Abstract
A probabilistic model was used to predict decompression sickness (DCS) outcome in pig (70 and 20 kg), hamster (100 g), rat (220 g) and mouse (20 g) following air saturation dives. The data set included 179 pig, 200 hamster, 360 rat, and 224 mouse exposures to saturation pressures ranging from 1.9–15.2 ATA and with varying decompression rates (0.9–156 ATA • min−1). Single exponential kinetics described the tissue partial pressures (Ptiss) of N2: Ptiss = ∫(Pamb – Ptiss) • τ−1 dt, where Pamb is ambient N2 pressure and τ is a time constant. The probability of DCS [P(DCS)] was predicted from the risk function: P(DCS) = 1−e−r, where r = ∫(PtissN2 − Thr − Pamb) • Pamb–1 dt, and Thr is a threshold parameter. An equation that scaled τ with body mass included a constant (c) and an allometric scaling parameter (n), and the best model included n, Thr, and two c. The final model provided accurate predictions for 58 out of 61 dive profiles for pig, hamster, rat, and mouse. Thus, body mass helped improve the prediction of DCS risk in four mammalian species over a body mass range covering 3 orders of magnitude.
Highlights
Decompression sickness (DCS) is a potential hazard for divers and aviators that is difficult to study in humans without exposing them to potential harm
As data for pigs were available for two separate body mass ranges (20 and 70 kg), two separate Ï„values were estimated for this species
The current study investigated the assumption that DCS risk is governed by inert gas dynamics and can be allometrically scaled between species
Summary
Decompression sickness (DCS) is a potential hazard for divers and aviators that is difficult to study in humans without exposing them to potential harm. Τdetermines the tissue uptake and removal rate, and is a physiologically relevant parameter related to the size (volume, V) of the animal, the solubility of the gas in the blood and tissue (λ), and the cardiac output (Q , L min−1) as: www.nature.com/scientificreports/. Variation in Q causes variation in uptake and removal rates of the inert gas and may alter P(DCS). A number of physiological variables such as body temperature, body mass (Mb), exercise, sex, adiposity, age, Doppler bubble grades, and patent foramen ovale have been suggested to alter P(DCS)[10,11,12,13,14], but among these only Mb has been shown to correlate with P(DCS) within and between species[10,15,16]. As Q scales allometrically with Mb17, DCS risk should scale with Mb unless there are differences in susceptibility between species
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