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Related Concept Videos

Heart Failure IV: Classification and Diagnostic Evaluation01:30

Heart Failure IV: Classification and Diagnostic Evaluation

73
Heart failure can be classified in various ways, with the most common classifications based on physical activity limitations, disease progression, severity, and treatment strategies.The Functional Classification of Heart Failure divides patients into four categories based on physical activity limitation due to symptom burden.Class I: Patients in this class have cardiac disease but no physical activity limitations. Ordinary activities like walking, climbing stairs, or routine tasks do not cause...
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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...
3.8K
Pathophysiology of Heart Failure01:17

Pathophysiology of Heart Failure

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Heart failure (HF) is a progressive syndrome involving ventricles that leads to inadequate cardiac output. It can be classified based on location and output or ejection fraction. Ejection fraction (EF) is an essential measurement in the diagnosis and surveillance of HF. Reduced EF corresponds to systolic heart failure (HFrEF). However, HF with preserved ejection fraction (HFpEF) is becoming increasingly prevalent. Also known as diastolic HF, this form of HF is related to aging. The...
2.0K
Heart Failure I: Introduction01:27

Heart Failure I: Introduction

131
Heart failure refers to a clinical syndrome caused by structural or functional cardiac disorders that prevent the heart from pumping an adequate amount of blood to meet the body's metabolic needs. This condition often arises from myocardial infarction or ischemia, leading to decreased cardiac output, reduced tissue perfusion, impaired gas exchange, fluid volume imbalance, and decreased functional ability.Heart failure can result from disruptions in the mechanisms that regulate cardiac output...
131
Heart Failure V: Medical Management01:30

Heart Failure V: Medical Management

49
Medical Management of Acute Decompensated Heart Failure (ADHF)The primary goals of therapy for patients hospitalized with acute decompensated heart failure (ADHF) include:Relieving symptomsOptimizing volume statusSupporting oxygenation and ventilationMaintaining cardiac output (CO) and end-organ perfusionIdentifying and addressing the cause of ADHFPreventing complicationsProviding patient education on factors precipitating HF exacerbationPlanning for dischargeOngoing monitoring and assessment...
49
Cardiomyopathy II: Dilated Cardiomyopathy01:30

Cardiomyopathy II: Dilated Cardiomyopathy

73
Dilated cardiomyopathy, or DCM, is a progressive myocardial disorder characterized by ventricular chamber dilation and contractile dysfunction.EtiologyVarious factors can cause DCM, including hypertension and heavy alcohol intake, which contribute to the weakening and enlargement of the heart muscle. Viral infections, such as Coxsackievirus B, adenoviruses, and influenza, can lead to DCM by causing inflammation and damage to heart tissue. Certain chemotherapeutic agents, including daunorubicin,...
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Heart Failure Duration, Cardiac Remodeling, Dysfunction, and Hemodynamic Severity in HFpEF and HFmrEF: Insights From REDUCE LAP-HF II.

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Related Experiment Video

Updated: Oct 15, 2025

Cutoff Value of Phase Angle by Bioelectrical Impedance Analysis at Admission as a Prognostic Factor in Patients with Acute Heart Failure
05:16

Cutoff Value of Phase Angle by Bioelectrical Impedance Analysis at Admission as a Prognostic Factor in Patients with Acute Heart Failure

Published on: June 10, 2025

307

Identifying Heart Failure in ECG Data With Artificial Intelligence-A Meta-Analysis.

Dimitri Grün1, Felix Rudolph1, Nils Gumpfer2

  • 1Department of Internal Medicine I, Cardiology, Justus-Liebig University Giessen, Giessen, Germany.

Frontiers in Digital Health
|October 29, 2021
PubMed
Summary

Artificial intelligence (AI) effectively predicts heart failure (HF) from electrocardiograms (ECG). While AI shows high accuracy, patient-level data is crucial for reliable diagnostic assessments.

Keywords:
ECGartificial intelligencediagnosisheart failuremeta-analysis

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Last Updated: Oct 15, 2025

Cutoff Value of Phase Angle by Bioelectrical Impedance Analysis at Admission as a Prognostic Factor in Patients with Acute Heart Failure
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Area of Science:

  • Cardiology
  • Medical Informatics
  • Artificial Intelligence

Background:

  • Electrocardiography (ECG) is a primary tool for cardiovascular disease screening.
  • Heart failure (HF) diagnosis can be enhanced by advanced analytical methods.
  • Artificial intelligence (AI) offers potential for semi-automated ECG analysis.

Purpose of the Study:

  • To review AI applications in detecting heart failure from ECG signals.
  • To conduct a meta-analysis of studies evaluating AI for HF prediction using ECG data.

Main Methods:

  • A comprehensive literature search of PubMed and Google Scholar was performed.
  • Included original, peer-reviewed articles on AI-based HF detection from ECG.
  • Analyzed data from five reports encompassing 57,027 patients and 579,134 ECGs.

Main Results:

  • AI-processed ECGs achieved areas under the receiver operator characteristics curves (AUCs) from 0.92 to 0.99.
  • A meta-analysis yielded a summary ROC (sROC) of 0.987.
  • Diagnostic odds ratios ranged from 3.44 to 13.61, with a meta-analysis OR of 7.59.

Conclusions:

  • AI demonstrates significant potential for predicting heart failure using standard 12-lead ECGs.
  • AI-based HF detection from ECGs is a promising approach.
  • Overestimation in artificial ECG databases highlights the need for prospective, patient-level studies.