End-systolic Pressure-Volume Relation, Ejection Fraction, and Heart Failure: Theoretical Aspect and Clinical Applications
| Autor: | Rachad M. Shoucri |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
lcsh:Diseases of the circulatory (Cardiovascular) system
Ejection fraction pressure–volume relation mathematical physiology business.industry Mathematical physiology PVR ventricular mechanics heart failure medicine.disease Normal group Stenosis Clinical work medicine.anatomical_structure Ventricle lcsh:RC666-701 ESPVR Heart failure medicine End systolic pressure volume relation segregation and classification of clinical data Cardiology and Cardiovascular Medicine business Biomedical engineering Original Research |
| Zdroj: | Clinical Medicine Insights. Cardiology Clinical Medicine Insights: Cardiology, Vol 2015, Iss Suppl. 1, Pp 111-120 (2015) Clinical Medicine Insights: Cardiology, Vol 9s1 (2015) |
| ISSN: | 1179-5468 |
| Popis: | A mathematical formalism describing the nonlinear end-systolic pressure–volume relation (ESPVR) is used to derive new indexes that can be used to assess the performance of the heart left ventricle by using the areas under the ESPVR (units of energy), the ordinates of the ESPVR (units of pressure), or from slopes of the curvilinear ESPVR. New relations between the ejection fraction (EF) and the parameters describing the ESPVR give some insight into the problem of heart failure (HF) with normal or preserved ejection fraction. Relations between percentage occurrence of HF and indexes derived from the ESPVR are also discussed. When ratios of pressures are used, calculation can be done in a noninvasive way with the possibility of interesting applications in routine clinical work. Applications to five groups of clinical data are given and discussed (normal group, aortic stenosis, aortic valvular regurgitation, mitral valvular regurgitation, miscellaneous cardiomyopathies). No one index allows a perfect segregation between all clinical groups, it is shown that appropriate use of two indexes (bivariate analysis) can lead to better separation of different clinical groups. |
| Databáze: | OpenAIRE |
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