The use of mathematical models can aid in optimizing therapy settings in ventilated patients to achieve certain therapy goals. Especially when multiple goals have to be met, the use of individualized models can be of ...The use of mathematical models can aid in optimizing therapy settings in ventilated patients to achieve certain therapy goals. Especially when multiple goals have to be met, the use of individualized models can be of great help. The presented work shows the potential of using models of respiratory mechanics and gas exchange to optimize minute ventilation and oxygen supply to achieve a defined oxygenation and carbon dioxide removal in a patient while guaranteeing lung protective ventilation. The venti-lator settings are optimized using respiratory mechanics models to compute a respira-tion rate and tidal volume that keeps the maximum airway pressure below the critical limit of 30 cm H2O while ensuring a sufficient expiration. A three-parameter gas ex-change model is then used to optimize both minute ventilation and oxygen supply to achieve defined arterial partial pressures of oxygen and carbon dioxide in the patient. The presented approach was tested using a JAVA based patient simulator that uses various model combinations to compute patient reactions to changes in the ventilator settings. The simulated patient reaction to the optimized ventilator settings showed good agreement with the desired goals.展开更多
文摘The use of mathematical models can aid in optimizing therapy settings in ventilated patients to achieve certain therapy goals. Especially when multiple goals have to be met, the use of individualized models can be of great help. The presented work shows the potential of using models of respiratory mechanics and gas exchange to optimize minute ventilation and oxygen supply to achieve a defined oxygenation and carbon dioxide removal in a patient while guaranteeing lung protective ventilation. The venti-lator settings are optimized using respiratory mechanics models to compute a respira-tion rate and tidal volume that keeps the maximum airway pressure below the critical limit of 30 cm H2O while ensuring a sufficient expiration. A three-parameter gas ex-change model is then used to optimize both minute ventilation and oxygen supply to achieve defined arterial partial pressures of oxygen and carbon dioxide in the patient. The presented approach was tested using a JAVA based patient simulator that uses various model combinations to compute patient reactions to changes in the ventilator settings. The simulated patient reaction to the optimized ventilator settings showed good agreement with the desired goals.
