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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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Pulmonary Embolism II: Diagnostic Studies and Interprofessional Care01:29

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Diagnosing Pulmonary EmbolismDiagnosing pulmonary embolism (PE) involves clinical assessment and advanced imaging tests. The preferred diagnostic tool is the spiral (helical) CT scan or CT angiography (CTA), which uses intravenous contrast media to visualize the pulmonary vasculature and identify emboli.A ventilation-perfusion (V/Q) scan is an alternative for patients unable to receive contrast media. This scan includes both perfusion and ventilation scanning. Perfusion scanning involves...
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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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Electrocardiogram Fundamentals01:28

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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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Acute Coronary Syndrome III: Diagnostic Studies01:30

Acute Coronary Syndrome III: Diagnostic Studies

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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...
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Artificial intelligence-driven electrocardiogram analysis for risk stratification in pulmonary embolism.

Tanmay A Gokhale1,2, Nathan T Riek2, Brent Medoff1

  • 1Heart and Vascular Institute, University of Pittsburgh Medical Center, 3550 Terrace St, B571.3 Scaife Hall, Pittsburgh, PA 15261, USA.

European Heart Journal. Digital Health
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Summary

Artificial intelligence (AI) analysis of electrocardiograms (ECGs) can rapidly identify patients with pulmonary embolism (PE) at high risk. This AI-ECG model predicts clinical risk, aiding timely treatment for severe PE cases.

Keywords:
AIECGPulmonary embolismRisk stratification

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Area of Science:

  • Cardiology
  • Artificial Intelligence
  • Medical Diagnostics

Background:

  • Acute pulmonary embolism (PE) requires rapid risk stratification for effective treatment.
  • Current risk assessment methods are multi-step, involving physical exams, imaging, and lab results.
  • Electrocardiogram (ECG) alone is explored as a rapid risk stratification tool.

Purpose of the Study:

  • To develop and validate an AI model using ECG data to predict clinical risk in acute PE patients.
  • To assess the utility of ECG-based AI for rapid identification of high-risk PE patients.

Main Methods:

  • A feature-based random forest model was trained on ECG data from 1376 PE patients.
  • The model predicted risk stratification determined by a PE response team (PERT).
  • Model performance was evaluated on a holdout test set for predicting severe PE and mortality.

Main Results:

  • The AI-ECG model achieved an AUC of 0.83 and F1 score of 0.78 in predicting clinical risk (low-risk vs. severe PE).
  • A significant difference in 30-day and in-hospital mortality was observed between low-risk and elevated-risk groups identified by the AI model.
  • 55% of the cohort had submassive or massive PE, defined as 'severe PE'.

Conclusions:

  • AI analysis of 12-lead ECGs offers a valuable method for rapid PE risk stratification.
  • This approach facilitates prompt identification and treatment of PE patients at high risk of adverse outcomes.