摘要：AbstractCurrent methods to optimise mechanical ventilation involve increasing positive end expiratory pressure (PEEP) in steps to maximize recruitment. If PEEP is too high, overdistension and damage occur. There is thus an inherent risk involved when increasing PEEP. This study predicts dynamic elastance and lung mechanics for higher PEEP using clinically relevant elastance basis functions, capturing distension, recruitment and constant stiffness, in a first order model of lung mechanics. The clinically relevant basis functions were used to fit elastance using a single compartment lung model for 10 patients undergoing recruitment maneuvers, where 2-4 PEEP levels were analysed, and then used to predict the elastance and pressure waveforms for PEEP level increases of 5 and 10cmH2O. The mean error for the pressure fits from the clinically relevant basis functions was 2.06%. Mean error for pressure predictions with a PEEP level increase of 5cmH2Owas 3.8-5.5%. Mean error for PEEP level increases of 10cmH2Owas slightly higher, between 5.0 and 6.6%. Good pressure fits and predictions show these basis functions accurately fit and predict elastance and thus lung behavior at increased PEEP levels. Each clinically relevant basis function behaved as expected, however improvements to the identifiability of distension would further improve the overall accuracy.
