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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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Tachyarrhythmias are a type of dysrhythmia where the heart rate exceeds 100 beats per minute. Here are some common types of tachyarrhythmias:Sinus TachycardiaSinus tachycardia originates from increased impulses from the sinus node, leading to an elevated heart rate. It is often triggered by stress, fever, or exercise.Patients may experience palpitations, a sensation of a racing heart, dizziness, and chest discomfort.Causes and Risk Factors: Common causes include physical exertion, emotional...
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Related Experiment Video

Updated: Mar 17, 2026

Catheter Ablation in Combination With Left Atrial Appendage Closure for Atrial Fibrillation
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Simple predictors for new onset atrial fibrillation.

Sandra Cabrera1, Ermengol Vallès1, Begoña Benito1

  • 1Electrophysiology Unit, Department of Cardiology, Hospital del Mar, Universitat Autònoma de Barcelona, Barcelona, Spain; Heart Diseases Biomedical Research Group, IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.

International Journal of Cardiology
|July 15, 2016
PubMed
Summary

Predicting new onset atrial fibrillation (NOAF) is challenging. Simple clinical, ECG, and Holter data effectively predict NOAF, aiding targeted monitoring.

Keywords:
Atrial fibrillationHolter monitoringRisk calculator

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Area of Science:

  • Cardiology
  • Electrocardiography
  • Predictive Analytics

Background:

  • Predicting new onset atrial fibrillation (NOAF) remains a significant clinical challenge.
  • Few studies have utilized 24-hour Holter monitoring characteristics for NOAF prediction.

Purpose of the Study:

  • To identify simple predictors for new onset atrial fibrillation (NOAF).
  • To develop and validate a risk calculator for NOAF prediction.

Main Methods:

  • A cohort of 299 patients undergoing Holter monitoring (excluding prior AF) was analyzed.
  • Univariate and multivariate analyses identified independent predictors of NOAF.
  • A risk calculator was developed and validated in an independent cohort of 200 patients.

Main Results:

  • The incidence of NOAF was 10.4% over a median follow-up of 39.1 months.
  • Independent predictors included age, heart failure/cardiomyopathy, premature atrial complexes (PACs) ≥0.2%, and PR interval.
  • The validated risk calculator demonstrated good discrimination (AUC 0.794 at 2 and 3 years).

Conclusions:

  • Clinical, ECG, and Holter parameters can effectively predict NOAF in a diverse patient population.
  • These predictors may guide more intensive monitoring strategies for individuals at risk of atrial fibrillation.