Close
Factors related to CO uptake and elimination in the human body: simulation by multi-compartment model
Carbon monoxide (CO) is a colourless, tasteless and odourless toxic gas and can be formed from the incomplete combustion of fossil fuels. CO is also generated within the body in small concentrations and is a neuro-transmitter. At high concentrations, CO is lethal to humans. In the body, CO will preferentially bind to haemoglobin (Hb) forming carboxyhaemoglobin (COHb), reducing oxygen transfer by the blood. As a result, human exposed to CO can suffer hypoxia and associated symptoms.
The main aim of the treatment for CO poisoning is to eliminate excess CO from the body as quickly as possible. Many studies have shown a natural half-life of CO in the blood of around 4 hours. However, there is a variation of CO elimination time seen in different patients. Many researchers have developed models and equations to explain the CO uptake and elimination. For example the Coburn-Foster-Kane(CFK) equation and multi-compartment models of Bruce and Bruce provide acceptable prediction, and contain several factors that relate to CO uptake, distribution and elimination.
However, there are still several factors that have not been adequately considered in previous models, such as total Hb mass, disease, smoking status, and lung function. Therefore, in the present project, we investigate the prediction model using data gathered from: pulmonary function tests, CO-rebreathing data, exhaled CO experimentally derived data and COHb elimination data after hyperbaric therapy.
In the present project, we create a model that includes the most relevant of these potential environmental and physiological factors and we aim to provide an improved prediction of CO uptake and elimination in the human body. We expect to determine the variation in uptake and elimination rates with a variation of the studied variables. Furthermore, we try to use the model to provide a backcast to understand different CO exposure scenarios and also to give suggestions for improvements to treatments for CO poisoning subjects.