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A cardiovascular model for renal perfusion during cardiopulmonary bypass surgery. | LitMetric

A cardiovascular model for renal perfusion during cardiopulmonary bypass surgery.

Comput Biol Med

Faculty of Engineering and Mathematical Sciences, The University of Western Australia, Perth, Australia.

Published: April 2020

Acute kidney injury (AKI) is a major complication following cardiac surgery requiring cardiopulmonary bypass (CPB). It is likely that poor renal perfusion contributes to the occurrence of AKI, via renal hypoxia, so it is imperative to maintain optimal renal perfusion during CPB. We have developed a straightforward cardiovascular perfusion model with parameter values calibrated against experimental and/or clinical data from several independent studies of CPB in humans and animals. Following model development and calibration, we performed a one-at-a-time parametric study to investigate the response of renal perfusion to several variables during CPB, namely pump flow (denoted CO for 'cardiac output'), renal vascular resistance, and non-renal vascular resistance. From the parametric study, we have found that all three parameters had a similarly strong influence on renal perfusion. We simulated three potential strategies for maintaining optimum renal perfusion during CPB and tested their effectiveness. The strategies were: (1) increasing the pump flow; (2) administrating noradrenaline (vasopressor); and (3) administrating fenoldopam (renal vasodilator). Simulations have revealed that administration of fenoldopam is likely to be the most effective of the three strategies. Other findings from our simulations are that increasing pump flow is less effective when central venous pressure is elevated. Further, renal autoregulation is likely inoperative during CPB, as evidenced by an unchanging renal vascular resistance with increasing CO and blood pressure. The cardiac-renal perfusion model developed in this study can be linked with other kidney models to simulate the changes in renal oxygenation during CPB.

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Source
http://dx.doi.org/10.1016/j.compbiomed.2020.103676DOI Listing

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