Is faster better? A randomised crossover study comparing algorithms for closed-loop automatic oxygen control.

Arch Dis Child Fetal Neonatal Ed

Division of Paediatric Epidemiology, Institute of Medical Biostatistics, Epidemiology and Informatics, University Medical Center Mainz, Mainz, Germany.

Published: July 2020

Objective: Closed-loop automatic control (CLAC) of the fractional inspired oxygen (FiO) improved oxygen administration to preterm infants on respiratory support. We investigated whether a revised CLAC algorithm (CLAC, ≤2 FiO adjustments/min), compared with routine manual control (RMC), increased the proportion of time with arterial haemoglobin oxygen saturation measured by pulse oximetry within prespecified target ranges (Target%) while not being inferior to the original algorithm (CLAC: ≤0.3 FiO adjustments/min).

Design: Unblinded randomised controlled crossover study comparing three modes of FiO control in random order for 8 hours each: RMC supported by CLAC was compared with RMC and RMC supported by CLAC. A computer-generated list of random numbers using a block size of six was used for the allocation sequence.

Setting: Two German tertiary university neonatal intensive care units.

Patients: Of 23 randomised patients, 19 were analysed (mean±SD gestational age 27±2 weeks; age at randomisation 24±10 days) on non-invasive (n=18) or invasive (n=1) respiratory support at FiO >0.21.

Main Outcome Measure: Target%.

Results: Mean±SD [95% CI] Target% was 68%±11% [65% to 71%] for CLAC versus 65%±11% [61% to 68%] for CLAC versus 58%±11% [55% to 62%] for RMC. Prespecified hypothesis tests of: (A) superiority of CLAC versus RMC and (B) non-inferiority of CLAC versus CLAC with margin of 5% yielded one-sided p values of <0.001 for both comparisons.

Conclusions: This revised and faster CLAC algorithm was still superior to routine care in infants on respiratory support and not inferior to a previously tested slower algorithm.

Trial Registration Number: NCT03163108.

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Source
http://dx.doi.org/10.1136/archdischild-2019-317029DOI Listing

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