Are interconnected compartmental models more effective at predicting decompression sickness risk?

Abstract

Interconnected tissue compartmental models having two, three, or four compartments, one or more of which was risk-bearing, have been previously investigated for predicting the probability of decompression sickness (DCS) in compressed gas diving. We extend this prior work under general conditions to multiple risk-bearing compartments while providing exact risk function integrals. Four biophysical models based on different inter-compartmental connections ranging from uncoupled to fully coupled with bidirectional interaction were trained on a large data set to reject unjustified model parameters. We also explore how coupled models (and similar uncoupled models) perform for the prediction of DCS in humans when extrapolated to dives outside of the training set. The most successful model assumes slower tissues influence faster tissues with all compartments bearing risk and provide very good predictions for dives with surface decompression using oxygen.