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Automated oxygen control in preterm infants, how does it work and what to expect: a narrative review
Citation
Salverda, HH and Cramer, SJE and Witlox, RSGM and Dargaville, PA and te Pas, AB, Automated oxygen control in preterm infants, how does it work and what to expect: a narrative review, Archives of Disease in Childhood. Fetal and Neonatal Edition. pp. F1-F7. ISSN 1359-2998 (2020) [Refereed Article]
Copyright Statement
Copyright 2020 Author(s) (or their employer(s))
DOI: doi:10.1136/archdischild-2020-318918
Abstract
Objective: To provide guidance to clinicians seeking to comprehend automated oxygen control and possibly introduce this technology in their practice.
Method: A narrative review of the commercially available devices using different algorithms incorporating rule-based, proportional-integral-derivative and adaptive concepts are described and explained. An overview of how they work and, if available, the clinical effect is given.
Results: All algorithms have shown a beneficial effect on the proportion of time that oxygen saturation is within target range, and a decrease in hyperoxia and severe hypoxia. Automated oxygen control may also reduce the workload for bedside staff. There is concern that such devices could mask clinical deterioration, however this has not been reported to date.
Conclusions: So far, trials involving different algorithms are heterogenous in design and no head-to-head comparisons have been made, making it difficult to differentiate which algorithm is most effective and what clinicians can expect from algorithms under certain conditions.
Item Details
Item Type: | Refereed Article |
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Keywords: | intensive care, neonatology, paediatric practice, respiratory, technology |
Research Division: | Biomedical and Clinical Sciences |
Research Group: | Paediatrics |
Research Field: | Paediatrics not elsewhere classified |
Objective Division: | Health |
Objective Group: | Specific population health (excl. Indigenous health) |
Objective Field: | Neonatal and child health |
UTAS Author: | Dargaville, PA (Professor Peter Dargaville) |
ID Code: | 140313 |
Year Published: | 2020 |
Web of Science® Times Cited: | 16 |
Deposited By: | Menzies Institute for Medical Research |
Deposited On: | 2020-08-06 |
Last Modified: | 2022-08-25 |
Downloads: | 0 |
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