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 N2-O2 dives but have failed to account for the observed DCS incidence in dives with high PO2 during decompression. Our most successful previous model, calibrated with 3,322 N2-O2 dives, predicts only 40% of the observed incidence in dives with 100% O2 breathing during decompression. We added 1,013 O2 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 O2 data. Therefore, two O2-specific modifications were proposed: PO2-based alteration of inert gas kinetics (model 1) and PO2 contribution to total inert gas (model 2). Both modifications statistically significantly improved the fit, and each predicts 90% of the observed DCS incidence in O2 dives. The success of models 1 and 2 in improving prediction of DCS occurrence suggests that elevated PO2 levels contribute to DCS risk, although less than the equivalent amount of N2. Both models allow rational optimization of O2 use in accelerating decompression procedures.