title: A new class of biophysical models for predicting the probability of decompression sickness in scuba diving.
abstract: Interconnected compartmental models have been used for decades in physiology and medicine to account for the observed multi-exponential washout kinetics of a variety of solutes (including inert gases) both from single tissues and from the body as a whole. They are used here as the basis for a new class of biophysical probabilistic decompression models. These models are characterized by a relatively well-perfused, risk-bearing, central compartment and one or two non-risk-bearing, relatively poorly perfused, peripheral compartment(s). The peripheral compartments affect risk indirectly by diffusive exchange of dissolved inert gas with the central compartment. On the basis of the accuracy of their respective predictions beyond the calibration regime, the three-compartment interconnected models were found to be significantly better than the two-compartment interconnected models. The former, on the basis of a number of criteria, was also better than a two-compartment parallel model used for comparative purposes. In these latter comparisons, the models all had the same number of fitted parameters (four), were based on linear kinetics, had the same risk function, and were calibrated against the same dataset. The interconnected models predict that inert gas washout during decompression is relatively fast, initially, but slows rapidly with time compared with the more uniform washout rate predicted by an independent parallel compartment model. If empirically verified, this may have important implications for diving practice.
authors: Dept. of Chemistry and the Guelph-Waterloo Physics Institute, Univ. of Guelph, Guelph, Ontario, Canada N1G 2W1. goldman@chembio.uoguelph.ca
authors: Saul
authors: S
authors: Goldman
mesh_terms: D055592:Biophysical Phenomena; D001703:Biophysics; D003665:Decompression Sickness / Q000209:etiology*; D004242:Diving / Q000009:adverse effects*; D006801:Humans; D008954:Models, Biological; D015233:Models, Statistical; D011237:Predictive Value of Tests; D012307:Risk Factors