A model to simulate human cardio-respiratory responses to ketamine analgesia.

In large-scale combat operations, decision-support systems based on artificial intelligence technology can augment the capability and capacity of medics to care for combat casualties. The development and assessment of such systems require large amounts of vital-sign data, which are impractical to obtain from clinical or experimental studies but can be generated using high-fidelity computational models. We previously developed and validated a human cardio-respiratory model (the CR model) that accounts for both cardiovascular and respiratory responses to hemorrhagic injuries and resuscitation with six commonly used fluid types. Here, we extended the CR model to represent the effect of ketamine analgesia on the vital signs by integrating two existing pharmacokinetic-pharmacodynamic models of ketamine [one representing the effect of ketamine on mean arterial pressure (MAP) and another on cardiac output], with two feedback controllers described within the CR model. We validated the extended model using experimental data of ketamine administration in three human studies for healthy individuals. Simulation results showed that the model captured the general trend of the experimental data for MAP and heart rate (HR) with root mean square errors of 6.17 mmHg and 7.51 beats/min, respectively. In addition, in simulations of hemorrhagic injury, ketamine administration rapidly increased MAP and cardiac output, but the magnitude of the increase decreased with hemorrhage severity. MAP increased by 40%, 30%, and 15% of its baseline value in the presence of no, moderate, and severe hemorrhage, respectively. Given that most wounded Service members receive pain medication in the form of ketamine, the ability to account for its effects on vital signs will allow us to generate more comprehensive synthetic data of combat casualties.