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Maximum likelihood analysis of air and HeO2 dives
P Tikuisis1, P K Weathersby, R Y Nishi
1Defence and Civil Institute of Environmental Medicine, North York, Ont., Canada.
Aviation, Space, and Environmental Medicine
|May 1, 1991
Summary
This study analyzed 1,949 dives to predict decompression sickness (DCS) risk. The best model indicates most DCS risk occurs post-dive, particularly from nitrogen in slow-acting gas compartments.
Area of Science:
- Diving Physiology
- Hyperbaric Medicine
- Biostatistics
Background:
- Decompression sickness (DCS) remains a significant risk in diving.
- Predictive models for DCS are crucial for diver safety.
- Previous models often simplify gas kinetics and solubility effects.
Purpose of the Study:
- To develop and validate a predictive model for DCS incidence.
- To identify key factors contributing to DCS risk in air and HeO2 dives.
- To compare the predictive performance of different gas uptake models.
Main Methods:
- Maximum likelihood analysis applied to 1,949 man-dives (1,041 air, 908 HeO2).
- Testing of single exponential gas uptake models in one and two compartments.
- Utilizing a potential gas volume criterion, considering solubilities and partial pressures.
Main Results:
- A two-compartment model distinguishing kinetic differences (time constants) best predicted DCS.
- The majority of DCS risk was identified as occurring post-surfacing.
- The slow compartment (approx. 420 min time constant) was the primary site of risk.
- Nitrogen contributed approximately twice the risk of helium in HeO2 dives.
Conclusions:
- Diving decompression models should prioritize kinetic differences over gas solubilities.
- Post-surfacing monitoring and management are critical for DCS prevention.
- Understanding the differential risk of nitrogen and helium is vital for optimizing breathing gas mixtures.