Using animal data to improve prediction of human decompression risk following air-saturation dives.

To plan for any future rescue of personnel in a disabled and pressurized submarine, the US Navy needs a method for predicting risk of decompression sickness under possible scenarios for crew recovery. Such scenarios include direct ascent from compressed air exposures with risks too high for ethical human experiments. Animal data, however, with their extensive range of exposure pressures and incidence of decompression sickness, could improve prediction of high-risk human exposures.

On the likelihood of decompression sickness during H(2) biochemical decompression in pigs.

A probabilistic model was used to predict decompression sickness (DCS) outcome in pigs during exposures to hyperbaric H(2) to quantify the effects of H(2) biochemical decompression, a process in which metabolism of H(2) by intestinal microbes facilitates decompression. The data set included 109 exposures to 22-26 atm, ca. 88% H(2), 9% He, 2% O(2), 1% N(2), for 0.

Mathematical model of gas bubble evolution in a straight tube.

Deep sea divers suffer from decompression sickness (DCS) when their rate of ascent to the surface is too rapid. When the ambient pressure drops, inert gas bubbles may form in blood vessels and tissues. The evolution of a gas bubble in a rigid tube filled with slowly moving fluid, intended to simulate a bubble in a blood vessel, is studied by solving a coupled system of fluid-flow and gas transport equations.

A model of extravascular bubble evolution: effect of changes in breathing gas composition.

Observations of bubble evolution in rats after decompression from air dives (O. Hyldegaard and J. Madsen.

Does the time course of bubble evolution explain decompression sickness risk?

A probabilistic model of decompression sickness (DCS) risk based on linear-exponential (LE) kinetics has given the best fit of the human air and nitrox DCS database. To test the hypothesis that its success may be due to the formation of a gas phase during decompression, we developed a physiologically based bubble evolution model using a numerical solution of a partial differential equation system. Because of the computational intensity of this method, it could not be used to fully explore our hypothesis.