Predicting oxygenator clinical performance from laboratory in-vitro testing.
Knowledge and predictability of oxygenator performance is vital to safe and effective conduct of cardiopulmonary bypass. The determination of oxygenator performance in the laboratory, however, is carried out under a strict set of conditions established by the Association for the Advancement of Medical Instrumentation (AAMI). This performance data is of limited value in the clinical setting where the perfusionist generally operates outside this set of parameters. This study (1) reports the laboratory performance characteristics of a hollow fiber membrane oxygenator (Sorin Monolyth), (2) uses this data to develop a model to predict performance under a wide range of clinical conditions, (3) compares predicted performance with clinical data collected at two open heart centers, and (4) reviews the complexities of comparing laboratory and clinical performance. An in-vitro "oxygenator-deoxygenator" circuit was utilized to determine O2 and CO2 gas exchange, blood path pressure drop, and heat exchanger efficiency at a variety of blood and gas flows, under standard (AAMI) blood inlet conditions: [table: see text] This laboratory performance data was compared to hospital and computer modeling data. Simple numerical comparison and analysis of variance of regression coefficients over groups indicated that some clinical parameters of performance (oxygen transfer and coefficient of heat exchange) were not predicted with the laboratory data. It is concluded that the laboratory performance data determined under strict controlled conditions may be of limited value in predicting clinical performance unless modeled to allow for variances in operating conditions.
Griffith
K E
KE
Division of Circulation Technology, School of Allied Medical Professions, Ohio State University, Columbus, USA.
Vasquez
M R
MR
Beckley
P D
PD
LaLone
B J
BJ
D000704:Analysis of Variance; D001784:Blood Gas Analysis; D001794:Blood Pressure; D002315:Cardiopulmonary Bypass / Q000295:instrumentation*; D003198:Computer Simulation; D006801:Humans; D008422:Materials Testing; D010100:Oxygen / Q000627:therapeutic use*; D011237:Predictive Value of Tests; D011659:Pulmonary Gas Exchange; D012044:Regression Analysis