PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
March 1, 1979AJP Heart and Circulatory Physiology432 citations

Total mechanical energy of a ventricle model and cardiac oxygen consumption

View Full Paper
HSHiroyuki Suga

Structured PICO

P
Population
Canine left ventricle (data from 11 hearts in literature, plus preliminary experimental study)
I
Intervention
Calculation of pressure-volume area (PVA) as a measure of mechanical energy
O
Outcome
Correlation between mechanical energy (PVA) and oxygen consumption per beat (VO2)surrogate

The pressure-volume area (PVA) is highly correlated with and can predict myocardial oxygen consumption per beat in the canine left ventricle.

Abstract

Mechanical energy (ENG) required by a time-varying elastance model of the ventricle was compared with oxygen consumption per beat (VO2) of the canine left ventricle contracting under a variety of loading conditions. ENG needed for this model to increase its elastance during systole is shown to be equal to the sum of the potential energy built in the elastance during systole plus the external mechanical stroke work. This ENG is equivalent to the area (PVA) bounded by the end-systolic and end-diastolic P-V curves and the systolic limb of the P-V loop trajectory in the P-V plane. There was a high correlation (r = 0.89) between VO2s documented in the literature and PVAs assessed by the author from the accompanying P-V data from both isovolumic and ejecting contractions in 11 hearts. A linear regression analysis yielded an empirical equation: VO2 (ml O2/beat) = a . PVA (mmHg . ml/beat) + b, where a = 1.37 X 10(-5) and b = 0.027, which can be used to predict VO2 from PVA. A preliminary experimental study in my laboratory confirmed the validity of this empirical equation.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Hiroyuki Suga (1979) studied this question.

synapsesocial.com/papers/6a14e4bb0b551a597239135ehttps://doi.org/10.1152/ajpheart.1979.236.3.h498
Ask AI
Helpful
Bookmark
Share
View Full Paper