Related Experiment Video
Updated: Feb 26, 2026
Electrophysiological Assessment of Murine Atria with High-Resolution Optical Mapping
Published on: February 22, 2018
Localization Of Accessory Pathway In Patients With Wolff-Parkinson-White Syndrome From Surface Ecg Using Arruda
Shahab Saidullah1, Bakhtawar Shah2, Hameed Ullah2
1Department of Cardiology, Pakistan Institute of Medical Sciences (PIMS), Islamabad, Pakistan.
Background:
To ablate accessory pathway successfully and conveniently, accurate localization of the pathway is needed. Electrophysiologists use different algorithms before taking the patients to the electrophysiology (EP) laboratory to plan the intervention accordingly. In this study, we used Arruda algorithm to locate the accessory pathway. The objective of the study was to determine the accuracy of the Arruda algorithm for locating the pathway on surface ECG.
Methods:
It was a cross-sectional observational study conducted from January 2014 to January 2016 in the electrophysiology department of Hayat Abad Medical Complex Peshawar Pakistan. A total of fifty nine (n=59) consecutive patients of both genders between age 14-60 years presented with WPW syndrome (Symptomatic tachycardia with delta wave on surface ECG) were included in the study. Patient's electrocardiogram (ECG) before taking patients to laboratory was analysed on Arruda algorithm. Standard four wires protocol was used for EP study before ablation. Once the findings were confirmed the pathway was ablated as per standard guidelines.
Results:
A total of fifty nine (n=59) patients between the age 14-60 years were included in the study. Cumulative mean age was 31.5 years±12.5 SD. There were 56.4% (n=31) males with mean age 28.2 years±10.2 SD and 43.6% (n=24) were females with mean age 35.9 years±14.0 SD. Arruda algorithm was found to be accurate in predicting the exact accessory pathway (AP) in 83.6% (n=46) cases. Among all inaccurate predictions (n=9), Arruda inaccurately predicted two third (n=6; 66.7%) pathways towards right side (right posteroseptal, right posterolateral and right antrolateral).
Conclusions:
Arruda algorithm was found highly accurate in predicting accessory pathway before ablation.
More Related Videos
06:07Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice
Published on: May 23, 2021
06:57Ablation of Ischemic Ventricular Tachycardia Using a Multipolar Catheter and 3-dimensional Mapping System for High-density Electro-anatomical Reconstruction
Published on: January 31, 2019
Related Concept Videos
01:25ECG Interpretation of Arrhythmias II: Atrial, Junctional and Ventricular Arrhythmias
01:28Electrocardiogram Fundamentals
An electrocardiogram (ECG) is a diagnostic tool for identifying cardiac conditions such as arrhythmias, conduction abnormalities, and myocardial ischemia.
Definition
An electrocardiogram (ECG) visualizes the heart's electrical activity by tracing the electrical movement associated with each heartbeat on a graph or monitor. As the heart beats, an electrical wave passes through it, correlating with the cardiac cycle events.
Parts of an ECG
An ECG utilizes electrodes on the skin...
01:16ECG Interpretation of Arrhythmias I: Sinus Arrhythmias
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,...
01:29Electrocardiogram
Three major waveforms are present in a typical ECG recording: the P wave, the QRS complex, and...
01:25Correlation between ECG and 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...
01:28Dysrhythmias II: Classification of Tachyarrhythmias