Probabilistic models of the role of oxygen in human decompression sickness
| Autor: | PB Massell, S. S. Survanshi, E. C. Parker, P. K. Weathersby |
|---|---|
| Rok vydání: | 1998 |
| Předmět: |
Air Pressure
medicine.medical_specialty Models Statistical Pulmonary Gas Exchange Physiology business.industry Probabilistic logic Decompression Sickness medicine.disease Noble Gases Risk Assessment Surgery Risk function Oxygen Decompression sickness Kinetics Physiology (medical) medicine Humans Blood Gas Analysis business Neuroscience Blood gas analysis |
| Zdroj: | Journal of Applied Physiology. 84:1096-1102 |
| ISSN: | 1522-1601 8750-7587 |
| Popis: | Probabilistic models of human decompression sickness (DCS) have been successful in describing DCS risk observed across a wide variety of N2-O2dives but have failed to account for the observed DCS incidence in dives with high [Formula: see text] during decompression. Our most successful previous model, calibrated with 3,322 N2-O2dives, 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: [Formula: see text]-based alteration of inert gas kinetics ( model 1) and[Formula: see text] contribution to total inert gas ( model 2). Both modifications statistically significantly improved the fit, and each predicts 90% of the observed DCS incidence in O2dives. The success of models 1 and 2 in improving prediction of DCS occurrence suggests that elevated [Formula: see text]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. |
| Databáze: | OpenAIRE |
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