Key result
New four-step algorithm personalizes HF device selection by integrating etiology, electrical evaluation, and prognostic modifiers.
Why the study?
Heart failure remains a major global health challenge with high morbidity, mortality, and economic burden despite continuous advances in therapy.
A new four-step decision algorithm is proposed to personalize device therapy selection in heart failure patients based on etiology, electrical/functional evaluation, and prognostic modifiers.
Should not yet alter device selection in heart failure; leaves open need for prospective validation of the algorithm.
Heart failure remains a major global health challenge, characterized by high morbidity, mortality, and economic burden despite continuous advances in therapy. This review summarizes landmark clinical trials that have shaped current approaches to device therapy in heart failure, including implantable cardioverter-defibrillators, cardiac resynchronization therapy, and emerging conduction system pacing. In addition, it discusses novel prognostic and monitoring methods such as impedance cardiography and dobutamine stress echocardiography, which enable more precise patient assessment. Based on the available clinical data, we propose a new four-step decision algorithm for personalised device therapy selection in heart failure, integrating etiology-specific risk stratification, electrical and functional evaluation, and prognostic modifiers. The integration of evidence-based interventions and phenotype-driven decision-making supports a proactive and individualized approach to improving outcomes and quality of life in patients with heart failure.
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Kohoutková et al. (2025) conducted a review in Heart failure. Device therapy (ICD, CRT, CSP) vs. Standard pharmacological treatment was evaluated. A new four-step decision algorithm integrates etiology-specific risk stratification, electrical evaluation, and prognostic modifiers to personalize device therapy selection in heart failure.
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