FiO prediction formula during low flow oxygen therapy in an adult model: a bench study.
(2024) Journal of Clinical Monitoring and Computing — Vol. 38, n° 2, p. 455-461 (2024)
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- Authors
Duprez, Frédéric 
- Abstract
- During low-flow oxygen therapy, the true value of inspired oxygen fraction (FiO) is generally unknown. Knowledge of delivered FiO values may be useful as well as to adjust oxygen therapy, as well as to predict patient deterioration. This study proposes a New FiO Prediction Formula (NFiO) for low-flow oxygenation and compares its predictive value to precedent formulas. In a bench study, the O Flow rate was delivered through a T-piece connected to a dual-compartment artificial lung controlled by a mechanical ventilator. To test the NFiO formula, a set of ventilatory parameters were tested: Tidal Volume was set from 400 to 600 ml, Respiratory Rate (RR) was set from 18 to 30 CPM, Ti/Ttot was set at 0.33 and 0.25, and O flow rates from 3 to 10 L/min. A data acquisition system measured all parameters. To quantify the accuracy of the NFiO compared to other FiO prediction formulas, Bland and Altman agreement analyses were performed. To make use of the Duprez Formula 2018 in clinical practice, we simplified the formula to estimate the FiO during oxygenation at low flow. This NFiO formula makes use of only O Flow Rate and RR. Bias and limits of agreement between predicted FiO and benchtop FiO highlighted consistent differences between different FiO prediction formulas. The NFiO and the Duprez Formula 2018 seemed to be the most accurate formulas, followed by the Vincent Formula, and lastly the Shapiro Formula. A New FiO Prediction Formula was developed using clinical readily available variables (RR and O Flow rate) which showed good accuracy in predicting FiO during oxygenation at low flow.
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Citations
Duprez, F., Mol, B., Lesire, B., Cotils, M., Michotte, J.-B., Mashayekhi, S., & de Terwangne, C. (2024). FiO prediction formula during low flow oxygen therapy in an adult model: a bench study. Journal of Clinical Monitoring and Computing, 38(2), 455-461. https://doi.org/10.1007/s10877-023-01109-y (Original work published 2024)