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. Hill equation dose-response models were fit, by using maximum likelihood, to 898 air-saturation, direct-ascent dives from humans, pigs, and rats, both individually and combined. Combining the species allowed estimation of one, more precise Hill equation exponent (steepness parameter), thus increasing the precision associated with human risk predictions. These predictions agreed more closely with the observed data at 2 ATA, compared with a current, more general, US Navy model, although the confidence limits of both models overlapped those of the data. However, the greatest benefit of adding animal data was observed after removal of the highest risk human exposures, requiring the models to extrapolate.

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 0.5-24 h. Single exponential kinetics described the tissue partial pressures (Ptis) of H(2) and He at time t: Ptis = integral (Pamb - Ptis). tau(-1) dt, where Pamb is ambient pressure and tau is a time constant. The probability of DCS [P(DCS)] was predicted from the risk function: P(DCS) = 1 - e(-r), where r = integral (Ptis(H(2)) + Ptis(He) - Thr - Pamb). Pamb(-1) dt, and Thr is a threshold parameter. Inclusion of a parameter (A) to estimate the effect of H(2) metabolism on P(DCS): Ptis(H(2)) = integral (Pamb - A - Ptis(H(2))). tau(-1) dt, significantly improved the prediction of P(DCS). Thus lower P(DCS) was predicted by microbial H(2) metabolism during H(2) biochemical decompression.

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. The governing equations for the fluid motion are solved using two techniques: an analytical method appropriate for small nondeformable spherical bubbles, and the boundary element method for deformable bubbles of arbitrary size, given an applied steady flow rate. A steady convection-diffusion equation is then solved numerically to determine the concentration of gas. The bubble volume, or equivalently the gas mass inside the bubble for a constant bubble pressure, is adjusted over time according to the mass flux at the bubble surface. Using a quasi-steady approximation, the evolution of a gas bubble in a tube is obtained. Results show that convection increases the gas pressure gradient at the bubble surface, hence increasing the rate of bubble evolution. Comparing with the result for a single gas bubble in an infinite tissue, the rate of evolution in a tube is approximately twice as fast. Surface tension is also shown to have a significant effect. These findings may have important implications for our understanding of the mechanisms of inert gas bubbles in the circulation underlying decompression sickness.

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. Undersea Biomed. Res. 16: 185-193, 1989; O. Hyldegaard and J. Madsen. Undersea Hyperbaric Med. 21: 413-424, 1994; O. Hyldegaard, M. Moller, and J. Madsen. Undersea Biomed. Res. 18: 361-371, 1991) suggest that bubbles may resolve more safely when the breathing gas is a heliox mixture than when it is pure O(2). This is due to a transient period of bubble growth seen during switches to O(2) breathing. In an attempt to understand these experimental results, we have developed a multigas-multipressure mathematical model of bubble evolution, which consists of a bubble in a well-stirred liquid. The liquid exchanges gas with the bubble via diffusion, and the exchange between liquid and blood is described by a single-exponential time constant for each inert gas. The model indicates that bubbles resolve most rapidly in spinal tissue, in adipose tissue, and in aqueous tissues when the breathing gas is switched to O(2) after surfacing. In addition, the model suggests that switching to heliox breathing may prolong the existence of the bubble relative to breathing air for bubbles in spinal and adipose tissues. Some possible explanations for the discrepancy between model and experiment are discussed.

Effect of lipid on inert gas kinetics.

A Monte Carlo simulation of inert gas transit through skeletal muscle has been extended to include regions of increased gas solubility to simulate regions of high lipid content. Position of the regions within the simulation module was varied, as was the muscle-lipid partition coefficient (lambda). The volume percentage of the lipid regions (alpha) was varied from 0 to 25% while lambda covered the range from 1 to 50. The effects of alpha and lambda on mean transit time and on relative dispersion (RD; ratio of SD to the mean) were examined for a single lipid volume and compared with expected values under the assumption that the tissue is composed of two well-stirred compartments. Mean transit times varied from approximately 0.80 to 1.20 times the values predicted by a simple parallel two-compartment model, whereas RD varied from 0.9 to 3.6. For fixed lambda, RD as a function of lipid fraction passes through a maximum that is shifted and was also smaller than expected from a simple two-compartment model. For fixed alpha, RD approaches an asymptotic value for large lambda, but the asymptote is smaller than that expected from the two-compartment model. When lipid is distributed in only two regions, RD decreases with increasing separation of the regions and with increasing surface area of the fat regions. A model of two well-stirred compartments that allows mixing between the compartments yields results similar to those from the simulation.

Quantifying the effect of intravascular perfluorocarbon on xenon elimination from canine muscle.

Intravenous infusions of perfluorocarbon (PFC) may improve decompression sickness outcome in animals by accelerating inert gas elimination from tissue, but any such effect has not been quantified experimentally. In this study we used an animal model of tissue Xe kinetics to test this hypothesis and to quantify the effect of PFC. Eight dogs were ventilated with dilute 133Xe in air for 4 h of Xe uptake. Four dogs were then given an infusion (20 ml/kg iv) of a 40% (vol/vol) perfluorodecalin-glycerol emulsion, and four control dogs were given only isotonic glycerol. All were then switched to open-circuit air breathing for 4 h of Xe elimination. During this time Xe radioactivity-time curves were recorded from two intact hind leg muscles, and the Xe mean residence times during elimination were estimated using an analysis by moments and compared by group. Tissue blood flows were measured using microspheres once during Xe uptake and twice during Xe elimination, and cardiac outputs were measured by thermodilution at 30-min intervals. In the PFC group the measured circulating PFC fraction increased the calculated Xe solubility by an average factor of 1.77 and so was expected to increase the Xe elimination rate by 77%. The observed Xe mean residence times on elimination for the PFC group averaged 33.5 min [95% confidence interval (CI) 19.5-47.6] compared with the glycerol control average of 70.1 min (95% CI 56.1-84.2), representing an increase in the rate of Xe elimination by a factor of 2.09 or 109%.(ABSTRACT TRUNCATED AT 250 WORDS)