Hermans, Ben

Laureanti, Rita

Schotten, Ulrich

Zeemering, Stef

Zink, Matthias

English

KITopen

The Extended ECG Improves Classification of Atrial FibrillationType and Prediction of Recurrence after Catheter AblationStef Zeemering1, Matthias Zink1,2, Ben Hermans1, Rita Laureanti3, and Ulrich Schotten11Cardiovascular Research Institute Maastricht (CARIM), Physiology, Maastricht, the Netherlands2University Hospital RWTH Aachen, Department of Internal Medicine 1-Cardiology, Aachen, Germany3Politecnico di Milano, Department of Electronics, Information and Bioengineering, Milano, ItalyBackgroundThe standard 10-second 12-lead electrocardio-gram (ECG) is the default tool to diagnose ongo-ing atrial fibrillation (AF). Suboptimal lead place-ment to capture atrial conduction properties andshort recording length may however limit its useas a tool to classify AF complexity and predicttreatment outcome.ObjectiveWe investigated the added value of features de-rived from an extended ECG (eECG) with ad-ditional atrial-specific lead locations and longerrecording length, when classifying AF type andpredicting AF recurrence after catheter ablation,compared to features derived from the standardECG.MethodsECGs with 3 additional atrial leads, 5-minuteduration, and 500 Hz sampling frequency, wererecorded in 242 patients before catheter ablationof AF, during sinus rhythm (SR, n=159) or AF(n=83). In SR features of the signal averagedP-wave (amplitude, area, entropy, and complex-ity) and beat-to-beat P-wave variability were com-puted. In AF F-wave features (dominant fre-quency, spectral organization index and entropy,amplitude, and variability) were determined. P-and F-wave features were used to classify AF type(paroxysmal or persistent AF) and to predict AFrecurrence within 1 year after ablation. Classi-fication and prediction models were constructedusing feature selection (elastic net logistic regres-sion) and performance (area under the receiver op-eration characteristics curve, AUC) was comparedto models restricted to features that could be de-rived from a standard 10-second 12-lead ECG.ResultsClassification of paroxysmal/persistent AF usingSR ECGs (n=119/40 respectively) was improvedby using eECG P-wave features compared to stan-dard features (median AUC 0.76 vs 0.58, p <0.001, using P-wave amplitude, entropy, complex-ity, and variability), also after correcting for clini-cal characteristics. In AF ECGs a small improve-ment in classification of AF type (n=30/53) wasobserved when comparing standard and eECGmodels that corrected for clinical characteristics(AUC 0.74 vs 0.71, p < 0.01, using F-wave ampli-tude, variability, and weight). Follow-up of atrialrhythm after ablation was available in 161 pa-tients (SR ECG: n=110, 32 AF recurrences; AFECG: n=51, 31 recurrences). Prediction perfor-mance of recurrence after ablation was poor usingstandard P-wave features but improved by usingeECG features (AUC 0.60 vs 0.70, p < 0.001, us-ing P-wave entropy and complexity), and furtherincreased when complemented by clinical charac-teristics (AUC 0.81, p < 0.001 compared to eECGmodel, using AF type). Both standard and eECGF-wave features prediction models performed well(AUC 0.75 vs 0.78, p=0.06, using dominant fre-quency and organization index). Performance in-creased by adding clinical characteristics (AUC0.81 and 0.83, using history of vascular disease).DiscussionP- and F-wave features of the extended ECG en-able moderate to good classification of paroxysmalversus persistent AF and prediction of AF recur-rence after catheter ablation. The extended ECGsignificantly improved classification or predictionperformance with respect to a standard 10-second12-lead ECG.doi:10.5445/IR/1000138464 Atrial Signals 2021 Proceedings 17

The Extended ECG Improves Classification of Atrial Fibrillation Type and Prediction of Recurrence after Catheter Ablation. Abstract

https://publikationen.bibliothek.kit.edu/1000138464/130453732

The Extended ECG Improves Classification of Atrial Fibrillation Type and Prediction of Recurrence after Catheter Ablation. Abstract

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