12-lead Surface Electrocardiogram Research Articles

Clinical validation of the 2021 European Society of Cardiology guidelines on preexisting right bundle branch block in patients undergoing transcatheter aortic valve implantation.

Risk stratification of patients with right bundle branch block (RBBB) undergoing transcatheter aortic valve implantation (TAVI) remains challenging. This study aimed to evaluate the European Society of Cardiology (ESC) criteria for risk stratification of RBBB patients undergoing TAVI. We retrospectively analyzed prospectively enrolled patients with preexisting RBBB undergoing TAVI between 2011 and 2023. A surface 12-lead electrocardiogram was available before and after the procedure in all patients. The following ESC criteria were validated: ΔPR interval ≥20 ms, QRS axis change, and transient high-degree atrioventricular block (HAVB) <24 hours after TAVI. Preexisting RBBB was documented in 107 of 1410 patients (7.6%) undergoing TAVI. Mean age was 83 ± 5 years, 34% were female, and 66% received self-expandable valves. Of those 107 patients with preexisting RBBB, 36 (34%) had persistent HAVB lasting longer than 24 hours and received permanent pacemaker therapy. Of the remaining 71 patients, 16 patients (23%) had delayed HAVB during 30 days of follow-up. The ESC criteria identified 81% of patients (13/16) with delayed HAVB during 30-day follow-up while missing 3 patients (19%; 2.8% of the overall cohort). This resulted in a sensitivity of 81% and a negative predictive value of 92%. Meeting the ESC criteria bore a 6-fold increase in the odds for development of HAVB during 30-day follow-up (odds ratio, 6.5; 95% confidence interval, 1.84-30.8; P = .007). In this large cohort of patients with preexisting RBBB undergoing TAVI with contemporary prosthesis and implantation techniques, the ESC criteria-PR prolongation, QRS axis change, and transient HAVB-correctly identified 4 of 5 patients in whom HAVB developed during 30-day follow-up.

Clinical validation of the 2021 European Society of Cardiology guidelines on pre-existing right bundle branch block patients undergoing transcatheter aortic valve replacement

Abstract Introduction The management of patients with right bundle branch block (RBBB) undergoing transcatheter aortic valve replacement (TAVR) remains challenging. In these patients, the 2021 ESC guidelines recommend early pacemaker (PM) implantation in case of PR prolongation, QRS axis change or transient high-degree atrioventricular block (HAVB). However, evidence for the proposed criteria is scarce. Purpose Our aim was to evaluate the ESC recommendation for risk stratification of RBBB patients undergoing TAVR. Methods We retrospectively analyzed patients with pre-existing RBBB undergoing TAVR at our institution between 2011-2023. A surface 12-lead electrocardiogram (ECG) was available before and after procedure in all patients. The following, proposed ESC criteria were validated: ΔPR interval ≥ 20ms, QRS axis change or transient HAVB &amp;lt; 24 hours after TAVR. Results Of a total 1412 patients undergoing TAVR, 109 had pre-existing RBBB and were eligible for final analysis (mean age 83±5 years, 39% female). Of 109 RBBB patients, 36 (33%) developed persistent HAVB and received a permanent PM. Among the other 73 patients (67%), 17 patients (23%) suffered delayed HAVB during 30-days FU. When applying the ESC Guidelines, PM placement would have been indicated in 52% (38/73) of patients with RBBB after TAVR: due to transient HAVB in 17 (23%), due to PR prolongation ≥ 20ms in 19 (26%) and due to QRS axis change in 20 patients (27%). The proposed ESC criteria identified 82% of patients (14/17) with delayed HAVB during 30-day FU, while missing 3 patients (18%, 2.8% of overall cohort, Figure). This resulted in a sensitivity of 82% and a negative predictive value of 91%. Among the 17 patients with delayed HAVB, 12 patients (71%) displayed transient atrioventricular (AV) block within 24 hours after TAVR. Conclusion In this large cohort of RBBB patients undergoing TAVR with contemporary valves and techniques, the proposed ESC criteria of PR prolongation, QRS axis change or transient HAVB correctly identified 4/5 patients developing HAVB during 30-day FU. Prospective studies are warranted to confirm these findings.

Utility of Right-Electrocardiogram Chest Leads in Localization of Accessory Pathways in Patients with Wolf-Parkinson-White Syndrome

Abstract Background Prediction of the precise location of an Accessory Pathway (AP) prior to the ablation procedure is of clinical importance. Several algorithms have been published to localize the AP on a surface 12-lead electrocardiogram (ECG). Most of them are based on analysis of delta wave morphology or QRS polarity. However, they are somewhat complicated, and an accurate determination of the delta wave morphology or QRS polarity are occasionally difficult, and their accuracy are still limited. Recently a new published algorithm using right-sided ECG chest leads for the prediction site of an AP is figured out and still under study for measuring its accuracy. Aim of the Work The aim of this study is to evaluate the accuracy of the utility of rightsided ECG Chest leads in the localization of APs in patients with manifest pre-excitation pattern in 12-lead ECG in prospective manner. Patients and Methods This study included 35 patients in whom successful ablation of manifest Wolff-Parkinson-White (WPW) syndrome was performed in prospective manner. Standard 12-lead ECG and right-sided chest ECG waveforms were recorded before the procedure. Results There were 13, 10, and 12 patients with left, right, and septal APs, respectively. All left AP patients had type A (RS morphology) in V1 and 12 of them in V4R leads, only 1 had type B in V4R lead. Of the 10 right AP patients, 5 had type B (rS morphology) in V1 while all 10 patients had type B in V4R. Of the 12 septal AP patients, 9 had type C (QS or Qr morphology) in V1, while 2 of the 12 patients had type B, and 1 of 12 patients had type A. All the 12 septal AP patients had type C in V4R. Conclusions The QRS morphology of V1 and V4R leads could predict the site of AP in patients with WPW syndrome with overall accuracy of 85.7% and 98%, respectively. Abbreviations AP: Accessory Pathway; ECG: Electrocardiogram; EPS: Electrophysiology study; RF: Radiofrequency; WPW: Wolff-Parkinson-White

Identification of supraventricular tachycardia mechanisms with surface electrocardiograms using a convolutional neural network.

It remains difficult to definitively distinguish supraventricular tachycardia (SVT) mechanisms using a 12-lead electrocardiogram (ECG) alone. Machine learning may identify visually imperceptible changes on 12-lead ECGs and may improve ability to determine SVT mechanisms. We sought to develop a convolutional neural network (CNN) that identifies the SVT mechanism according to the gold standard of SVT ablation and to compare CNN performance against experienced electrophysiologists among patients with atrioventricular nodal re-entrant tachycardia (AVNRT), atrioventricular reciprocating tachycardia (AVRT), and atrial tachycardia (AT). All patients with 12-lead surface ECG during sinus rhythm and SVT and had successful SVT ablation from 2013 to 2020 were included. A CNN was trained using data from 1505 surface ECGs that were split into 1287 training and 218 test ECG datasets. We compared the CNN performance against independent adjudicationby 2 experienced cardiac electrophysiologists on the test dataset. Our dataset comprised 1505 ECGs (368 AVNRT, 304 AVRT, 95 AT, and 738 sinus rhythm) from 725 patients. The CNN areas under the receiver-operating characteristic curve for AVNRT, AVRT, and AT were 0.909, 0.867, and 0.817, respectively. When fixing the specificity of the CNN to the electrophysiologist adjudicators' specificity, the CNN identified all SVT classes with higher sensitivity: (1) AVNRT (91.7% vs 65.9%), (2) AVRT (78.4% vs 63.6%), and (3) AT (61.5% vs 50.0%). A CNN can be trained to differentiate SVT mechanisms from surface 12-lead ECGs with high overall performance, achieving similar performance to experienced electrophysiologists at fixed specificities.

Reentrant atrial tachycardia in a patient with arrhythmogenic right ventricular cardiomyopathy

A 59-year-old man with a diagnosis of definite ARVC without overt left ventricular involvement presented with recurrent palpitations. The surface 12-lead electrocardiogram raised the suspicion of atrial tachycardia.

Utility of the aVL Lead in the Electrocardiographic Diagnosis of Atrioventricular Nodal Re-Entrant Tachycardia

Background: Reciprocating atrioventricular tachycardia can be categorized into common slow–fast atrioventricular node re-entrant (AVNRT) and orthodromic atrioventricular reciprocating tachycardia (AVRT). The electrocardiogram (ECG) during tachycardia is useful in distinguishing these two mechanisms. The presence of a pseudo- R0-wave in lead V1 or pseudo-S-wave in the inferior leads has been widely used, although the value of an isolated aVL lead has not been evaluated yet. To determine whether an isolated aVL lead of the surface 12-lead ECG is useful for the differential diagnosis between AVNRT and AVRT. Methods: This cross sectional observational study was conducted at the department of Cardiology, National Institute of Cardiovascular Diseases &amp; Hospital, for 1-year period. Patient admitted in NICVD due to supraventricular tachycardia and was screened as a case of AVNRT &amp; AVRT were approached for inclusion of the study. After initial management all patients were subjected to perform electrophysiological study and radiofrequency ablation. The specific pattern of changes in aVL lead were recorded in each cases and were analyze to determine the sensitivity, specificity and positive predictive values to estimate AVRT &amp; AVNRT. Informed written consent was taken from the subject and ethical issues were ensured. Total 60 patients were included for final analysis. Data analysis was done by statistical program Statistical Package for Social Science (SPSS) version 20.0. Results: Among the 60 study population, mean age was 41.28±11.21 SD (years) [age range: 18-65 years]. Total 44 patients (73%) had AVNRT and 16 patients (27%) had found AVRT in Electrophysiological evaluation. About 61.7% patients were female and 38.3% patients were male in this study with no significant gender difference in between AVNRT and AVRT group (p&gt;0.05). Total 43.3% patients had aVL notch on ECG. Among patients who had AVNRT, 54.5% had aVL notch and among patients who had AVRT, 12.5% had aVL .........

Hybrid machine learning to localize atrial flutter substrates using the surface 12-lead electrocardiogram.

AimsAtrial flutter (AFlut) is a common re-entrant atrial tachycardia driven by self-sustainable mechanisms that cause excitations to propagate along pathways different from sinus rhythm. Intra-cardiac electrophysiological mapping and catheter ablation are often performed without detailed prior knowledge of the mechanism perpetuating AFlut, likely prolonging the procedure time of these invasive interventions. We sought to discriminate the AFlut location [cavotricuspid isthmus-dependent (CTI), peri-mitral, and other left atrium (LA) AFlut classes] with a machine learning-based algorithm using only the non-invasive signals from the 12-lead electrocardiogram (ECG).Methods and resultsHybrid 12-lead ECG dataset of 1769 signals was used (1424 in silico ECGs, and 345 clinical ECGs from 115 patients—three different ECG segments over time were extracted from each patient corresponding to single AFlut cycles). Seventy-seven features were extracted. A decision tree classifier with a hold-out classification approach was trained, validated, and tested on the dataset randomly split after selecting the most informative features. The clinical test set comprised 38 patients (114 clinical ECGs). The classifier yielded 76.3% accuracy on the clinical test set with a sensitivity of 89.7%, 75.0%, and 64.1% and a positive predictive value of 71.4%, 75.0%, and 86.2% for CTI, peri-mitral, and other LA class, respectively. Considering majority vote of the three segments taken from each patient, the CTI class was correctly classified at 92%.ConclusionOur results show that a machine learning classifier relying only on non-invasive signals can potentially identify the location of AFlut mechanisms. This method could aid in planning and tailoring patient-specific AFlut treatments.

C60. Management of Symptomatic Wolff-Parkinson-White (WPW) Syndrome: A Case Report

Abstract Background Atrioventricular reentrant tachycardia (AVRT) could be the reentrant tachyarrhythmia that occurs in Wolff-Parkinson-White (WPW) syndrome. In AVRT, the existence of normal AV node and accessory pathway (AP) along with the atria and ventricles establish the electrical circuit that permits impulse re-entry. The incidence of multiple accessory pathways (MAP) is reported 3-15% and incidence of sudden cardiac death (SCD) in WPW syndrome is about 0.25% per year or 3% to 4% over a lifetime. Case Description We presented a case of Wolff-Parkinson-White Syndrome. A 28-year old man was admitted for evaluation of frequent episodes of palpitation. The diagnosis of WPW syndrome was established based on the 12 lead surface electrocardiogram (ECG). Echocardiography showed normal resting echocardiography then we performed electrophysiology study (EPS). We conducted the radiofrequency ablation (RFA) to the accessory pathway (AP). The challenging point of this case was multiple accessory pathways (APs) located at right posteroseptal and left lateral. Discussion Ablation of multiple accessory pathways (MAP) had a longer fluoroscopic time and large number of unsuccessful attempts than those with a single accessory pathway. We performed RFA at right posteroseptal and left lateral accessory pathway. The radiofrequency ablation has successfully eliminated both accessory pathways. In summary, we conclude that anatomical consideration, EP study, and the ablation strategy was important to improve the safety and success rate of RFA procedure.

C60. Management of Symptomatic Wolff-Parkinson-White (WPW) Syndrome: A Case Report

Abstract Background Atrioventricular reentrant tachycardia (AVRT) could be the reentrant tachyarrhythmia that occurs in Wolff-Parkinson-White (WPW) syndrome. In AVRT, the existence of normal AV node and accessory pathway (AP) along with the atria and ventricles establish the electrical circuit that permits impulse re-entry. The incidence of multiple accessory pathways (MAP) is reported 3-15% and incidence of sudden cardiac death (SCD) in WPW syndrome is about 0.25% per year or 3% to 4% over a lifetime. Case Description We presented a case of Wolff-Parkinson-White Syndrome. A 28-year old man was admitted for evaluation of frequent episodes of palpitation. The diagnosis of WPW syndrome was established based on the 12 lead surface electrocardiogram (ECG). Echocardiography showed normal resting echocardiography then we performed electrophysiology study (EPS). We conducted the radiofrequency ablation (RFA) to the accessory pathway (AP). The challenging point of this case was multiple accessory pathways (APs) located at right posteroseptal and left lateral. Discussion Ablation of multiple accessory pathways (MAP) had a longer fluoroscopic time and large number of unsuccessful attempts than those with a single accessory pathway. We performed RFA at right posteroseptal and left lateral accessory pathway. The radiofrequency ablation has successfully eliminated both accessory pathways. In summary, we conclude that anatomical consideration, EP study, and the ablation strategy was important to improve the safety and success rate of RFA procedure.

Value of 12-lead electrocardiogram to predict myocardial scar on FDG PET in heart failure patients

PurposeA surface 12-lead electrocardiogram (ECG) is widely available, fast, inexpensive, and safe. However, its value to predict a true myocardial scar in patients with ischemic cardiomyopathy (ICM) has not been studied extensively yet. This study was conducted to assess whether Q waves on resting surface 12-lead ECG are predictive of non-viable myocardium in patients with ICM. MethodsWe analyzed resting ECGs of 149 patients with ICM undergoing cardiac positron emission tomography (PET) with 13N-ammonia (NH3) and 18F-fluorodeoxyglucose (FDG) at our institution. Pathological Q waves and QS complexes were assigned to one of three coronary artery territories and compared to the PET findings. Myocardial scar was defined as 2 or more contiguous myocardial segments with an average (matched) reduction of NH3 and FDG uptake <50% of the maximum value. ResultsPathological Q waves had a sensitivity and specificity of 70% and 40%, respectively, and a PPV and NPV of 37% and 73%, respectively, to detect myocardial scar on FDG PET. For QS complexes, sensitivity and specificity were 46% and 59%, respectively, and PPV and NPV were 36% and 68%, respectively. Sensitivity was lower, but specificity was significantly higher in both the LCX and RCA compared to the LAD territory (p<0.001), particularly for QS complexes. ConclusionPathological Q waves on resting 12-lead ECG have poor or at best moderate sensitivity and specificity to detect myocardial scar on FDG PET. These findings support the use of more advanced imaging techniques to assess myocardial viability in ICM.

Impaired left atrial strain in the presence of interatrial block in patients with type 2 diabetes mellitus.

Type 2 diabetes mellitus (T2DM) is one of the most common chronic diseases, and is a risk factor for atrial cardiomyopathy. Interatrial block (IAB), as a predictor of AF, is correlated with the extent of LA fibrosis in the process of atrial cardiomyopathy. We have not encountered any study evaluating LA and LV functions with 3D-STE in the presence of IAB in the T2DM patients. The purpose of the present study was to compare the LA and LV myocardial functions in patients with T2DM with and without IAB by 3D-STE. A total of 175 consecutive patients with T2DM who were examined at outpatient clinics were enrolled in the study (85 patients with IAB and 90 patients without IAB). Surface 12-lead standard electrocardiograms (ECGs) were recorded. Clinical characteristics and laboratory values of the patients were obtained. Conventional 2D echocardiographic and 3D-STE analyses were performed. The mean age of the patients was 59 ± 8.7 years, and 112 (64%) of the patients were female. The LAS-r and LAS-active were significantly decreased in the IAB (+) group than in the IAB (-) group. Statistically significant strong negative linear correlations were observed between P-wave duration and 3D-LA strain values. Our results indicate that there is an impairment in LA myocardial dynamics in the presence of IAB in T2DM patients. According to these findings, we can say that it will be useful to evaluate the LA functions at the preclinical stage in the presence of IAB in patients with T2DM, when considering ischemic cardiovascular and cerebral events.

Use of Artificial Intelligence and Deep Neural Networks in Evaluation of Patients With Electrocardiographically Concealed Long QT Syndrome From the Surface 12-Lead Electrocardiogram

Long QT syndrome (LQTS) is characterized by prolongation of the QT interval and is associated with an increased risk of sudden cardiac death. However, although QT interval prolongation is the hallmark feature of LQTS, approximately 40% of patients with genetically confirmed LQTS have a normal corrected QT (QTc) at rest. Distinguishing patients with LQTS from those with a normal QTc is important to correctly diagnose disease, implement simple LQTS preventive measures, and initiate prophylactic therapy if necessary. To determine whether artificial intelligence (AI) using deep neural networks is better than the QTc alone in distinguishing patients with concealed LQTS from those with a normal QTc using a 12-lead electrocardiogram (ECG). A diagnostic case-control study was performed using all available 12-lead ECGs from 2059 patients presenting to a specialized genetic heart rhythm clinic. Patients were included if they had a definitive clinical and/or genetic diagnosis of type 1, 2, or 3 LQTS (LQT1, 2, or 3) or were seen because of an initial suspicion for LQTS but were discharged without this diagnosis. A multilayer convolutional neural network was used to classify patients based on a 10-second, 12-lead ECG, AI-enhanced ECG (AI-ECG). The convolutional neural network was trained using 60% of the patients, validated in 10% of the patients, and tested on the remaining patients (30%). The study was conducted from January 1, 1999, to December 31, 2018. The goal of the study was to test the ability of the convolutional neural network to distinguish patients with LQTS from those who were evaluated for LQTS but discharged without this diagnosis, especially among patients with genetically confirmed LQTS but a normal QTc value at rest (referred to as genotype positive/phenotype negative LQTS, normal QT interval LQTS, or concealed LQTS). Of the 2059 patients included, 1180 were men (57%); mean (SD) age at first ECG was 21.6 (15.6) years. All 12-lead ECGs from 967 patients with LQTS and 1092 who were evaluated for LQTS but discharged without this diagnosis were included for AI-ECG analysis. Based on the ECG-derived QTc alone, patients were classified with an area under the curve (AUC) value of 0.824 (95% CI, 0.79-0.858); using AI-ECG, the AUC was 0.900 (95% CI, 0.876-0.925). Furthermore, in the subset of patients who had a normal resting QTc (<450 milliseconds), the QTc alone distinguished those with LQTS from those without LQTS with an AUC of 0.741 (95% CI, 0.689-0.794), whereas the AI-ECG increased this discrimination to an AUC of 0.863 (95% CI, 0.824-0.903). In addition, the AI-ECG was able to distinguish the 3 main genotypic subgroups (LQT1, LQT2, and LQT3) with an AUC of 0.921 (95% CI, 0.890-0.951) for LQT1 compared with LQT2 and 3, 0.944 (95% CI, 0.918-0.970) for LQT2 compared with LQT1 and 3, and 0.863 (95% CI, 0.792-0.934) for LQT3 compared with LQT1 and 2. In this study, the AI-ECG was found to distinguish patients with electrocardiographically concealed LQTS from those discharged without a diagnosis of LQTS and provide a nearly 80% accurate pregenetic test anticipation of LQTS genotype status. This model may aid in the detection of LQTS in patients presenting to an arrhythmia clinic and, with validation, may be the stepping stone to similar tools to be developed for use in the general population.

Comparison of clinical features and conventional echocardiographic characteristics of patients with heart failure with mid-range ejection fraction with and without interatrial block

Heart failure with mid-range ejection fraction (HFmrEF) has been proposed as a distinct heart failure (HF) phenotype. Interatrial block (IAB) is a conduction delay between the atria and is associated with cardiovascular disease. Although there are several studies examining the effect of IAB in patients with HF with reduced ejection fraction and HF with preserved ejection fraction, a literature review did not reveal any study investigating the clinical importance of the presence of IAB in patients with HFmrEF. Thus, the aim of this research was to evaluate clinical characteristics of HFmrEF with and without IAB.A total of 520 consecutive patients with HFmrEF in sinus rhythm who were examined at outpatient clinics were enrolled in the study (244 patients with IAB and 276 patients without IAB). Surface 12-lead standard electrocardiograms (ECGs) were recorded. Clinical characteristics, echocardiographic examination results, and laboratory values of the patients were recorded.The mean age of the patients was 67.4±11.1 years, and 76.1% were male. The patients with IAB had more comorbidities, including hypertension, diabetes mellitus, and stroke/transient ischemic attack. A statistically significant, strong, positive linear correlation was observed between P-wave duration and age, systolic blood pressure, and left atrial volume index (r=0.718, p<0.001; r=0.704, p<0.001; and r=0.725, p<0.001, respectively).To the best of our knowledge, the present study is the first to evaluate the clinical relevance of IAB in HFmrEF. Adding this simple ECG marker to the clinical evaluation could add significantly to the management of HFmrEF. IAB can be used to identify high-risk HFmrEF patients, as well as to guide follow-up and appropriate treatment.

Synthesis of Standard 12-lead Electrocardiograms from Asynchronous Bipolar Leads

We describe a 41-year-old man with a prior history of myocardial infarction, whose surface 12-lead electrocardiogram did not show typical left bundle-branch block pattern or wide QRS complex. However, electrophysiological study showed distinct left ventricular electrical conduction delays. The surface 12-lead electrocardiogram modified to the paper at 50 mm/s and double standard (20 mm equals 1 mV) revealed obvious notches of the terminal forces of the QRS in leads II, III, aVL, aVF, V3, V4, V5, and V6, these might be partially consistent with left ventricular electrical conduction delay in the scar lesion of the infero-posterior of the ventricle.

Deterministic Learning-Based Methodology for Detecting Abnormal Dynamics of Cardiac Repolarization During Ischemia.

This study concentrates on subtle electrocardiogram (ECG) spatiotemporal characteristics in the repolarization phase, and describes a deterministic learning-based methodology for the detection of abnormal cardiac dynamics induced by ischemia. ST-T complex of the surface 12-lead ECG signals are identified and extracted. Cardiac dynamics underlying ST-T complex signals is captured using deterministic learning algorithm. This kind of dynamics information represents the beat-to-beat temporal change of electrophysiological modifications in ventricular repolarization, which is shown to be sensitive to the variance during myocardial ischemia. Cardiodynamicsgram (CDG) is proposed as the three-dimensional graphic representation of cardiac dynamics information. Encouraging evaluation results are achieved on electrocardiograms from public PTB database and hospital patients. Significant correlations are found between the CDG morphology and ischemia. Anormal dynamics of cardiac repolarization during ischemia can be detected using a deterministic learning-based methodology. The extracted cardiac dynamics information within routine ECG is expected to provide early detection for latent ischemia before obvious pathological changes are present in ECG. The proposed techniques can be considered as a complementary tool to the generally accepted ECG method for detection of abnormal dynamics in cardiac repolarization, which are important for identifying patients at risk of myocardial ischemia.

Unusual manifestation of left ventricular electrical conduction delay on the surface 12-lead electrocardiogram in a patient with prior myocardial infarction

We describe a 41-year-old man with a prior history of myocardial infarction, whose surface 12-lead electrocardiogram did not show typical left bundle-branch block pattern or wide QRS complex. However, electrophysiological study showed distinct left ventricular electrical conduction delays. The surface 12-lead electrocardiogram modified to the paper at 50 mm/s and double standard (20 mm equals 1 mV) revealed obvious notches of the terminal forces of the QRS in leads II, III, aVL, aVF, V3, V4, V5, and V6, these might be partially consistent with left ventricular electrical conduction delay in the scar lesion of the infero-posterior of the ventricle.

Coefficient of variation of P-wave duration measured using an automated measurement system predicts recurrence of atrial fibrillation

BackgroundP-wave parameters representing atrial conduction heterogeneity are associated with recurrence of atrial fibrillation (AF) after catheter ablation. However, intra- and inter-observer variabilities are unavoidable during manual measurement of P-wave parameters. MethodsThe study included 201 patients with paroxysmal AF who underwent catheter ablation. P-wave duration (PWD) was measured using a computerized automated measurement system with a surface 12-lead electrocardiogram. The coefficient of variation of PWD (CV-PWD) across the 12 electrocardiographic leads was determined as an index of atrial conduction heterogeneity. ResultsAF did not recur in 157 (78%) patients during a 12-month follow-up period. CV-PWD assessed before catheter ablation was not different between the AF-recurrent and AF-free groups (0.069 ± 0.023 vs. 0.069 ± 0.023, P = 0.090). However, CV-PWD measured after catheter ablation was significantly larger in the AF-recurrent group than in the AF-free group (0.090 ± 0.037 vs. 0.073 ± 0.024, P < 0.001). In receiver operating curve analysis, CV-PWD assessed after catheter ablation achieved an area under the curve of 0.702; the sensitivity, specificity, and positive and negative predictive values were 68%, 69%, 38%, and 88%, respectively, for the cut-off value of 0.080. During the follow-up period, AF freedom rates of high CV-PWD patients (CV-PWD ≥ 0.080) and low CV-PWD patients (CV-PWD < 0.080) were 65% and 88%, respectively. ConclusionsCV-PWD determined using an automated measurement system was associated with AF recurrence after catheter ablation in patients with paroxysmal AF.

Prevalence of preexcitation as detected by 12 lead surface electrocardiogram of school children in Egypt

Prevalence of preexcitation as detected by 12 lead surface electrocardiogram of school children in Egypt

The effect of nebulized salbutamol on atrial electrical properties in mechanically ventilated critically ill patients - a randomized, double-blind study.

Salbutamol is a short acting beta-2 mimetic commonly used among intensive care unit patients. There are data suggesting that his mechanism of action can be a potential factor triggering arrhythmias. The aim of this study was to assess whether nebulized salbutamol causes systemic effects resulting in electrocardiographic alterations associated with atrial fibrillation occurrence in mechanically ventilated patients. 50 individuals were randomly allocated to receive either 2.5 or 5 mg of nebulized salbutamol for 20 minutes. 60 minutes prior to the start of nebulization, 12 lead surface electrocardiogram has been recorded. Electrocardiographic parameters associated with atrial activity - P wave and PR interval, and their derivates: P wave dispersion and PR interval dispersion were analysed. Both doses of inhaled salbutamol caused changes of P wave indices - maximal, minimal and mean P wave duration, from simultaneously recorded leads, and concomitant decrease of P wave dispersion. Prolongation of P wave affected predominantly minimal P wave duration (11.93 ms [95% CI: 8.69-15.17]) comparing with maximal P wave duration (2.61 [95% CI: 021-5.43]). Atrio-ventricular conduction - PR interval was also prolonged, however minimal PR interval duration from simultaneously recorded leads was shortened in group receiving 5 mg of salbutamol. Nebulized salbutamol in ICU patient possess systemic effects which causes changes in P wave indices in surface ECG recordings. This electrophysiological influence may be associated with the increased risk of atrial fibrillation among this group of patients.

1361Paroxysmal versus persistent atrial fibrillation: predictive benefit from 10 seconds of surface 12-lead electrocardiogram

1361Paroxysmal versus persistent atrial fibrillation: predictive benefit from 10 seconds of surface 12-lead electrocardiogram