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Related Concept Videos

Heart Failure Drugs: Inhibitors of Renin-Angiotensin System01:26

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The activation of the sympathetic nervous system and the renin-angiotensin-aldosterone system (RAAS) contributes to cardiac remodeling, and inhibiting the RAAS is a pharmacological target in heart failure management. As a result, neurohumoral modulation is a crucial treatment principle for managing heart failure. This approach involves using medications like ACE inhibitors (ACEIs), angiotensin receptor blockers (ARBs), β-blockers, mineralocorticoid receptor antagonists (MRAs), and neutral...
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Heart Failure VI: Adjunct Therapies01:22

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Additional therapies for treating patients with heart failure (HF) may include procedural interventions, supplemental oxygen, the management of sleep disorders, and nutritional therapy.Procedural InterventionsImplantable Cardioverter-Defibrillator: For patients at risk of life-threatening arrhythmias due to severe left ventricular dysfunction, an Implantable Cardioverter-Defibrillator (ICD) can detect and terminate these arrhythmias, preventing sudden cardiac death and improving survival rates.
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Heart Failure V: Medical Management01:30

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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...
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Systolic Heart Failure and Compensatory MechanismsSystolic heart failure (also termed HFrEF, Heart Failure with Reduced Ejection Fraction) is the most prevalent type of heart filure. It results in a decreased volume of blood being pumped from the ventricle. The aortic arch and carotid sinuses have baroreceptors that detect reduced blood pressure, triggering the sympathetic nervous system (SNS) to release epinephrine and norepinephrine. Initially, this response aims to boost heart rate and...
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Heart Failure IV: Classification and Diagnostic Evaluation01:30

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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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Heart Failure I: Introduction01:27

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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...
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Artificial intelligence in heart failure.

Xueqin Li1, Yu Liu1, Xianya Zhang2

  • 1Department of Medical Ultrasound, Minda Hospital of Hubei Minzu University, Enshi, Hubei, China.

The Egyptian Heart Journal : (EHJ) : Official Bulletin of the Egyptian Society of Cardiology
|March 1, 2026
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Artificial intelligence (AI) is transforming heart failure (HF) management, moving beyond "one-size-fits-all" treatments. This review explores AI

Keywords:
Artificial intelligenceHeart failureMachine learningPatient management

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Area of Science:

  • Cardiovascular Medicine and Artificial Intelligence
  • Digital Health and Precision Medicine

Background:

  • Heart failure (HF) is a growing global health concern affecting millions.
  • Current HF management guidelines show variable treatment efficacy, necessitating personalized approaches.
  • Artificial intelligence (AI) is increasingly integrated into cardiovascular research, yet clinical translation for HF remains limited.

Purpose of the Study:

  • To provide a comprehensive review of AI applications across the entire HF clinical process.
  • To analyze the prospects and challenges of AI development in HF.
  • To offer insights for future clinical transformation and research optimization of AI in HF.

Main Methods:

  • Systematic review of AI applications in HF patient diagnosis and subtyping.
  • Evaluation of AI in prognostic assessment and treatment response prediction.
  • Assessment of AI in pre- and post-treatment monitoring and telecare for HF patients.

Main Results:

  • AI demonstrates potential across various HF management stages, from diagnosis to telecare.
  • Specific AI applications include patient stratification, risk prediction, and personalized treatment strategies.
  • The review highlights AI's role in enhancing HF patient monitoring and remote care.

Conclusions:

  • AI offers a promising avenue for individualized HF care, addressing limitations of current approaches.
  • Challenges remain in AI's clinical translation, requiring further research and validation.
  • Future directions focus on developing robust AI systems for seamless integration into clinical practice.