ReviewClinical Medicine Insights. Cardiology2015
Characterizing heart failure in the ventricular volume domain.
Review in Clinical Medicine Insights. Cardiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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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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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
12 citing papers in PubMed, 43 citations in OpenAlex.
- Article
- Improved Interpretation of Pulmonary Artery Wedge Pressures through Left Atrial Volumetry-A Cardiac Magnetic Resonance Imaging Study.Journal of cardiovascular development and disease · 2024Article
- Automatic measurements of left ventricular volumes and ejection fraction by artificial intelligence: clinical validation in real time and large databases.European heart journal. Cardiovascular Imaging · 2024Article
- ln silico simulation of the interaction among autoregulatory mechanisms regulating cerebral blood flow rate in the healthy and systolic heart failure conditions during exercise.Medical & biological engineering & computing · 2022Article
- Cardiac structure and function and quality of life associations in HFpEF: An analysis from TOPCAT-Americas.International journal of cardiology · 2022Article
- A framework for developing sex-specific engineered heart models.Nature reviews. Materials · 2022Review
- The role of mechanotransduction in heart failure pathobiology-a concise review.Heart failure reviews · 2021Review
- Overcoming the Limits of Ejection Fraction and Ventricular-Arterial Coupling in Heart Failure.Frontiers in cardiovascular medicine · 2021Article
- Clinical significance of quantitative assessment of right ventricular glucose metabolism in patients with heart failure with reduced ejection fraction.European journal of nuclear medicine and molecular imaging · 2019Article
- Article
- The Volume Regulation Graph versus the Ejection Fraction as Metrics of Left Ventricular Performance in Heart Failure with and without a Preserved Ejection Fraction: A Mathematical Model Study.Clinical Medicine Insights. Cardiology · 2015Article
- Exploring Guidelines for Classification of Major Heart Failure Subtypes by Using Machine Learning.Clinical Medicine Insights. Cardiology · 2015Article
Corrections and comments
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Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Heart failure (HF) may be accompanied by considerable alterations of left ventricular (LV) volume, depending on the particular phenotype. Two major types of HF have been identified, although heterogeneity within each category may be considerable. All variants of HF show substantially elevated LV filling pressures, which tend to induce changes in LV size and shape. Yet, one type of HF is characterized by near-normal values for LV end-diastolic volume (EDV) and even a smaller end-systolic volume (ESV) than in matched groups of persons without cardiac disease. Furthermore, accumulating evidence indicates that, both in terms of shape and size, in men and women, the heart reacts differently to adaptive stimuli as well as to certain pharmacological interventions. Adjustments of ESV and EDV such as in HF patients are associated with (reverse) remodeling mechanisms. Therefore, it is logical to analyze HF subtypes in a graphical representation that relates ESV to EDV. Following this route, one may expect that the two major phenotypes of HF are identified as distinct entities localized in different areas of the LV volume domain. The precise coordinates of this position imply unique characteristics in terms of the actual operating point for LV volume regulation. Evidently, ejection fraction (EF; equal to 1 minus the ratio of ESV and EDV) carries little information within the LV volume representation. Thus far, classification of HF is based on information regarding EF combined with EDV. Our analysis shows that ESV in the two HF groups follows different patterns in dependency of EDV. This observation suggests that a superior HF classification system should primarily be founded on information embodied by ESV.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.