In:
Archives of Disease in Childhood - Fetal and Neonatal Edition, BMJ, Vol. 107, No. 1 ( 2022-01), p. 39-44
Abstract:
To evaluate the performance of a rapidly responsive adaptive algorithm (VDL1.1) for automated oxygen control in preterm infants with respiratory insufficiency. Design Interventional cross-over study of a 24-hour period of automated oxygen control compared with aggregated data from two flanking periods of manual control (12 hours each). Setting Neonatal intensive care unit. Participants Preterm infants receiving non-invasive respiratory support and supplemental oxygen; median birth gestation 27 weeks (IQR 26–28) and postnatal age 17 (12–23) days. Intervention Automated oxygen titration with the VDL1.1 algorithm, with the incoming SpO 2 signal derived from a standard oximetry probe, and the computed inspired oxygen concentration (FiO 2 ) adjustments actuated by a motorised blender. The desired SpO 2 range was 90%–94%, with bedside clinicians able to make corrective manual FiO 2 adjustments at all times. Main outcome measures Target range (TR) time (SpO 2 90%–94% or 90%–100% if in air), periods of SpO 2 deviation, number of manual FiO 2 adjustments and oxygen requirement were compared between automated and manual control periods. Results In 60 cross-over studies in 35 infants, automated oxygen titration resulted in greater TR time (manual 58 (51–64)% vs automated 81 (72–85)%, p 〈 0.001), less time at both extremes of oxygenation and considerably fewer prolonged hypoxaemic and hyperoxaemic episodes. The algorithm functioned effectively in every infant. Manual FiO 2 adjustments were infrequent during automated control (0.11 adjustments/hour), and oxygen requirements were similar (manual 28 (25–32)% and automated 26 (24–32)%, p=0.13). Conclusion The VDL1.1 algorithm was safe and effective in SpO 2 targeting in preterm infants on non-invasive respiratory support. Trial registration number ACTRN12616000300471.
Type of Medium:
Online Resource
ISSN:
1359-2998
,
1468-2052
DOI:
10.1136/archdischild-2020-321538
Language:
English
Publisher:
BMJ
Publication Date:
2022
detail.hit.zdb_id:
2188490-0
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