Abstract

Patients undergoing hyperbaric oxygen therapy and divers engaged in underwater activity are at risk of central nervous system oxygen toxicity. An algorithm for predicting CNS oxygen toxicity in active underwater diving has been published previously, but not for humans at rest. Using a procedure similar to that employed for the derivation of our active diving algorithm, we collected data for exposures at rest, in which subjects breathed hyperbaric oxygen while immersed in thermoneutral water at 33°C (n = 219) or in dry conditions (n = 507). The maximal likelihood method was employed to solve for the parameters of the power equation. For immersion, the CNS oxygen toxicity index is KI = t2 × PO210.93, where the calculated risk from the Standard Normal distribution is ZI = [ln(KI0.5) – 8.99)]/0.81. For dry exposures this is KD = t2 × PO212.99, with risk ZD = [ln(KD0.5) – 11.34)]/0.65. We propose a method for interpolating the parameters at metabolic rates between 1 and 4.4 MET. The risk of CNS oxygen toxicity at rest was found to be greater during immersion than in dry conditions. We discuss the prediction properties of the new algorithm in the clinical hyperbaric environment, and suggest it may be adopted for use in planning procedures for hyperbaric oxygen therapy and for rest periods during saturation diving.

Highlights

  • Patients undergoing hyperbaric oxygen (HBO) therapy and divers engaged in underwater activity breathe pure oxygen at greater than atmospheric pressure

  • In the power equation for the rat, that as metabolic rate increases there is a linear decrease in the power of the partial pressure of oxygen (PO2) and in ln(Kc) (Arieli, 2003)

  • We chose to separate immersed from dry exposures when solving for the parameters of the power equation

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Summary

Introduction

Patients undergoing hyperbaric oxygen (HBO) therapy and divers engaged in underwater activity breathe pure oxygen at greater than atmospheric pressure. In such situations, there is always an imminent risk of central nervous system oxygen toxicity (CNS-OT). We previously proposed the power equation and exponential recovery algorithm to predict the risk of CNS-OT in an active diver expending energy at 4.4 metabolic equivalents of task (MET) (Arieli et al, 2002). In further studies (Arieli, 2003, 2019), we elaborated ways of alleviating the risk. The power equation for underwater activity takes the form:

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