Single-beat evaluation of left ventricular inotropic state in conscious dogs.
Two competing left ventricular elastic-resistive (ER) models were used to predict parameter values from pressure, volume, and time data of a single ejective beat in conscious dogs during control, enhanced (dobutamine), and decreased (propranolol) inotropic states. The animals were instrumented with three pairs of microcrystals and a transducer to measure intraventricular volume and pressure. Results showed that with the ER nonlinear model (ERNL), parameter values in all animals lay within the physiological range. These were the slope (Emax) and the intercept (V0) of the isovolumic end-systolic pressure-volume relationship (ESPVR), the slope of the end-diastolic pressure-volume relationship (Ed), the time to Emax (Tmax), the normalized time to end of activation (A), and the resistive constant (K). In the two models, the normalized SE of the estimate of data fitting was below 0.2 Emax, as estimated from a single beat, responded to changes in contractility in a significantly more consistent fashion than the slope of ESPVRs (Ees) generated by preload maneuvers in conscious dogs. Single-beat estimated Tmax and K with the ERNL model did also respond consistently to contractility changes, whereas with the elastic resistive linear (ERL) model, K did not reproduce the experimental findings with decreased inotropic state. We conclude that 1) the ERNL model can be employed to assess contractility changes in conscious dogs from data of a single ejective beat, and 2) these changes are better indicated by single-beat estimated Emax than by Ees calculated from conventional ESPVRs.
Lascano
E C
EC
Departamento de Investigación y Docencia de la Fundación Favaloro, Universidad de Buenos Aires, Argentina.
Negroni
J A
JA
Barra
J G
JG
Crottogini
A J
AJ
Pichel
R H
RH
D000465:Algorithms; D000818:Animals; D004285:Dogs; D006321:Heart / Q000502:physiology*; D006439:Hemodynamics; D009200:Myocardial Contraction; D012016:Reference Values; D016276:Ventricular Function