Optimal flow adjustment of veno-venoarterial extracorporeal membrane oxygenation with an adaptive prediction model: cannula sizes screening and pump speeds estimation

• Published in: IET science, measurement & technology measurement & technology, 2016-05, Vol.10 (3), p.177-184
• Main Authors: Kan, Chung-Dann, Chen, Wei-Ling, Lin, Chia-Hung, Lu, Pong-Jeu, Du, Yi-Chun
• Format: Article
• Language: English
• Subjects: adaptive prediction model; biomedical measurement; biomembranes; blood; blood vessels; cannula sizes screening; extracorporeal flow; Gas exchange; gas exchange capability; generalised regression neural network; haemodynamics; hemodynamic stability; intensive care unit; Mathematical models; Medical materials; Membranes; neural nets; Optimal flow adjustment; Optimization; Oxygenation; pulmonary circulation; pump speeds estimation; Pumps; regression analysis; substitution‐rate matrix; Tubes; veno‐venoarterial extracorporeal membrane oxygenation; well‐oxygenated blood
• ISSN: 1751-8822; 1751-8830; 1751-8830
• DOI: 10.1049/iet-smt.2015.0030

Veno-venoarterial extracorporeal membrane oxygenation is an upgraded configuration that provides well-oxygenated blood to the systemic and pulmonary circulations. Sufficient sized cannulas, gas exchange capability, and other equipment should be selected to fulfil the desired extracorporeal supporting flow for temporary life support. Therefore, an accurate prediction model is used to screen the optimal combinations of cannula sizes and determine adequate extracorporeal flow for gas exchange. Prediction models use a substitution-rate matrix to choose optimal combinations under hemodynamic stability, and a generalised regression neural network to estimate the desired pump speed required to maintain sufficient flow. Experimental studies are used to validate the proposed model and suggest further modifications in the base/reference for the intensive care unit.