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Related Experiment Video

Updated: Jul 12, 2026

A Model to Simulate Clinically Relevant Hypoxia in Humans

A Model to Simulate Clinically Relevant Hypoxia in Humans

Published on: December 22, 2016

Testing of hypotheses about altitude decompression sickness by statistical analyses

H D Van Liew¹, M E Burkard, J Conkin

¹Department of Physiology, University at Buffalo, SUNY 14214, USA.

Undersea & Hyperbaric Medicine : Journal of the Undersea and Hyperbaric Medical Society, Inc

|December 1, 1996

Summary

This study refines decompression sickness risk models for exercising individuals at altitude. Accounting for ascent rate reveals a rise-and-decay risk pattern, improving statistical fit and aligning with theoretical expectations.

Keywords:

NASA Center JSC NASA Discipline Environmental Health

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Area of Science:

Physiology
Aerospace Medicine
Statistical Modeling

Background:

Decompression sickness (DCS) risk at altitude is influenced by environmental pressure, exposure duration, and pre-breathing oxygen.
Previous models suggested a linear increase in instantaneous DCS risk with continued altitude exposure.
Understanding DCS mechanisms is crucial for safe ascent and descent protocols.

Purpose of the Study:

To statistically analyze forced-descent decompression sickness in exercising subjects.
To incorporate the rate of ascent as an explanatory variable in DCS risk models.
To evaluate alternative risk accrual models beyond linear increase.

Main Methods:

Extended a previous statistical analysis of DCS using a subset of data.
Introduced 'rate of ascent' as a new explanatory variable.
Compared a linear risk accrual model with a rise-and-decay risk model using log likelihood.

Main Results:

The inclusion of ascent rate improved the statistical model fit for the data subset.
Accounting for ascent rate allowed a rise-and-decay risk model to significantly outperform the linear model.
Log likelihood increased by 37 log units with the rise-and-decay model, indicating a better fit.

Conclusions:

A more representative dataset and accounting for ascent rate variability revealed a rise-and-decay DCS risk pattern.
This observed pattern aligns with theoretical expectations and prior observations of DCS mechanisms.
The findings necessitate a revision of current DCS risk models for altitude exposure.