Predicting Pulmonary O2 Toxicity: A New Look at the Unit Pulmonary Toxicity Dose

Abstract

Pulmonary oxygen toxicity becomes a concern in U.S. Navy operations during long saturation dives or decompression procedures and during treatment of difficult cases of decompression sickness. Currently, the Unit Pulmonary Toxicity Dose (UPTD) concept based on changes in vital capacity is used as a guided for prediction the risk associated with cumulative O2 exposures. In this report, we review the general model which gave rise to the UPTD, included a current summary of available vital capacity data, and perform a quantitative statistical analysis to explicitly test parameters in the model as well as to evaluate the contribution of individual variability to this index. A simplified model relating partial pressure oxygen, time of exposure, and predicted change in vital capacity is proposed: % deltaVC = -0.011 (PO2 - 0.5) (time) where partial pressure oxygen is given in ATA and time in minutes. As with the UPTD, the effect of cumulative exposures can be calculated by summing the effect predicted at each level of partial pressure oxygen exposure. We discuss the limitations of changes in VC as the index of pulmonary O2 toxicity. Individual susceptability is the single largest source of variability, accounting for 35% of the uncertainty of any prediction.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1985
Accession Number
ADA177439

Entities

People

  • Andrea L. Harabin
  • Edward T. Flynn
  • Louis D. Homer
  • Paul K. Weathersby

Organizations

  • Naval Medical Research Center

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Airway Management
  • Biomedical Research
  • Cardiovascular Physiological Phenomena
  • Cells
  • Decompression
  • Decompression Sickness
  • Embolism And Thrombosis
  • Governments
  • Macrophages
  • Measurement
  • Medical Personnel
  • Navy
  • Pain
  • Respiratory Physiological Phenomena
  • Rodents
  • Saturation

Readers

  • Regression Analysis.
  • Systems Analysis and Design
  • Underwater engineering and Marine Technology.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference