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Related Concept Videos

Electrocardiogram01:29

Electrocardiogram

5.3K
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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Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

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Introduction
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...
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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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Imaging Studies for Cardiovascular System I:Echocardiography01:17

Imaging Studies for Cardiovascular System I:Echocardiography

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Cardiac imaging studies encompass a wide range of noninvasive and minimally invasive techniques designed to visualize the heart's structure and function in detail. One such technique is echocardiography, which uses high-frequency ultrasound waves to produce detailed images of the heart, known as echocardiograms.
Indications: Echocardiography is utilized to diagnose heart failure, valve disorders, and myocardial infarction. It also assesses cardiac structures' size, shape, and motion,...
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Acute Coronary Syndrome III: Diagnostic Studies01:30

Acute Coronary Syndrome III: Diagnostic Studies

207
Diagnosing acute coronary syndrome or ACS begins with a thorough patient history. Notable symptoms include central, crushing chest pain radiating to the left arm, neck, jaw, or back, along with shortness of breath, sweating (diaphoresis), nausea, vomiting, dizziness, and palpitations.It is crucial to note any history of cardiac illnesses and assess risk factors, including age, gender, smoking, hypertension, diabetes, hyperlipidemia, and a sedentary lifestyle.During physical examination, vital...
207
Dysrhythmias V: Evaluating Dysrhythmias01:30

Dysrhythmias V: Evaluating Dysrhythmias

323
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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Related Experiment Video

Updated: Jan 13, 2026

Evaluation of Left Ventricular Structure and Function using 3D Echocardiography
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Evaluation of Left Ventricular Structure and Function using 3D Echocardiography

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Cumulative electrocardiogram abnormalities predict left ventricular ejection fraction reduction: EchoNext database

Solomon Kim1, Beshoy Saad1, Gary Chu2

  • 1California Northstate University College of Medicine, Elk Grove, CA, USA.

Journal of Electrocardiology
|January 9, 2026
PubMed
Summary
This summary is machine-generated.

Combining continuous electrocardiogram (ECG) parameters like QRS duration and QT interval (QTc) improves prediction of reduced left ventricular ejection fraction (LVEF) over single measures. However, missing data may underestimate the true predictive power of these ECG markers.

Keywords:
Diagnostic testingEjection fractionElectrocardiogramPredictive modelingQRS durationRisk assessmentSystolic dysfunction

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Area of Science:

  • Cardiology
  • Medical Informatics
  • Biostatistics

Background:

  • Individual electrocardiographic (ECG) abnormalities are linked to reduced left ventricular ejection fraction (LVEF).
  • The synergistic predictive value of multiple continuous ECG parameters versus single parameters or binary scoring for LVEF is not fully understood.

Purpose of the Study:

  • To evaluate the predictive value of combined continuous ECG parameters (QRS duration, PR interval, heart rate-corrected QT interval - QTc) for reduced LVEF.
  • To compare the predictive performance of a multi-parameter continuous ECG model against individual ECG parameters and binary scoring methods.

Main Methods:

  • Analysis of 89,630 paired ECG-echocardiogram studies from the EchoNext database.
  • Development and evaluation of seven logistic regression models using training (70%) and validation (30%) sets, adjusted for age and sex.
  • Models were assessed using bootstrap confidence intervals and 5-fold stratified cross-validation, with systematic evaluation of missing data patterns.

Main Results:

  • The full continuous ECG model showed fair discrimination (AUC 0.710) compared to QTc alone (AUC 0.695).
  • QTc had the strongest individual association (AUC 0.695), followed by QRS duration (AUC 0.673) and PR interval (AUC 0.603).
  • Prevalence of LVEF ≤45% increased significantly with the number of ECG abnormalities (p < 0.001).

Conclusions:

  • Combined continuous ECG parameters offer enhanced predictive value for reduced LVEF compared to individual parameters or binary classifications.
  • Significant selection bias due to non-random missing data suggests that the observed associations likely underestimate the true predictive power.