No abstract

The advantages of automatic control of the fraction of inspired oxygen in neonates have been documented in recently published clinical trials. Many control algorithms are available, but their comparison is missing in the literature. A mathematical model of neonatal oxygen transport could be a useful tool to compare and enhance both automatic control algorithms and manual control of fraction of inspired oxygen. Besides other components, the model of neonatal oxygen transport must include a module linking arterial (SaO2) and peripheral (SpO2) oxygen saturation. The pulse oximeter module must reflect issues of SpO2 measurement typical for clinical practice, such as overestimation of SpO2 over SaO2 documented by several studies, or inaccurate pulse oximeter readings due to high noise. The aim of this study was to describe both the bias between SaO2 and SpO2 and the noise, characteristic for continuous SpO2 recording, for a computer model of oxygenation of a premature infant. The SpO2-SaO2 bias, derived from available clinical data, describes a typical deviation of the SpO2 measurement as a function of the true SaO2 value in three different SaO2 intervals. The SpO2 measurement noise was considered as a random process that affects biased SpO2values at each time point with statistical properties estimated from SpO2 continuous recordings of 5 stable newborns. The results of the study will help to adjust a computer model of neonatal oxygenation to the real situations observed in the clinical practice.

Maintaining a prescribed peripheral oxygen saturation (SpO2) target during routine care of neonates is challenging and inspired fraction of oxygen (FiO2) titration practices differ among caregivers and centers. Algorithms for automatic feedback control of SpO2 are being developed and tested, that would adapt to the changing neonatal organism and better maintain the required SpO2 target range. While clinical data is necessary to validate differences in the titration strategies, a continuous physiological model of oxygenation in neonates would facilitate baseline testing of different approaches, manual or automated. The objective of our study was to enhance a mathematical model of oxygenation of the neonate and to compare the performance of the model with available clinical data. We have implemented the diffusion resistance into the model as well as a variable oxyhemoglobin dissociation relationship and the bias between arterial and peripheral oxygen saturation. Values of model parameters were scaled to fit preterm infant scenarios. The comparison of the clinical data and computer simulations suggest that the model can reliably simulate episodes of oxygen desaturation and describe the relation between ventilation, FiO2and SpO2. It appears that the model may be an effective tool to test manual and automatic FiO2titration strategies.