Accession Number:

AD1101527

Title:

A Probabilistic Model of Altitude Decompression Sickness Based on the 3RUT-MB Model of Gas Bubble Evolution in Perfused Tissue

Descriptive Note:

Technical Report,01 Oct 2004,30 Sep 2017

Corporate Author:

Navy Experimental Diving Unit Panama City United States

Report Date:

2018-01-19

Pagination or Media Count:

123.0

Abstract:

We here describe a probabilistic model of DCS occurrence able to accommodate the influences of pressure, changing inspired inert gas, oxygen breathing, and exercise in profiles of arbitrary complexity. The model is a time-dependent covariate survival model in which the risks of DCS during an exposure are determined as functions of the prevailing volumes and profusions of gas bubbles in a perfusion-limited gas exchange compartment. The bubbles vary in volume by diffusion-limited exchange of gas between the bubbles and their surroundings according to an implementation of a three region unstirred tissue model of gas bubble evolution elaborated to accommodate the influences of exercise and oxygen breathing on compartmental gas exchange and bubble nucleation. Parameters in the model were fit with maximum likelihood techniques to training data comprising detailed descriptions of actual human decompressions and their observed DCS outcomes in 2598 man-exposures to hypobaric pressures completed in a wide variety of NASA,NASA-sponsored, and U.S. Air Force chamber trials. The model underestimates the observed DCS occurrence density in the first four hours after start of the last decompression and consequently fails to fit the data. However, when model estimates of DCS occurrence are made with planned times at altitude, no tactual times that are shorter than planned due to occurrence of DCS, the model fits data from 84 of the 117 groups in the training data to within a chi-square P0.05. In this form, the model is shown to perform better than other published models on a variety of data subset collections that is much more diverse than can be handled by any one of the other models.

Subject Categories:

  • Stress Physiology

Distribution Statement:

APPROVED FOR PUBLIC RELEASE