Physiological trend analysis of a novel cardio-pulmonary model during a preload reduction manoeuvre. (June 2022)

• Record Type: Journal Article
• Authors: Cushway, James; Murphy, Liam; Chase, J. Geoffrey; Shaw, Geoffrey M.; Desaive, Thomas
• Is Part Of: Computer methods and programs in biomedicine. Volume 220(2022)
• Publication Date: 2022-06
• Subjects: Positive end-expiratory pressure -- Stressed blood volume -- Cardiovascular -- Cardio-pulmonary -- Thoracic pressure; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2022.106819
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: A cardio-pulmonary model developed from 3 chamber cardiovascular model and 1 chamber respiratory model. Both models used to identify haemodynamic parameters of 4 pigs during a preload reduction manoeuvre. Model outputs and parameters compared. Analysis of effects of PEEP on haemodynamic parameters and model performance. Abstract: Background and objective: Mechanical ventilation causes adverse effects on the cardiovascular system. However, the exact nature of the effects on haemodynamic parameters is not fully understood. A recently developed cardio-vascular system model which incorporates cardio-pulmonary interactions is compared to the original 3-chamber cardiovascular model to investigate the exact effects of mechanical ventilation on haemodynamic parameters and to assess the trade-off of model complexity and model reliability between the 2 models. Methods: Both the cardio-pulmonary and three chamber models are used to identify cardiovascular system parameters from aortic pressure, left ventricular volume, airway flow and airway pressure measurements from 4 pigs during a preload reduction manoeuvre. Outputs and parameter estimations from both models are contrasted to assess the relative performance of each model and to further investigate the effects of mechanical ventilation on haemodynamic parameters. Results: Both models tracked measurements accurately as expected. There was no identifiable increase in error from the added complexity of the cardio-pulmonary model, with both models having a mean average error below 0.5% for all pigs. Identified left ventricle and vena cava elastances of the 3-chamber model was found to diverge exponentially with PEEP from identified left ventricle and vena cava elastances of the cardio-pulmonary model. The r 2 of the fit for each pig ranged from 0.888 to 0.998 for left ventricle elastance divergence and from 0.905 to 0.999 for vena cava elastance divergence. All other identified parameters showed no significant difference between models. Conclusions: Despite the increase in model complexity, there was no loss in the cardio-pulmonary model's ability to accurately estimate haemodynamic parameters and reproduce system dynamics. Furthermore, the cardio-pulmonary model was able to demonstrate how mechanical ventilation affected parameter estimations as PEEP was increased. The 3-chamber model was shown to produce parameter estimations which diverged exponentially with PEEP, while the cardiopulmonary model estimations remained more stable, suggesting its ability to produce more physiologically accurate parameter estimations under higher PEEP conditions.