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Related Concept Videos

Electrocardiogram01:29

Electrocardiogram

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An electrocardiogram (ECG or EKG) is a critical diagnostic tool that records the electrical signals produced by the heart during each heartbeat. This recording is achieved through electrodes placed strategically on the arms, legs, and chest. The electrocardiograph amplifies these signals and produces 12 distinct tracings, offering a comprehensive understanding of the heart's electrical activity.
Three major waveforms are present in a typical ECG recording: the P wave, the QRS complex, and...
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ECG Interpretation of Arrhythmias II: Atrial, Junctional and Ventricular Arrhythmias01:25

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Arrhythmia is a condition characterized by an irregular heart rhythm, with ECG changes that differ based on its origin and nature. The types of arrhythmias discussed below include atrial, junctional, and ventricular arrhythmias.Atrial ArrhythmiasPremature Atrial Complexes (PACs): PACs are early atrial beats caused by stress, caffeine, alcohol, electrolyte imbalances, hypoxia, hyperthyroidism, or certain medications (e.g., bronchodilators and decongestants). The ECG shows early P waves with an...
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Pulse rhythm01:30

Pulse rhythm

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Pulse rhythm refers to the pattern of pulsations within specific intervals, offering valuable insights into the regularity or irregularity of the heart's beats as observed through the pattern of pulsation within specific intervals. A regular pulse exhibits a consistent heart rate with uniform waveforms and pulsation force, variations of which can be classified as normal, weak, or bounding.
Conversely, an irregular pulse pattern is termed dysrhythmia, stemming from disruptions in cardiac...
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ECG Interpretation of Arrhythmias I: Sinus Arrhythmias01:16

ECG Interpretation of Arrhythmias I: Sinus Arrhythmias

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Arrhythmias are disturbances in the heart's rhythm that lead to abnormal heartbeats. These irregularities can originate from different parts of the heart and are classified based on their origin and nature.
Types of Arrhythmias
Sinus Node Arrhythmias
Sinus Bradycardia: Originating from the sinoatrial (SA) node, sinus bradycardia involves slower impulses, resulting in a heart rate of less than 60 beats per minute (bpm). Causes include sleep, vagal stimulation, beta-blockers, hypothyroidism,...
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Correlation between ECG and Cardiac Cycle01:25

Correlation between ECG and Cardiac Cycle

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The electrical signals recorded on an electrocardiogram (ECG) occur before the mechanical processes of contraction and relaxation during the cardiac cycle.
A cardiac action potential originates in the SA node and spreads throughout the atria and the AV node in approximately 0.03 seconds. This results in the P wave in an ECG and triggers atrial contraction. The action potential is then briefly slowed at the AV node, allowing the atria to contract and fill the ventricles with blood before...
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Dysrhythmias V: Evaluating Dysrhythmias01:30

Dysrhythmias V: Evaluating Dysrhythmias

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Dysrhythmias, also known as arrhythmias, are disturbances in the heart's rhythm that range from benign to life-threatening. A thorough evaluation is crucial for appropriate management and involves a comprehensive medical history, physical examination, and various diagnostic tests.Medical HistorySymptoms: Collect detailed information on palpitations, dizziness, syncope, chest pain, and fatigue. Note their onset, frequency, and triggers.Previous Cardiac Issues: Document any history of heart...
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Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice
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Prediction of Sinus Rhythm Maintenance After Electrical Cardioversion Using Spectral and Vector Cardiographic ECG

Sabri Hassouna1, Marek Hozman1, Dalibor Heřman1

  • 1Cardiocenter, Third Faculty of Medicine, Charles University and University Hospital Kralovske Vinohrady, Prague, Czech Republic.

Annals of Noninvasive Electrocardiology : the Official Journal of the International Society for Holter and Noninvasive Electrocardiology, Inc
|August 15, 2025
PubMed
Summary

Predicting atrial fibrillation (AF) recurrence after electrical cardioversion (ECV) is improved by combining spectral analysis of AF activity and vector cardiographic (VCG) analysis of ECGs. This combined approach offers more accurate predictions for maintaining sinus rhythm (SR) post-treatment.

Keywords:
atrial fibrillationelectrical cardioversionprediction of sinus rhythmspectral and vectorcardiographic analysis

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Methods for ECG Evaluation of Indicators of Cardiac Risk, and Susceptibility to Aconitine-induced Arrhythmias in Rats Following Status Epilepticus
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Area of Science:

  • Cardiology
  • Medical Imaging
  • Signal Processing

Background:

  • Electrical cardioversion (ECV) is a treatment for atrial fibrillation (AF).
  • Predicting successful maintenance of sinus rhythm (SR) after ECV is crucial for patient management.
  • Existing prediction methods may not fully capture the complexities of AF dynamics and ventricular activity.

Purpose of the Study:

  • To identify predictors of sustained SR maintenance following ECV for AF.
  • To evaluate the predictive power of spectral analysis of AF activity and vector cardiographic (VCG) analysis of ECGs.
  • To determine if combining these analyses improves prediction accuracy compared to individual methods.

Main Methods:

  • Prospective enrollment of 80 consecutive patients with AF undergoing elective ECV.
  • Analysis of pre-ECV ECGs using spectral analysis (dominant frequency, regularity index, organizational index) and VCG (dXmean, dYmean, dZmean).
  • Lasso Logistic Regression (LLR) with five-fold cross-validation for feature selection and model building, using a 60%-40% train-test split.

Main Results:

  • At 3-month follow-up, 45% of patients experienced AF recurrence.
  • The best single predictor was dZMean from VCG (OR 0.18, p < 0.001), yielding an AUC of 0.78.
  • Spectral analysis's best predictor was Dominant Frequency (DF) (OR 3.54, p = 0.006), with spectral features achieving an AUC of 0.76.
  • Combining VCG and spectral features in an LLR model resulted in the highest AUC of 0.79.
  • Clinical features did not prove to be significant predictors in the models.

Conclusions:

  • The combination of spectral analysis of AF activity and VCG analysis of ventricular activity significantly enhances the prediction of SR maintenance after ECV.
  • This integrated analytical approach provides superior predictive accuracy compared to using either spectral or VCG analysis alone.
  • The findings suggest a more robust method for identifying patients likely to maintain SR post-cardioversion.