial premature beats, and various types of noise. MAIN RESULTS Two expert cardiologists assessed the realism of simulated signals relative to real ECG signals, both in sinus rhythm and AF. The cardiologists identified the correct rhythm in all cases, and considered two-thirds of the simulated signals as realistic. The proposed model was also investigated by evaluating the performance of two AF detectors which explored either rhythm only or both rhythm and morphology. The results show that detection performance is strongly dependent on AF episode duration, and, consequently, demonstrate that the model can play a significant role in the investigation of detector properties.
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Affiliation(s)
- Andrius Petrenas
- Biomedical Engineering Institute, Kaunas University of Technology, Kaunas, Lithuania
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Wallman M, Sandberg F. Characterisation of human AV-nodal properties using a network model. Med Biol Eng Comput 2017; 56:247-259. [DOI: 10.1007/s11517-017-1684-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2017] [Accepted: 07/03/2017] [Indexed: 02/05/2023]
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Masè M, Disertori M, Marini M, Ravelli F. Characterization of rate and regularity of ventricular response during atrial tachyarrhythmias. Insight on atrial and nodal determinants. Physiol Meas 2017; 38:800-818. [DOI: 10.1088/1361-6579/aa6388] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Henriksson M, Corino VDA, Sornmo L, Sandberg F. A Statistical Atrioventricular Node Model Accounting for Pathway Switching During Atrial Fibrillation. IEEE Trans Biomed Eng 2016; 63:1842-1849. [DOI: 10.1109/tbme.2015.2503562] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Henriques TS, Mariani S, Burykin A, Rodrigues F, Silva TF, Goldberger AL. Multiscale Poincaré plots for visualizing the structure of heartbeat time series. BMC Med Inform Decis Mak 2016; 16:17. [PMID: 26860191 PMCID: PMC4746786 DOI: 10.1186/s12911-016-0252-0] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2015] [Accepted: 01/27/2016] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Poincaré delay maps are widely used in the analysis of cardiac interbeat interval (RR) dynamics. To facilitate visualization of the structure of these time series, we introduce multiscale Poincaré (MSP) plots. METHODS Starting with the original RR time series, the method employs a coarse-graining procedure to create a family of time series, each of which represents the system's dynamics in a different time scale. Next, the Poincaré plots are constructed for the original and the coarse-grained time series. Finally, as an optional adjunct, color can be added to each point to represent its normalized frequency. RESULTS We illustrate the MSP method on simulated Gaussian white and 1/f noise time series. The MSP plots of 1/f noise time series reveal relative conservation of the phase space area over multiple time scales, while those of white noise show a marked reduction in area. We also show how MSP plots can be used to illustrate the loss of complexity when heartbeat time series from healthy subjects are compared with those from patients with chronic (congestive) heart failure syndrome or with atrial fibrillation. CONCLUSIONS This generalized multiscale approach to Poincaré plots may be useful in visualizing other types of time series.
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Affiliation(s)
- Teresa S Henriques
- Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA, USA.
- Center for Anesthesia Research and Excellence (CARE), Beth Israel Deaconess Medical Center, Boston, MA, USA.
- Margret and H.A. Rey Institute of Nonlinear Dynamics in Physiology and Medicine, Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center, Boston, MA, USA.
| | - Sara Mariani
- Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA, USA.
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Anton Burykin
- Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA, USA.
| | - Filipa Rodrigues
- Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA, USA.
- Department of Physics, Faculty of Sciences, University of Lisbon, Lisbon, Portugal.
| | - Tiago F Silva
- Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA, USA.
- Department of Physics, Faculty of Sciences, University of Lisbon, Lisbon, Portugal.
| | - Ary L Goldberger
- Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA, USA.
- Margret and H.A. Rey Institute of Nonlinear Dynamics in Physiology and Medicine, Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center, Boston, MA, USA.
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Lenhoff H, Darpö B, Ferber G, Rosenqvist M, Frick M. Reduction over time of QTc prolongation in patients with sotalol after cardioversion of atrial fibrillation. Heart Rhythm 2015; 13:661-8. [PMID: 26654918 DOI: 10.1016/j.hrthm.2015.11.040] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2015] [Indexed: 11/24/2022]
Abstract
BACKGROUND Sotalol is recommended to prevent relapse of atrial fibrillation after cardioversion (CV). Sotalol prolongs the action potential by blocking the rapid component of the delayed rectifier potassium current, which results in corrected QT (QTc) prolongation on the electrocardiogram. Pronounced QTc prolongation may lead to proarrhythmias and sudden death. OBJECTIVE We investigated the dynamics of the QTc interval during the week after CV in patients treated with sotalol compared with patients treated with a β-blocker. METHODS Patients who underwent elective CV for persistent atrial fibrillation and maintained sinus rhythm for 1 week were included prospectively. All patients were on the highest tolerable stable dose of metoprolol or sotalol. Twelve-lead electrocardiograms were recorded 1 hour and 1 week after CV. RESULTS A total of 104 patients on sotalol and 104 on metoprolol were included; clinical characteristics between groups were comparable. One hour after CV, the QTc interval was significantly longer in sotalol-treated patients than in metoprolol-treated patients (465 ± 25 ms vs 423 ± 30 ms; P ≤ .0001). After 1 week, the QTc interval was reduced by -20.3 ± 24 ms in sotalol-treated patients (P ≤ .001); no such effect was seen in metoprolol-treated patients (-2.5 ± 18 ms; P = 0.28). The heart rate was stable during the week in both groups. In multivariate analysis of sotalol-treated patients, factors contributing to pronounced reduction in the QTc interval were longer QTc interval after CV and renal function. CONCLUSION The QTc interval is significantly reduced during the week after CV to sinus rhythm in sotalol-treated patients. This provides insight into the increased risk of proarrhythmias in the immediate time period after CV.
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Affiliation(s)
- Hanna Lenhoff
- Department of Clinical Science and Education, Division of Cardiology, Karolinska Institute, South Hospital, Stockholm, Sweden.
| | - Börje Darpö
- Statistik Georg Ferber GmbH, Riehen, Switzerland
| | - Georg Ferber
- Statistik Georg Ferber GmbH, Riehen, Switzerland
| | - Mårten Rosenqvist
- Department of Clinical Sciences, Karolinska Institute, Danderyd Hospital, Stockholm, Sweden
| | - Mats Frick
- Department of Clinical Science and Education, Division of Cardiology, Karolinska Institute, South Hospital, Stockholm, Sweden
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