[abstract] A STATISTICAL BUBBLE DYNAMICS MODEL OF DECOMPRESSION SICKNESS RISK FOR DIVING AND ALTITUDE DECOMPRESSIONS

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[abstract] A STATISTICAL BUBBLE DYNAMICS MODEL OF DECOMPRESSION SICKNESS RISK FOR DIVING AND ALTITUDE DECOMPRESSIONS

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Title: [abstract] A STATISTICAL BUBBLE DYNAMICS MODEL OF DECOMPRESSION SICKNESS RISK FOR DIVING AND ALTITUDE DECOMPRESSIONS
Author: Gerth, WA; Vann, RD
Abstract: BACKGROUND: A model for minimum preflight surface intervals that keeps DCS risk within acceptable limits during flying after diving must account for DCS risk from both hyperbaric and hypobaric decompressions, which typically exhibit different DCS onset time distributions. Probabilistic survival models in which cumulative DCS risk is a function of modeled bubble volumes in one or more parallel-perfused gas exchange compartment have been shown to accommodate DCS onset time distributions for either diving or altitude decompressions, but not both in a single model. METHODS: Maximum likelihood was used to optimize the parameters of bubble dynamics (BD) models about hyperbaric decompression data used to develop the USN 1993 Air/N2O2 Algorithm (93LE1) [R8: n = 2383, mean PDCS = 5.8percent] and altitude decompression data from the USAF Armstrong Laboratory (USAFAL) Hypobaric Decompression Sickness Database [AL8: n=1194, mean PDCS=33.6percent]. RESULTS: All models tested achieved maximum log likelihood (LLmax) values about their training data significantly higher than that of a corresponding null model (Table). A three-compartment BD model with Model:No.:LLmax, NULL:LLmax:elastic resistance (Training Data):Parameters:::to bubble growth S4(R8):21:-890.7:-698.7:in each S6(AL8):10:-2007.2:-1714.2:compartment SC(R8+AL8):24:-4112.2:-2607.2:(S4) correlated the R8 data to nearly the LLmax of -697.1 achieved by our implementation of 93LE1 about the same data. The best correlation of the AL8 dataset was provided by a single-compartment BD model (S6) with elastic resistance to bubble growth, bubble nucleation from a size-distributed population of pressure-sensitive pre-formed nuclei, DCS risk defined to be dependent on both bubble volume and bubble number density, and accommodation of compartmental gas elimination by VGE formation. Models S4 and S6 combined correlated the combined R8 + AL8 data, but the longest half-time compartment of model S4 collapsed into the more complex compartment from model S6, yielding a final model (SC) with only 3 compartments. CONCLUSION: BD models are beginning to illuminate why altitude DCS can appear mechanistically different from diving DCS and may provide an algorithm for evaluating DCS risk during flying after diving. (Supported by NOAA-NURP, USSOC, DAN, USAFAL High Altitude Protection Function and LANL Advanced Computing Laboratory).
Description: Undersea and Hyperbaric Medical Society, Inc. (http://www.uhms.org )
URI: http://archive.rubicon-foundation.org/477
Date: 1996

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  • UHMS Meeting Abstracts
    This is a collection of the published abstracts from the Undersea and Hyperbaric Medical Society (UHMS) annual meetings.

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