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1.
ASAIO J ; 46(5): 563-8, 2000.
Artículo en Inglés | MEDLINE | ID: mdl-11016507

RESUMEN

The objective was to determine whether a previously developed technique for biological aortic valves could predict flow through a mechanical valve. An electrical analog model of the aortic valve that includes compliance, resistance, and inertance parameters, and corresponding second order differential equations was used to predict flow given a pressure gradient, as previously reported. Simulated pressures and flow were recorded by using a pulse duplicator system. The heart rate was varied from 60 to 180 bpm, and the stroke volume was varied from 22 to 67 cc. Resistance, inertance, and compliance parameters of the governing differential equation were estimated by using a least-squares fit to the measured flow at 120 bpm and 50 cc stroke volume. By using these parameter estimates, flow was calculated for other heart rates and stroke volumes. To achieve a better flow prediction, a nonlinear filter (third order polynomial range calibration equation) was applied to the output of the linear model (flow). The mean error, full-scale error, and spectral error in magnitude and phase between measured and predicted flow were compared. Error in mean flow ranged from 3% at medium flow rates to 90% at low flow rates. The maximum and minimum full scale errors were 12% and 5%, respectively. Error in the harmonics of measured and calculated flow ranged from 0% to 55%. Larger errors were usually present at the higher harmonics. The agreement between measured and calculated flow was better at normal and high flows but rather poor at low flows. The nonlinear filter (range calibration equation) was unable to account for the discrepancies between the measured and calculated flow over all flow ranges. It seems that this linear model and nonlinear filter have limited application, and an alternate nonlinear approach may produce better results.


Asunto(s)
Válvula Aórtica/fisiología , Prótesis Valvulares Cardíacas , Válvula Aórtica/cirugía , Frecuencia Cardíaca , Humanos , Presión , Volumen Sistólico
2.
ASAIO J ; 45(3): 204-10, 1999.
Artículo en Inglés | MEDLINE | ID: mdl-10360724

RESUMEN

The objective was to develop a technique for calculating continuous, beat-to-beat aortic flow (AoF) using only left ventricular pressure (LVP) and aortic pressure (AoP). An electric analog model of the aortic valve was developed that includes resistance (R), inertance (L), and compliance (C) parameters, and resulting second order differential equations were derived. Aortic flow, AoP, and LVP recorded in eight subjects during a 5 day period and during lower body negative pressure (LBNP) were used to validate the model. Resistance, L, and C were estimated using a least-squares fit to the measured AoF on day 0 and during 0 mm Hg LBNP. For days 1-4, AoF was calculated using measured values of AoP and LVP and the R, L, and C values from day 0. Similarly, for LBNP, AoF was calculated using measured values of AoP and LVP, and the R, L, and C values from 0 mm Hg LBNP. The calculated and measured AoF were compared. Differences in cardiac output between the calculated and measured flows were less than 13.1+/-17% across days and under minor altered physiologic conditions (LBNP). Waveform morphology for the calculated AoF also agreed well with the measured AoF. Spectral analysis showed differences in magnitude and phase between measured and calculated aortic flow for the first five harmonics across days, less than 20+/-6% and 25+/-14 degrees, respectively. Preliminary evaluation indicates that our model works well for calculating flow through a biologic valve using LVP and AoP. We speculate that it may perform better for a mechanical valve, and if so it may be possible to develop an instrumented mechanical valve capable of continuous LVP, AOP, and AoF measurements.


Asunto(s)
Aorta/fisiología , Válvula Aórtica/fisiología , Presión Sanguínea/fisiología , Modelos Cardiovasculares , Flujo Pulsátil/fisiología , Animales , Velocidad del Flujo Sanguíneo/fisiología , Macaca mulatta , Masculino , Método de Montecarlo
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