Probabilistic models of the role of oxygen in human decompression sickness

Probabilistic models of human decompression sickness (DCS) have been successful in describing DCS risk observed across a wide variety of N-2-O-2 dives but have failed to account for the observed DCS incidence in dives with high For, during decompression. Our most successful previous model, calibrated with 3,322 N-2-O-2 dives, predicts only 40% of the observed incidence in dives with 100% O-2 breathing during decompression. We added 1,013 O-2 decompression dives to the calibration data. Fitting the prior model to this expanded data set resulted in only a modest improvement in DCS prediction of O-2 data. Therefore, two O-2-specific modifications were proposed: Po-2-based alteration of inert gas kinetics (model 1) and Po-2 contribution to total inert gas (model 2). Both modifications statistically significantly improved the fit, and each predicts 90% of the observed DCS incidence in Oa dives. The success of models 1 and 2 in improving prediction of DCS occurrence suggests that elevated Po, levels contribute to DCS risk, although less than the equivalent amount of Nz. Both models allow rational optimization of O-2 use in accelerating decompression procedures.