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Antoun I, Li X, Kotb A, Barker J, Mavilakandy A, Koev I, Vali Z, Somani R, Ng GA. Body surface mapping of P-waves in sinus rhythm to predict recurrence following cardioversion for atrial fibrillation. Front Cardiovasc Med 2024; 11:1417029. [PMID: 39119182 PMCID: PMC11306046 DOI: 10.3389/fcvm.2024.1417029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2024] [Accepted: 07/15/2024] [Indexed: 08/10/2024] Open
Abstract
Background Direct current cardioversion (DCCV) is used as elective and emergency rhythm control for atrial fibrillation (AF). We aimed to explore the role of P-wave parameters measured during sinus rhythm using body surface mapping (BSM) in predicting successful DCCV for persistent atrial fibrillation (persAF) at 12 months. Methods This case-control study included 56 males >18 years old who underwent DCCV for persAF. P-wave parameter collection after DCCV for AF was done using 128 unipolar leads. A band-pass filter of 1-50 Hz was utilised. Corrected P-wave duration (PWDc), P-wave amplitude, and P-wave dispersion were measured to predict 12-month outcomes and time of recurrence. Results The mean age was 64 ± 4 years, and 23 patients (44%) were on amiodarone. The 12-month success rate was 44% (n = 23), while the rest reverted to AF after 2.6 ± 0.4 months. The parameters were comparable between successful and failed DCCV in the entire cohort and patients not on amiodarone. In patients on amiodarone, patients with failed arms had higher PWDc than those with successful arms (188 vs. 150 ms, P = 0.04). Receiver operator characteristic curve analysis for PWDc in the amiodarone cohort showed an area under the curve (AUC) of 0.75 and P = 0.049. A recurrence cut-off >161 ms had a sensitivity of 69% and a specificity of 100%, with a hazard ratio of 10.7, P = 0.004. The parameters were not predictive of the time of recurrence. Conclusion In patients on amiodarone, increased PWDc measured using BSM was associated with higher AF recurrence at 12 months following DCCV for persAF.
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Affiliation(s)
- Ibrahim Antoun
- Department of Cardiology, University Hospitals of Leicester NHS Trust, Glenfield Hospital, Leicester, United Kingdom
| | - Xin Li
- Department of Engineering, University of Leicester, Glenfield Hospital, Leicester, United Kingdom
| | - Ahmed Kotb
- Department of Cardiovascular Sciences, Clinical Science Wing, University of Leicester, Glenfield Hospital, Leicester, United Kingdom
| | - Joseph Barker
- Department of Cardiovascular Sciences, Clinical Science Wing, University of Leicester, Glenfield Hospital, Leicester, United Kingdom
| | - Akash Mavilakandy
- Department of Cardiovascular Sciences, Clinical Science Wing, University of Leicester, Glenfield Hospital, Leicester, United Kingdom
| | - Ivelin Koev
- Department of Cardiology, University Hospitals of Leicester NHS Trust, Glenfield Hospital, Leicester, United Kingdom
| | - Zakariyya Vali
- Department of Cardiology, University Hospitals of Leicester NHS Trust, Glenfield Hospital, Leicester, United Kingdom
| | - Riyaz Somani
- Department of Cardiology, University Hospitals of Leicester NHS Trust, Glenfield Hospital, Leicester, United Kingdom
- Department of Cardiovascular Sciences, Clinical Science Wing, University of Leicester, Glenfield Hospital, Leicester, United Kingdom
| | - G. André Ng
- Department of Cardiology, University Hospitals of Leicester NHS Trust, Glenfield Hospital, Leicester, United Kingdom
- Department of Cardiovascular Sciences, Clinical Science Wing, University of Leicester, Glenfield Hospital, Leicester, United Kingdom
- Department of Research, National Institute for Health Research Leicester Research Biomedical Centre, Leicester, United Kingdom
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Kwon S, Lee E, Ju H, Ahn HJ, Lee SR, Choi EK, Suh J, Oh S, Rhee W. Machine Learning Prediction for the Recurrence After Electrical Cardioversion of Patients With Persistent Atrial Fibrillation. Korean Circ J 2023; 53:677-689. [PMID: 37653713 PMCID: PMC10625851 DOI: 10.4070/kcj.2023.0012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 05/25/2023] [Accepted: 06/13/2023] [Indexed: 09/02/2023] Open
Abstract
BACKGROUND AND OBJECTIVES There is limited evidence regarding machine-learning prediction for the recurrence of atrial fibrillation (AF) after electrical cardioversion (ECV). This study aimed to predict the recurrence of AF after ECV using machine learning of clinical features and electrocardiograms (ECGs) in persistent AF patients. METHODS We analyzed patients who underwent successful ECV for persistent AF. Machine learning was designed to predict patients with 1-month recurrence. Individual 12-lead ECGs were collected before and after ECV. Various clinical features were collected and trained the extreme gradient boost (XGBoost)-based model. Ten-fold cross-validation was used to evaluate the performance of the model. The performance was compared to the C-statistics of the selected clinical features. RESULTS Among 718 patients (mean age 63.5±9.3 years, men 78.8%), AF recurred in 435 (60.6%) patients after 1 month. With the XGBoost-based model, the areas under the receiver operating characteristic curves (AUROCs) were 0.57, 0.60, and 0.63 if the model was trained by clinical features, ECGs, and both (the final model), respectively. For the final model, the sensitivity, specificity, and F1-score were 84.7%, 28.2%, and 0.73, respectively. Although the AF duration showed the best predictive performance (AUROC, 0.58) among the clinical features, it was significantly lower than that of the final machine-learning model (p<0.001). Additional training of extended monitoring data of 15-minute single-lead ECG and photoplethysmography in available patients (n=261) did not significantly improve the model's performance. CONCLUSIONS Machine learning showed modest performance in predicting AF recurrence after ECV in persistent AF patients, warranting further validation studies.
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Affiliation(s)
- Soonil Kwon
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea
| | - Eunjung Lee
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Hojin Ju
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea
| | - Hyo-Jeong Ahn
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea
| | - So-Ryoung Lee
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea
| | - Eue-Keun Choi
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea.
| | - Jangwon Suh
- Department of Intelligence and Information, Seoul National University, Seoul, Korea
| | - Seil Oh
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea
| | - Wonjong Rhee
- Department of Intelligence and Information, Seoul National University, Seoul, Korea.
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Atrial fibrillation detection using convolutional neural networks on 2-dimensional representation of ECG signal. Biomed Signal Process Control 2022. [DOI: 10.1016/j.bspc.2021.103470] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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Wang X, Huang C, Zhao Q, Huang H, Tang Y, Dai Z, Wang X, Guo Z, Xiao J. Effect of renal sympathetic denervation on the progression of paroxysmal atrial fibrillation in canines with long-term intermittent atrial pacing. Europace 2014; 17:647-54. [PMID: 25349225 DOI: 10.1093/europace/euu212] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2014] [Accepted: 07/03/2014] [Indexed: 11/13/2022] Open
Abstract
AIMS The aim of the present study was to explore the effect of renal sympathetic denervation (RSD) on the progression of paroxysmal atrial fibrillation (AF) in canines with long-term intermittent atrial pacing. METHODS AND RESULTS Nineteen beagles were randomly divided into sham-operated group (six dogs), control group (six dogs), and RSD group (seven dogs). Sham-operated group were implanted with pacemakers without pacing; control group were implanted with pacemakers with long-term intermittent atrial pacing; and RSD group underwent catheter-based RSD bilaterally and were simultaneously implanted with pacemakers. Atrial pacing was maintained for 8 h a day and a total of 12 weeks in the control group and RSD group. Echocardiography showed that the left atrial structure and function were significantly improved in the RSD group compared with the control group (P < 0.05). Compared with the control group, the RSD group had fewer incidences of AF and a shorter duration of AF (P < 0.05) after long-term intermittent atrial pacing. In addition to increased atrial effective refractory period (AERP) and AF cycle length, AERP dispersion and P-wave duration and dispersion were significantly decreased in the RSD group compared with the control group (P < 0.05). Atrial morphological evaluation suggested that fibrosis and ultrastructural changes induced by long-term intermittent atrial pacing were markedly suppressed in the RSD dogs compared with controls (P < 0.05). Immunohistochemistry results showed that connexin 43 distribution in RSD mid-myocardial was significantly fewer heterogeneous than that in control mid-myocardial (P < 0.05). CONCLUSION Renal denervation inhibits the progression of paroxysmal AF, which might be related to the suppression of atrial electrophysiology and structural heterogeneity.
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Affiliation(s)
- Xule Wang
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan City 430060, People's Republic of China Cardiovascular Research Institute of Wuhan University, Wuhan City 430060, People's Republic of China
| | - Congxin Huang
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan City 430060, People's Republic of China Cardiovascular Research Institute of Wuhan University, Wuhan City 430060, People's Republic of China
| | - Qingyan Zhao
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan City 430060, People's Republic of China Cardiovascular Research Institute of Wuhan University, Wuhan City 430060, People's Republic of China
| | - He Huang
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan City 430060, People's Republic of China Cardiovascular Research Institute of Wuhan University, Wuhan City 430060, People's Republic of China
| | - Yanhong Tang
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan City 430060, People's Republic of China Cardiovascular Research Institute of Wuhan University, Wuhan City 430060, People's Republic of China
| | - Zixuan Dai
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan City 430060, People's Republic of China Cardiovascular Research Institute of Wuhan University, Wuhan City 430060, People's Republic of China
| | - Xiaozhan Wang
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan City 430060, People's Republic of China Cardiovascular Research Institute of Wuhan University, Wuhan City 430060, People's Republic of China
| | - Zongwen Guo
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan City 430060, People's Republic of China Cardiovascular Research Institute of Wuhan University, Wuhan City 430060, People's Republic of China
| | - Jinping Xiao
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan City 430060, People's Republic of China Cardiovascular Research Institute of Wuhan University, Wuhan City 430060, People's Republic of China
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Hegbom F, Tveit A, Grundvold I, Arnesen H, Smith P. Effects of angiotensin receptor blockade on serial P-wave signal-averaged electrocardiograms after electrical cardioversion of persistent atrial fibrillation. Europace 2009; 11:1301-7. [DOI: 10.1093/europace/eup220] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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Automatic real time detection of atrial fibrillation. Ann Biomed Eng 2009; 37:1701-9. [PMID: 19533358 DOI: 10.1007/s10439-009-9740-z] [Citation(s) in RCA: 135] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2008] [Accepted: 06/06/2009] [Indexed: 10/20/2022]
Abstract
Atrial fibrillation (AF) is the most common sustained arrhythmia and is associated with significant morbidity and mortality. Timely diagnosis of the arrhythmia, particularly transient episodes, can be difficult since patients may be asymptomatic. In this study, we describe a robust algorithm for automatic detection of AF based on the randomness, variability and complexity of the heart beat interval (RR) time series. Specifically, we employ a new statistic, the Turning Points Ratio, in combination with the Root Mean Square of Successive RR Differences and Shannon Entropy to characterize this arrhythmia. The detection algorithm was tested on two databases, namely the MIT-BIH Atrial Fibrillation Database and the MIT-BIH Arrhythmia Database. These databases contain several long RR interval series from a multitude of patients with and without AF and some of the data contain various forms of ectopic beats. Using thresholds and data segment lengths determined by Receiver Operating Characteristic (ROC) curves we achieved a high sensitivity and specificity (94.4% and 95.1%, respectively, for the MIT-BIH Atrial Fibrillation Database). The algorithm performed well even when tested against AF mixed with several other potentially confounding arrhythmias in the MIT-BIH Arrhythmia Database (Sensitivity = 90.2%, Specificity = 91.2%).
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Nomura M, Kawano T, Nakayasu K, Nakaya Y. The effects of losartan on signal-averaged P wave in patients with atrial fibrillation. Int J Cardiol 2008; 126:21-7. [PMID: 17509704 DOI: 10.1016/j.ijcard.2007.03.106] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2006] [Revised: 01/24/2007] [Accepted: 03/25/2007] [Indexed: 11/26/2022]
Abstract
BACKGROUND Losartan has recently been reported to suppress atrial structural remodeling. However, few reports exist on signal-averaged electrocardiography (ECG) for preventing atrial electrical remodeling. We examined the effect of losartan on atrial electricity by using signal-averaged ECG of P waves. METHODS The subjects comprised 40 patients with essential hypertension complicated with symptomatic paroxysmal atrial fibrillation. The patients received pilsicainide for the complication; they were defibrillated and divided into two subgroups for antihypertensive therapy: calcium antagonist-administrated (CB) and losartan-administrated (LOS) groups. We recorded the signal-averaged electrocardiography of P waves and calculated (1) filtered P wave duration (PD), (2) the voltage integral for the entire P wave (integral-p), and (3) the root mean square voltages of the terminal 40, 30, and 20 ms (RMS-40, RMS-30, and RMS-20). Procollagen C propeptide type I (PIP) and A- and B-type natriuretic peptide (ANP and BNP, respectively) levels in the groups were measured before and after antihypertensive agent administration. RESULTS RMS-20 increased significantly and PD decreased significantly in the LOS group 24 weeks after antihypertensive drug administration; however, they remained unchanged in the CB group. Integral-p decreased significantly in both groups, and the decrease rate was significantly higher in the LOS group. Serum BNP levels decreased significantly only in the LOS group. CONCLUSIONS Losartan inhibits atrial remodeling by inhibiting left atrial fibrosis as indicated by the procollagen C propeptide type I, ANP, and BNP levels. Signal-averaged ECG demonstrated that losartan suppresses atrial fibrillation recurrence by improving atrial conduction disturbance.
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Affiliation(s)
- Masahiro Nomura
- Faculty of Integrated Arts and Science, Department of Digestive and Cardiovascular Medicine, The University of Tokushima Graduate School, The University of Tokushima, Japan.
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