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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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Cardiopulmonary Resuscitation III: AED Use01:23

Cardiopulmonary Resuscitation III: AED Use

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Introduction to AEDAn Automated External Defibrillator (AED) is a portable medical device that analyzes the heart's rhythm and, if necessary, delivers an electrical shock to help the heart re-establish an effective rhythm during sudden cardiac arrest (SCA). SCA occurs when the heart suddenly and unexpectedly stops beating, leading to a loss of blood flow to the brain and other vital organs. In such emergencies, time is of the essence, and using an AED, combined with Cardiopulmonary...
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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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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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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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Artificial intelligence-enabled electrocardiogram for mortality and cardiovascular risk estimation: a model

Arunashis Sau1, Libor Pastika2, Ewa Sieliwonczyk3

  • 1National Heart and Lung Institute, Imperial College London, London, UK; Department of Cardiology, Imperial College Healthcare NHS Trust, London, UK.

The Lancet. Digital Health
|October 25, 2024
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI)-enabled electrocardiography (ECG) can predict mortality risk. The new AI-ECG risk estimator (AIRE) platform provides actionable, explainable, and biologically plausible predictions for individual patients.

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Area of Science:

  • Cardiology
  • Artificial Intelligence
  • Medical Informatics

Background:

  • Artificial intelligence (AI)-enabled electrocardiography (ECG) shows promise for predicting future disease and mortality.
  • Current AI-ECG models lack individual patient actionability, explainability, and biological plausibility.
  • The AI-ECG risk estimator (AIRE) platform was developed to address these limitations.

Purpose of the Study:

  • To develop an AI-ECG platform (AIRE) that provides actionable, explainable, and biologically plausible risk predictions.
  • To predict not only the risk of mortality but also the time-to-mortality using a single ECG.
  • To validate the AIRE platform across diverse, transnational patient cohorts.

Main Methods:

  • The AIRE platform was developed using deep learning and a discrete-time survival model on a large secondary care dataset (1,163,401 ECGs from 189,539 patients).
  • AIRE was validated in five diverse, transnational cohorts, including volunteers, primary care, and secondary care patients.
  • Phenome-wide and genome-wide association studies were conducted to identify biological pathways associated with predicted risk.

Main Results:

  • AIRE accurately predicts all-cause mortality (C-index 0.775 in development, 0.638-0.773 in validation).
  • AIRE also predicts future ventricular arrhythmia, atherosclerotic cardiovascular disease, and heart failure with high accuracy.
  • Identified biological pathways include cardiac structure/function changes and genes linked to aging and metabolic syndrome.

Conclusions:

  • AIRE is an actionable, explainable, and biologically plausible AI-ECG risk estimation platform.
  • The platform has potential for worldwide clinical use in various contexts for short-term and long-term risk estimation.
  • AIRE represents a significant advancement in AI-driven cardiovascular risk prediction.