On the likelihood of decompression sickness during H₂ biochemical decompression in pigs

Abstract

. On the likelihood of decompression sickness during H2 biochemical decompression in pigs. J Appl Physiol 91: 2720 -2729, 2001.-A probabilistic model was used to predict decompression sickness (DCS) outcome in pigs during exposures to hyperbaric H 2 to quantify the effects of H2 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% O2, 1% N2, for 0.5-24 h. Single exponential kinetics described the tissue partial pressures (Ptis) of H2 and He at time t: Ptis ϭ ͐ (Pamb Ϫ Ptis) ⅐ Ϫ1 dt, where Pamb is ambient pressure and is a time constant. The probability of DCS [P(DCS)] was predicted from the risk function:Ϫr , where r ϭ ͐ (Ptis H 2 ϩ PtisHe Ϫ Thr Ϫ Pamb) ⅐ Pamb Ϫ1 dt, and Thr is a threshold parameter. Inclusion of a parameter (A) to estimate the effect of H2 metabolism on P(DCS): PtisH 2 ϭ ͐ (Pamb Ϫ A Ϫ Ptis H 2 ) ⅐ Ϫ1 dt, significantly improved the prediction of P(DCS). Thus lower P(DCS) was predicted by microbial H 2 metabolism during H2 biochemical decompression. probabilistic modeling; Sus scrofa; hydrogen diving; H2 metabolism; Methanobrevibacter smithii MODELING OF DECOMPRESSION SICKNESS (DCS) risk has been impeded by the inability to identify correlated physiological variables. Some studies have tried to find a correlation between DCS risk and variables such as body temperature, body weight, exercise, gender, adiposity, age, serum cholesterol, sensitivity to complement activation, Doppler bubble grades, and patent foramen ovale (4,12,16,23,28). However, where some studies have found a correlation, others refute those results (5,8,16). The only physiological variable that has been undisputedly correlated with DCS risk in rats is body weight (20). Because reliable physiological correlates are lacking, researchers have used a variety of models based solely on the physical history of the compression and decompression sequence to find variables that can predict the probability of DCS (26, 31-34).The DCS risk assessment used in this study builds on previously published models used in DCS research (26,31,33,34). The goal is to estimate the beneficial effects on DCS risk of the active removal of tissue H 2 by injecting H 2 -metabolizing microbes into the intestines of pigs during simulated H 2 dives and to suggest a physiological mechanism for the process called H 2 biochemical decompression (19). The metabolism of H 2 in the intestine is readily followed by measuring the release of CH 4 , the metabolic end product of the microbial metabolism (21)(1)The model presented here differs from earlier models of DCS (26,31,33,34) in that a parameter for the microbial metabolism of H 2 is included. In constructing this model, the microbial metabolism of H 2 was considered to have a direct physiological effect by influencing the gas kinetics. The measure of H 2 metabolism was based on either the total microbial activity injected into the animals (Inj), or as the CH 4 release rate (V CH 4 ) fr...

Probabilistic Modelling for Estimating Gas Kinetics and Decompression Sickness Risk in Pigs During H2 Biochemical Decompression

“…However, the separation of different τ values for uptake and elimination was not validated by the model . Therefore, Fahlman et al, (2001) used one exponential time constant to describe the kinetics, which satisfactorily explained the observed DCS incidence. However, since other DCS modelling efforts (Tikuisis et al, 1991;Himm et al, 1994;Lillo et al, 1997;Parker et al, 1998;Lillo and Parker, 2000) and studies using direct physiological or physical measurements of gas fluxes in animals (D'aoust et al, 1976;Novotny et al, 1990) suggest that the uptake and elimination of gases are asymmetrical, we wanted to perform a critical evaluation of our previous model in an attempt to gain further understanding of gas fluxes in hyperbaria.…”

“…In this model, r is constrained to be 0 or any positive number, and accordingly, r will be set to zero at any time P amb > P tis (Weathersby et al, 1985(Weathersby et al, , 1992Fahlman et al, 2001).…”

“…The microbes metabolize a small but critical fraction of the H 2 dissolved in the tissues of these animals during a hyperbaric H 2 exposure. The volume of dissolved gas eliminated by this process was previously estimated to be on the order of 12% of the total gas burden acquired during a 3 h dive in the pig, or approximately 10 mmol, resulting in a decrease in the DCS incidence by as much as 50% (Kayar et al, 1998;Fahlman, 2001;Fahlman et al, 2001).…”

“…In the study by Fahlman et al (2001), the gas kinetics of H 2 were initially modelled using the data from 109 well-documented hyperbaric exposures of varying durations, pressures, and compression and decompression rates. Initially, the model was designed to estimate two separate time constants for uptake and elimination.…”

“…Of particular importance to the present study, we consider whether the time to a given percent completion of the rate function that we define mathematically corresponds to the same level of physical saturation of the dive subject with gas (Lillo and Parker, 2000). Thus, we have followed the procedures established by others (Lillo et al, 1997;Lillo and Parker, 2000) and separated hyperbaric exposures taken from the study of Fahlman et al (2001). Of the original 109 exposures, only the 89 exposures that were all at one pressure were retained for this analysis.…”