Probabilistic pharmacokinetic models of decompression sickness in humans: Part 2, coupled perfusion-diffusion models

Area of Science:

• Physiology
• Diving Medicine
• Pharmacokinetics

Background:

• Decompression sickness (DCS) occurs when dissolved inert gases form bubbles after pressure reduction.
• Current DCS models often use simple perfusion-limited compartments for gas uptake and elimination.
• Previous research suggests coupled perfusion-diffusion models better represent gas kinetics in animal tissues.

Purpose of the Study:

• To evaluate coupled pharmacokinetic models with diffusion compartments for predicting human DCS incidence.
• To compare the predictive performance of these diffusion-inclusive models against the LEM-NMRI98 gas content model.

Main Methods:

• Applied pharmacokinetic models featuring coupled perfusion-diffusion compartments to human dive data.
• Compared model predictions to observed DCS incidence.
• Benchmarked against the U.S. Navy's LEM-NMRI98 model, which uses uncoupled perfusion-limited compartments.

Main Results:

• Pharmacokinetic models with diffusion components demonstrated superior prediction of DCS for human air, single non-air bounce, and oxygen decompression dives.
• The LEM-NMRI98 model, despite its limitations, remained the best overall descriptor for the complete dataset.
• This indicates the importance of diffusion in modeling gas exchange for specific decompression scenarios.

Conclusions:

• Pharmacokinetic models incorporating diffusion offer enhanced accuracy for predicting DCS in various human diving profiles.
• The findings support the refinement of decompression algorithms by including diffusion kinetics.
• Further research may be needed to optimize models for comprehensive DCS prediction across all dive types.