OxyGenie®: Inspired Oxygen Control
In 2016, SLE saw an Auto O2 system which really excited us. It was responsive, safe and most importantly, effective. It managed to maximise the time SpO2 spent within a target range of 5%; it looked at many different inputs to determine an action; it analysed the inputs every second and could make as many changes as necessary and it reacted well when it experienced sudden changes in baby saturation. Additionally, it had been shown to virtually eliminate prolonged episodes of both hyperoxaemia, and hypoxaemia [3]. We have incorporated this new system into a software module for the SLE6000 and we’re calling it OxyGenie®, because it could make your wish for a stable saturation come true!
Why Auto O2?
Oxygen is one of the drugs most frequently used in neonates, often with the highest concentrations given to those with the least developed defence mechanisms to its potentially toxic side effects. Even minor variations in blood oxygen levels may affect longer term outcomes such as mortality, retinopathy of prematurity (ROP) or necrotising enterocolitis (NEC) as has been shown in a number of recent studies [1]. In addition to the importance of closely maintaining an effective baseline target range, avoiding intermittent hypoxaemia or hyperoxaemia (e.g. a saturation of <80% or >95%) is equally important [2].
Decrease workloads
With the high workload medical staff caring for preterm infants often face, an automatic O2 system that can help reduce the time spent adjusting the ventilator and allowing staff to spend more time caring for the patient would be invaluable. The properties required for such control, however, are extensive: they should be able to respond to both a gradual change in oxygen requirements and sudden hypoxaemia, and should also be capable of avoiding the build-up of increasing fluctuations in FiO2/SpO2 during periods with changeable SpO2 values. Infants with significant lung disease also need the algorithm to be responsive to their requirements. The introduction of a reliable, accurate controller for oxygen would give a reduction in manual interventions enabling an improvement in efficiency of care.
OxyGenie®: Reducing your Workload
Reactive Algorithm
Developed at the University of Tasmania, in collaboration with the Royal Hobart Hospital, the OxyGenie® software module uses a Proportional/Integral/Derivative algorithm which makes it responsive to SpO2 deviations, allowing it to recognise serious instability and then be able to safely and quickly counteract it
Peace of Mind
The new algorithm incorporates additional software that has a different response depending upon the severity of lung disease, plus target range attenuation and Severinghaus compensation. The overall design of the software allows it to respond smoothly and effectively to both gradual and sudden changes in SpO2.
SLE6000 Integration
Various software and hardware modules can be added to the SLE6000 during production or at a later date as an upgrade. To add OxyGenie® to an SLE6000 requires the OxyGenie® software module plus the SpO2 module. Integrating it into the SLE6000 also gives the caregiver a chance to observe the SpO2 trend against the FiO2 trend on the same time scales allowing easy correlation between cause and effect. What’s more, the integration is so seamless that only two additional controls are needed on the SLE6000’s Lunar™ interface. There’s one to set your target range (default 91-95%) and another to turn OxyGenie® on and off.
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References
1 Saugstad OD, Aune D. Optimal oxygenation of extremely low birth weight infants: a meta-analysis and systematic review of the oxygen saturation target studies. Neonatology 2014;105:55–63.
2 Poets CF, Roberts RS, Schmidt B, et al. Association between intermittent hypoxemia or bradycardia and late death or disability in extremely preterm infants. JAMA 2015;314:595–603.
3 Plottier GK, Wheeler KI, Ali SKM, Sadeghi Fathabadi O, Jayakar R, Gale TJ, Dargaville PA. Clinical evaluation of a novel adaptive algorithm for automated control of oxygen therapy in preterm infants on non-invasive respiratory support. Arch Dis Child Fetal Neonatal Ed 2017; 102: F37-F43.
4 Peter A Dargaville, Omid Sadeghi Fathabadi, Gemma K Plottier, Kathleen Lim, Kevin I Wheeler, Rohan Jayakar, Timothy J Gale Development and preclinical testing of an adaptive algorithm for automated control of inspired oxygen in the preterm infant Arch Dis Child Fetal Neonatal Ed 2016;0:F1–F6.
5 Clarke, A., Yeomans, E., Elsayed, K., Medhurst, A., Berger, P., Skuza, E. and Tan, K. (2015) A randomised crossover trial of clinical algorithm for oxygen saturation targeting in preterm infants with frequent desaturation episodes. Neonatology, 107 (2), 130-136.