ReviewEuropean heart journal. Digital health2026
Respiratory signal extraction from the electrocardiogram for risk stratification in cardiac patients.
Review in European heart journal. Digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
14 authors.
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Abstract
Respiration is a fundamental vital sign and an established marker of disease severity and mortality risk, particularly in patients with cardiovascular disease. Despite its prognostic significance, respiratory monitoring remains underused in routine clinical practice and remote telemonitoring. At the same time, advances in biosignal processing enable robust extraction of respiratory information from the ubiquitous electrocardiogram, allowing respiratory assessment without additional sensors. This review highlights respiration as an underused biosignal in cardiovascular medicine and summarizes physiological principles and technical approaches for electrocardiogram-derived respiration, including respiratory sinus arrhythmia, respiration-related QRS amplitude modulations, and electrical axis shifts. It emphasizes the potential of electrocardiogram-derived respiration-especially nocturnal respiratory rate-in cardiac patients to enhance risk stratification and guide clinical decision-making, including patient selection for implantable cardioverter-defibrillator therapy. The feasibility of integrating nocturnal respiratory rate monitoring into standard surveillance of cardiac patients is discussed, alongside emerging evidence that this marker may identify patients with limited benefit from prophylactic implantable cardioverter-defibrillator therapy. The technical possibility to derive respiration from routine electrocardiographic recordings represents a significant yet under-utilized opportunity. Electrocardiogram-derived respiratory rate is a promising scalable non-invasive biomarker for individualized risk stratification and may complement conventional indicators such as left-ventricular ejection fraction. Large-scale prospective randomized trials are now needed to establish whether incorporating electrocardiogram-derived respiratory markers into routine practice can improve patient outcomes and optimize therapy allocation.
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