B-PO03-123 RELATION BETWEEN PREMATURE VENTRICULAR CONTRACTION ORIGIN, UNDERLYING HEART DISEASE AND ABLATION OUTCOME

Ice pick headache is a momentary, transient, repetitive headache disorder and manifests with the stabbing pains and jolts. The exact mechanism causing this disease is unknown. Premature ventricular contractions are early depolarization of the ventricular myocardium and in the absence of a structural heart disease, it is considered to be a benign disease. In this report, we describe a male patient presenting with the symptom of momentary headache attacks accompanied with instant chest pain which is associated with premature ventricular contraction.

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Long-term Prognosis for Non-ischemic Heart Disease Patients with Premature Ventricular Contraction and Non-sustained Ventricular Tachycardia

Journal of Arrhythmia ◽

10.1016/s1880-4276(08)80003-8 ◽

2008 ◽

Vol 24 (1) ◽

pp. 18-25

Author(s):

Masakazu Komoriya ◽

Shinobu Imai ◽

Hiroshi Aoyama ◽

Hideki Yagi ◽

Masaaki Nagashima ◽

...

Keyword(s):

Heart Disease ◽

Ventricular Tachycardia ◽

Ischemic Heart Disease ◽

Premature Ventricular Contraction ◽

Sustained Ventricular Tachycardia ◽

Ischemic Heart ◽

Ventricular Contraction ◽

Long Term Prognosis

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QT variability paradox after premature ventricular contraction in patients with structural heart disease and ventricular arrhythmias

Journal of Electrocardiology ◽

10.1016/j.jelectrocard.2012.07.016 ◽

2012 ◽

Vol 45 (6) ◽

pp. 652-657 ◽

Cited By ~ 5

Author(s):

Durgesh Das ◽

Lichy Han ◽

Ronald D. Berger ◽

Larisa G. Tereshchenko

Keyword(s):

Heart Disease ◽

Ventricular Arrhythmias ◽

Premature Ventricular Contraction ◽

Structural Heart Disease ◽

Ventricular Contraction ◽

Qt Variability

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CARDIAC AFFERENT SIGNALING PARTIALLY UNDERLIES PREMATURE VENTRICULAR CONTRACTION-INDUCED CARDIOMYOPATHY

Journal of the American College of Cardiology ◽

10.1016/s0735-1097(21)01938-0 ◽

2021 ◽

Vol 77 (18) ◽

pp. 579

Author(s):

Yuichi Hori ◽

Taro Temma ◽

Christian Wooten ◽

Christopher O Sobowale ◽

Christopher Chan ◽

...

Keyword(s):

Premature Ventricular Contraction ◽

Ventricular Contraction ◽

Afferent Signaling

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Robust deep learning pipeline for PVC beats localization

Technology and Health Care ◽

10.3233/thc-218045 ◽

2021 ◽

Vol 29 ◽

pp. 475-486

Author(s):

Bohdan Petryshak ◽

Illia Kachko ◽

Mykola Maksymenko ◽

Oles Dobosevych

Keyword(s):

Neural Networks ◽

Deep Learning ◽

Premature Ventricular Contraction ◽

Ecg Signal ◽

Ventricular Contraction ◽

Localization Task ◽

Robust Performance ◽

Extensive Evaluation ◽

Decoder Architecture ◽

Public Datasets

BACKGROUND: Premature ventricular contraction (PVC) is among the most frequently occurring types of arrhythmias. Existing approaches for automated PVC identification suffer from a range of disadvantages related to hand-crafted features and benchmarking on datasets with a tiny sample of PVC beats. OBJECTIVE: The main objective is to address the drawbacks described above in the proposed framework, which takes a raw ECG signal as an input and localizes R peaks of the PVC beats. METHODS: Our method consists of two neural networks. First, an encoder-decoder architecture trained on PVC-rich dataset localizes the R peak of both Normal and anomalous heartbeats. Provided R peaks positions, our CardioIncNet model does the delineation of healthy versus PVC beats. RESULTS: We have performed an extensive evaluation of our pipeline with both single- and cross-dataset paradigms on three public datasets. Our approach results in over 0.99 and 0.979 F1-measure on both single- and cross-dataset paradigms for R peaks localization task and above 0.96 and 0.85 F1 score for the PVC beats classification task. CONCLUSIONS: We have shown a method that provides robust performance beyond the beats of Normal nature and clearly outperforms classical algorithms both in the case of a single and cross-dataset evaluation. We provide a Github1 repository for the reproduction of the results.

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