Theo Lankveld

The ECG as a tool to determine atrial fibrillation complexity

The use of the ECG for atrial fibrillation (AF) in clinical daily practice is still limited to its diagnosis. Recent research shows however that ECG-derived parameters can also be used to assess the spatiotemporal properties of AF. Specifically, the complexity of the f-waves in the ECG reflects the complexity of the fibrillatory conduction during AF and therefore can be used for quantification of the degree of electrophysiological alterations in the atria. This information might be useful for guiding AF therapy and might form the basis for classification of AF. This review focuses on technical and mathematical aspects of ECG-based atrial complexity assessment and its potential ability to guide treatment strategies.

Atrial Fibrillation Complexity Parameters Derived From Surface ECGs Predict Procedural Outcome and Long-Term Follow-Up of Stepwise Catheter Ablation for Atrial Fibrillation

Background—The success rate of catheter ablation for persistent atrial fibrillation (AF) is still far from satisfactory. Identification of patients who will benefit from ablation is highly desirable. We investigated the predictive value of noninvasive AF complexity parameters derived from standard 12-lead ECGs for AF termination and long-term success of catheter ablation and compared them with clinical predictors. Methods and Results—The study included a training (93 patients) and a validation set (81 patients) of patients with persistent AF undergoing stepwise radiofrequency ablation. In the training set AF terminated in 81% during catheter ablation, 77% were in sinus rhythm after 6 years and multiple ablations. ECG-derived complexity parameters were determined from a baseline 10-s 12-lead ECG. Prediction of AF termination was similar using only ECG (cross-validated mean area under the curve [AUC], 0.76±0.15) or only clinical parameters (mean AUC, 0.75±0.16). The combination improved prediction to a mean AUC of 0.79±0.13. Using a combined model of ECG and clinical parameters, sinus rhythm at long-term follow-up could be predicted with a mean AUC of 0.71±0.12. In the validation set AF terminated in 57%, 61% were in sinus rhythm after 4.6 years. The combined models predicted termination with an AUC of 0.70 and sinus rhythm at long-term follow-up with an AUC of 0.61. Overall, fibrillation-wave amplitude provided the best rhythm prediction. Conclusions—The predictive performance of ECG-derived AF complexity parameters for AF termination and long-term success of catheter ablation in patients with persistent AF is at least as good as known clinical predictive parameters, with fibrillation-wave amplitude as the best predictor.

Systematic analysis of ECG predictors of sinus rhythm maintenance after electrical cardioversion for persistent atrial fibrillation

BACKGROUND Electrical cardioversion (ECV) is one of the rhythm control strategies in patients with persistent atrial fibrillation (AF). Unfortunately, recurrences of AF are common after ECV, which significantly limits the practical benefit of this treatment in patients with AF. OBJECTIVES The objectives of this study were to identify noninvasive complexity or frequency parameters obtained from the surface electrocardiogram (ECG) to predict sinus rhythm (SR) maintenance after ECV and to compare these ECG parameters with clinical predictors. METHODS We studied a wide variety of ECG-derived time- and frequency-domain AF complexity parameters in a prospective cohort of 502 patients with persistent AF referred for ECV. RESULTS During 1-year follow-up, 161 patients (32%) maintained SR. The best clinical predictor of SR maintenance was antiarrhythmic drug (AAD) treatment. A model including clinical parameters predicted SR maintenance with a mean cross-validated area under the receiver operating characteristic curve (AUC) of 0.62 ± 0.05. The best single ECG parameter was the dominant frequency (DF) on lead V6. Combining several ECG parameters predicted SR maintenance with a mean AUC of 0.64 ± 0.06. Combining clinical and ECG parameters improved prediction to a mean AUC of 0.67 ± 0.05. Although the DF was affected by AAD treatment, excluding patients taking AADs did not significantly lower the predictive performance captured by the ECG. CONCLUSION ECG-derived parameters predict SR maintenance during 1-year follow-up after ECV at least as good as known clinical predictors of rhythm outcome. The DF proved to be the most powerful ECG-derived predictor.

The electrocardiogram as a predictor of successful pharmacological cardioversion and progression of atrial fibrillation

Aims Non-invasive characterization of atrial fibrillation (AF) substrate complexity based on the electrocardiogram (ECG) may improve outcome prediction in patients receiving rhythm control therapies for AF. Multiple parameters to assess AF complexity and predict treatment outcome have been suggested. A comparative study of the predictive performance of complexity parameters on response to therapy and progression of AF in a large patient population is needed to standardize non-invasive analysis of AF. Methods and results A large variety of ECG complexity parameters were systematically compared in patients with recent onset AF undergoing pharmacological cardioversion (PCV) with flecainide. Parameters were computed on 10-s 12-lead ECGs of 221 patients before drug administration. The ability of ECG parameters to predict successful PCV and progression to persistent AF (mean follow-up 49 months) was evaluated and compared with common clinical predictors. Optimal prediction performance of successful PCV using only one ECG parameter was low, using dominant atrial frequency [lead II, receiver operating area under curve (AUC) 0.66, 95% confidence interval [0.64-0.67]], but the optimal combination of several ECG parameters strongly improved predictive performance (AUC 0.78 [0.76-0.79]). While predictive value of the optimal combination of clinical predictors was low (AUC 0.68 [0.66-0.70], using right atrial volume and weight), adding ECG parameters strongly increased performance (AUC 0.81 [0.79-0.82], P < 0.001). Interestingly, higher dominant frequency and higher f-wave amplitude were associated with increased risk of progression to persistent AF during follow-up. Conclusion Assessment of AF complexity from 12-lead ECGs significantly improves prediction of successful PCV and progression to persistent AF compared with common clinical and echocardiographic predictors.

P-wave complexity in normal subjects and computer models

BACKGROUND P waves reported in electrocardiology literature uniformly appear smooth. Computer simulation and signal analysis studies have shown much more complex shapes. OBJECTIVE We systematically investigated P-wave complexity in normal volunteers using high-fidelity electrocardiographic techniques without filtering. METHODS We recorded 5-min multichannel ECGs in 16 healthy volunteers. Noise and interference were reduced by averaging over 300 beats per recording. In addition, normal P waves were simulated with a realistic model of the human atria. RESULTS Measured P waves had an average of 4.1 peaks (range 1-10) that were reproducible between recordings. Simulated P waves demonstrated similar complexity, which was related to structural discontinuities in the computer model of the atria. CONCLUSION The true shape of the P wave is very irregular and is best seen in ECGs averaged over many beats.

Left atrial dyssynchrony time measured by tissue Doppler imaging to predict atrial fibrillation recurrences after pulmonary vein isolation: is this a mirage or the panacea?

and Cardiovascular Research Institute Maastricht, P. Debyelaan 25, PO Box 5800, 6229 HX Maastricht, 6202AZ, Maastricht-The Netherlands Phone: +31 43 3877070 Fax: +31-43-3875104 E-mail: drnarendra007kr@gmail.com Accepted Date: 25.10.2014 Available Online Date: 21.01.2015 ©Copyright 2015 by Turkish Society of Cardiology Available online at www.anakarder.com DOI:10.5152/akd.2015.14399 Editorial Comment

Poor anticoagulation relates to extended access times for cardioversion and is associated with long-term major cardiac and cerebrovascular events

BACKGROUND Patients undergoing elective electrical cardioversion (ECV) for atrial fibrillation have a temporarily increased risk of thromboembolism. Current guidelines recommend adequate anticoagulation for ≥3 consecutive weeks precardioversion, i.e. consecutive INR values 2.0-3.0 in patients with vitamin K antagonists (VKA). We aimed to evaluate the occurrence and impact of subtherapeutic INRs precardioversion and to study factors associated with these unwanted fluctuations. METHODS We recruited 346 consecutive patients undergoing elective ECV in the Maastricht University Medical Centre between 2008 and 2013. Predictors of subtherapeutic INR values were identified and incorporated into a logistic regression model. RESULTS A subtherapeutic INR precardioversion occurred in 55.2% of patients. The only statistically significant predictor was VKA-naivety (Odds Ratio (OR) 4.78, 95% Confidence Interval (CI) 2.67-8.58, p<0.001). In patients with ≥1 subtherapeutic INR precardioversion, time from referral until cardioversion was 91.1±42.8days, compared to 41.7±26.6days (p<0.001) in patients without subtherapeutic INRs. No thromboembolic events occurred <30days after the ECV. Independent predictors for the combined endpoint of cardiovascular death, ischemic stroke and the need of blood transfusion (n=30, median follow-up of 374days) were coronary artery disease in the history (OR 3.35, 95%CI 1.54-7.25, p=0.002) and subtherapeutic INR precardioversion (OR 3.64, 95%CI 1.43-9.24, p=0.007). CONCLUSIONS The use of VKA often results in subtherapeutic INRs precardioversion and is associated with a significant delay until cardioversion, especially in patients with recent initiation of VKA therapy. Furthermore, subtherapeutic INR levels prior to ECV are associated with the combined endpoint of cardiovascular death, ischemic stroke and the need of blood transfusion.