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Related Concept Videos

Acute Coronary Syndrome III: Diagnostic Studies01:30

Acute Coronary Syndrome III: Diagnostic Studies

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...
Electrocardiogram01:29

Electrocardiogram

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 the T...
Acute Coronary Syndrome II: Pathophysiology and Clinical Manifestations01:19

Acute Coronary Syndrome II: Pathophysiology and Clinical Manifestations

The pathophysiology of Acute Coronary Syndrome [ACD] involves several key processes:The main underlying cause of ACD is atherosclerosis, a chronic inflammatory disease characterized by the buildup of lipid-laden plaques within the coronary arteries.As the atherosclerotic plaque grows in the coronary artery, it may become unstable due to the formation of a lipid-rich core and a thin fibrous cap. Inflammatory cells within the plaque, such as macrophages, secrete enzymes that degrade the...
Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT01:25

Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT

Calcium-Scoring CT ScanA calcium-scoring CT scan, also known as coronary artery calcium (CAC) scan, detects calcium deposits in the coronary arteries. This test assesses the risk of coronary artery disease (CAD), which can lead to cardiovascular events such as angina, heart failure, and sudden cardiac arrest.A calcium-scoring CT scan is generally recommended for individuals at intermediate risk of CAD without symptoms. It includes:Men aged 40-75 and women aged 50-75: Especially those with a...
Acute Coronary Syndrome I: Introduction01:30

Acute Coronary Syndrome I: Introduction

Acute Coronary Syndrome (ACS) encompasses a spectrum of heart conditions caused by sudden obstruction of coronary arteries, typically resulting from the rupture of an atherosclerotic plaque and subsequent thrombus (blood clot) formation. This obstruction can lead to partial or complete blockage of blood flow, causing varying degrees of myocardial ischemia or infarction.ACS includes the following clinical entities:Unstable Angina (UA)Non-ST-Elevation Myocardial Infarction (NSTEMI)ST-Elevation...
Pulse rhythm01:30

Pulse rhythm

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 muscle...

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Related Experiment Video

Updated: May 23, 2026

Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease
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Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease

Published on: August 9, 2024

Acute Coronary Syndrome Risk Prediction Using Portable Cable-Free ECG Device Combined With Clinical Risk Assessment.

Alexei Shvilkin1, Sanja Zdolšek2, Nataša Zlatić3

  • 1Cardiovascular Division, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.

JACC. Advances
|May 21, 2026
PubMed
Summary
This summary is machine-generated.

A new algorithm combining clinical risk factors, symptoms, and portable ECG data aids in acute coronary syndrome (ACS) risk assessment. This technology may empower patients for earlier self-triage, reducing delays and improving outcomes.

Keywords:
acute coronary syndromemobile healthportable electrocardiographypre-hospital triagerisk stratification

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Patient Directed Recording of a Bipolar Three-Lead Electrocardiogram using a Smartwatch with ECG Function
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Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease
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A Research Method For Detecting Transient Myocardial Ischemia In Patients With Suspected Acute Coronary Syndrome Using Continuous ST-segment Analysis
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A Research Method For Detecting Transient Myocardial Ischemia In Patients With Suspected Acute Coronary Syndrome Using Continuous ST-segment Analysis

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Patient Directed Recording of a Bipolar Three-Lead Electrocardiogram using a Smartwatch with ECG Function
05:03

Patient Directed Recording of a Bipolar Three-Lead Electrocardiogram using a Smartwatch with ECG Function

Published on: December 11, 2019

Area of Science:

  • Cardiology
  • Medical Device Technology
  • Artificial Intelligence in Healthcare

Background:

  • Patient uncertainty in interpreting symptoms of acute coronary syndrome (ACS) leads to delayed presentation, increasing morbidity and mortality.
  • A portable, patient-operated device integrating clinical context and ECG analysis could enable earlier self-triage.
  • Current diagnostic pathways for ACS can be lengthy, contributing to delays in treatment initiation.

Purpose of the Study:

  • To assess the diagnostic performance of an algorithm for ACS risk estimation.
  • The algorithm integrates pre-existing atherosclerotic cardiovascular risk (PER), symptom risk (SR), and portable ECG data.
  • Evaluation focuses on a hand-held, cable-free ECG device for user-operated risk assessment.

Main Methods:

  • Prospective single-center study of 212 emergency department patients with chest pain; 184 analyzed.
  • A hierarchical fusion model integrated PER, SR, and ST-vector loop parameters from a cable-free ECG.
  • Algorithm performance was evaluated using ROC analysis and compared to human consensus interpretation.

Main Results:

  • The algorithm achieved an area under the curve (AUC) of 0.865 with a single portable ECG, improving to 0.929 with postevent reference comparison.
  • At matched sensitivity, the algorithm's specificity was comparable to human consensus (0.527 vs 0.458).
  • Reference comparison significantly improved model specificity (0.198 vs 0.556, P = 0.004).

Conclusions:

  • An algorithm integrating clinical factors, symptoms, and portable ECG data offers meaningful ACS risk stratification.
  • This approach, if integrated into personal devices, can support early self-triage decisions.
  • The technology has the potential to reduce patient-related prehospital delays in ACS management.