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Related Concept Videos

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

Heart Failure Drugs: Inhibitors of Renin-Angiotensin System

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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 Drugs: Inotropic Agents01:26

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Positive inotropic agents are commonly used as the first line of treatment for heart failure. One such agent is digoxin, derived from the genus Digitalis, which has been known for centuries but effectively utilized since 1785. However, these cardiac glycosides can have potentially toxic effects due to their mechanism of action, which involves inhibiting Na+/K+-ATPase and increasing contractility. Digoxin is absorbed orally and distributed in various tissues, including the CNS. It has a long...
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Pathophysiology of Heart Failure01:17

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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...
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Heart Failure Drugs: Diuretics01:22

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Heart failure and kidney perfusion are interconnected in a complex way. Reduced renal perfusion and venous congestion are two significant factors that contribute to renal dysfunction in heart failure. The kidneys, primarily responsible for fluid balance in the body, are adversely affected due to compromised cardiac output and increased venous pressure. In response to reduced renal perfusion, the kidneys activate neurohumoral mechanisms to restore balance. However, these mechanisms can be...
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Related Experiment Video

Updated: May 21, 2025

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction
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Developing an artificial intelligence-based decision engine for disease-modifying therapy in heart failure: a pilot

Arno J Gingele1, Hesam Amin1,2,3, Kurt De Wit4

  • 1Department of Cardiology, Maastricht University Medical Centre, P.Debyelaan 25, 6229 HX Maastricht, The Netherlands.

European Heart Journal. Digital Health
|March 20, 2025
PubMed
Summary
This summary is machine-generated.

An artificial intelligence (AI) decision engine was developed to provide guideline-based medication recommendations for heart failure patients. This AI tool achieved 94% agreement with specialist decisions, enhancing self-care for heart failure management.

Keywords:
Artificial intelligenceClinicalDecision support systemsGuidelineHeart failure

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Area of Science:

  • Cardiology
  • Artificial Intelligence
  • Digital Health

Background:

  • Heart failure presents a growing global health challenge, necessitating innovative care solutions.
  • Current eHealth tools lack the capability to initiate or adjust heart failure medications.
  • Artificial intelligence offers potential for advancing personalized heart failure treatment.

Purpose of the Study:

  • To develop an AI-based decision engine for guideline-directed heart failure medication recommendations.
  • To create a tool that supports enhanced self-care and clinical decision-making in heart failure management.

Main Methods:

  • European Society of Cardiology (ESC) heart failure guidelines were translated into Business Process Model and Notation (BPMN).
  • A safety evaluation assessed the engine's clinical applicability across 72 virtual heart failure patient scenarios.
  • An independent heart failure specialist validated the engine's treatment recommendations.

Main Results:

  • The AI decision engine generated guideline-based recommendations for disease-modifying heart failure therapy.
  • The engine achieved 94% concordance with independent specialist treatment decisions.
  • 100% of the engine's recommendations aligned with the 2021 ESC heart failure guidelines.

Conclusions:

  • The developed AI decision engine provides accurate, guideline-based therapeutic recommendations for heart failure.
  • This tool has the potential to empower heart failure patients in self-care and improve treatment adherence.
  • Prospective validation in a multicentre clinical trial is underway to confirm real-world efficacy.