Simulation of Cumulative Risk of Developing Altitude Decompression Sickness
Nikolaev VP. Simulation of cumulative risk of developing altitude decompression sickness. Aviat Space Environ Med 2008; 79:21–9.
Background: Recently we proposed the probabilistic model of decompression sickness (DCS) based on stochastic simulation of bubbling processes in body tissues under decompression, and on the concept of a critical volume of a free gas phase in tissues. The model defines the cumulative probability of developing all DCS symptoms by an exponential equation whose index is the integral cumulative risk function of all body tissue lesions by bubbles, Fcum(t). Methods: In this study, we modified this model by considering differences in the blood flow rates and the nucleation intensities in rested and exercised subjects. Using the new model, we analyzed the dependence of the function Fcum(t) on decompression magnitude, preoxygenation duration, and physical activity of subjects during sojourn at an altitude. Results: Simulation of the integral function Fcum(t) for various decompression profiles with the use of the hypothetic values of tissue parameters showed that body tissues which experience the largest risk of bubble lesions are different for various decompression profiles. In a finite period, Fcum(t) for any profile is identical to the function Fw(t), defining the time history of the risk of bubble lesions of some virtual tissues having a comparatively small value of nitrogen washout half-time. The virtual rates of new bubble generation in such tissues are significantly smaller than the tentative values of the rates of new bubble generation in real tissues. Good agreement of predictions of the model with the known empirical data for DCS incidence justifies the specific features of the functions Fcum(t) and Fw(t). Conclusion: Our model provides a new approach to evaluating DCS risk for various decompression profiles.
Background: Recently we proposed the probabilistic model of decompression sickness (DCS) based on stochastic simulation of bubbling processes in body tissues under decompression, and on the concept of a critical volume of a free gas phase in tissues. The model defines the cumulative probability of developing all DCS symptoms by an exponential equation whose index is the integral cumulative risk function of all body tissue lesions by bubbles, Fcum(t). Methods: In this study, we modified this model by considering differences in the blood flow rates and the nucleation intensities in rested and exercised subjects. Using the new model, we analyzed the dependence of the function Fcum(t) on decompression magnitude, preoxygenation duration, and physical activity of subjects during sojourn at an altitude. Results: Simulation of the integral function Fcum(t) for various decompression profiles with the use of the hypothetic values of tissue parameters showed that body tissues which experience the largest risk of bubble lesions are different for various decompression profiles. In a finite period, Fcum(t) for any profile is identical to the function Fw(t), defining the time history of the risk of bubble lesions of some virtual tissues having a comparatively small value of nitrogen washout half-time. The virtual rates of new bubble generation in such tissues are significantly smaller than the tentative values of the rates of new bubble generation in real tissues. Good agreement of predictions of the model with the known empirical data for DCS incidence justifies the specific features of the functions Fcum(t) and Fw(t). Conclusion: Our model provides a new approach to evaluating DCS risk for various decompression profiles.
Keywords: cumulative risk function; decompression; exercise; gas bubbles; mathematical models; nucleation; preoxygenation; “worst” virtual tissues
Document Type: Research Article
Affiliations: From the Department of Barophysiology and Dive Medicine, Institute of Biomedical Problems RAS, Moscow, Russia.
Publication date: 01 January 2008
- The peer-reviewed monthly journal, Aviation, Space, and Environmental Medicine (ASEM) provides contact with physicians, life scientists, bioengineers, and medical specialists working in both basic medical research and in its clinical applications. It is the most used and cited journal in its field. ASEM is distributed to more than 80 nations.
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