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The best of both worlds: Refining respiratory phenotypes through combined non-invasive lung monitoring

Pediatric Research volume 95, pages 877–879 (2024)Cite this article

Despite significant advancements in neonatal care, the incidence of bronchopulmonary dysplasia (BPD) in survivors of prematurity remains high.1 Defining BPD is challenging, and current definitions primarily rely on assessment of respiratory support requirements at a single point in time.2 Lung injury is a continuous process; defining BPD based on a measurement at a static point in time will not appreciate the complex development of respiratory insufficiency that occurs over time. To better understand the evolution, and thus better define BPD, the ability to serially and non-invasively monitor lung function at the bedside is required. Amongst the growing number of non-invasive lung monitoring tools, measurement of respiratory system reactance using forced oscillations and lung ultrasound have garnered significant interest within the neonatal community. To date, most of these tools have been explored in isolation.

In this issue of Pediatric Research, Rigotti and colleagues report the novel use of a combination of lung ultrasound and respiratory system reactance (XRS, measured using forced oscillation technique; FOT) to examine in detail the evolution of lung disease.3 The authors performed serial LUS and XRS in 61 infants with a median gestational age of 30 weeks at birth. The measurements were performed in the evolving phase of preterm lung disease, beyond the first week after birth. They explored the utility of these measures by modelling the concurrent respiratory severity score (equal to fraction of inspired oxygen multiplied by mean airway pressure, over 24 h) in relation to LUS and XRS. The key finding was that a multivariate model that included both the lung ultrasound and XRS scores described the respiratory severity score better than each individual parameter alone. The authors concluded that the combination of tools have the potential to monitor the progress of lung disease better than each tool alone. The authors make the intriguing postulation that this combined approach may identify different phenotypes of lung disease based on underlying lung mechanics and aeration patterns. Indeed, they observed high variability in lung ultrasound (LUS) scores corresponding to XRS scores in the normal range. LUS scores rose consistently with increasing levels of respiratory support, but XRS was typically elevated among infants on CPAP or invasively ventilated. Correspondingly, there was substantial variability in XRS scores particularly with high LUS scores. As XRS reflects the proportion of lung regions reached by the oscillatory signal, the authors speculate that normal XRS values with high LUS scores may be more suggestive of interstitial lung disease, such as interstitial oedema or inflammation, with preserved peripheral ventilation. One challenge with such studies is the lack of a gold standard outcome for severity of lung disease. The use of respiratory severity score as a proxy is not specific to the underlying lung pathology and is subject to variability. However, the authors found that infants with both high LUS and XRS scores were most likely to develop bronchopulmonary dysplasia. It is important to note that LUS was not scored blind to the infant’s respiratory support but was blind to the XRS score.

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Authors and Affiliations

  1. Neonatal Research, Murdoch Children’s Research Institute, Melbourne, VIC, Australia

    Arun Sett, Gillian W. C. Foo & David G. Tingay

  2. Joan Kirner Women’s and Children’s, Sunshine Hospital, Melbourne, VIC, Australia

    Arun Sett & Gillian W. C. Foo

  3. Department of Obstetrics, Gynaecology and Newborn Health, University of Melbourne, Melbourne, VIC, Australia

    Arun Sett & Shiraz Badurdeen

  4. Newborn Research Centre, The Royal Women’s Hospital, Melbourne, VIC, Australia

    Arun Sett

  5. Department of Paediatrics, University of Melbourne, Melbourne, VIC, Australia

    David G. Tingay

  6. Melbourne Children’s Global Health, Murdoch Children’s Research Institute, Melbourne, VIC, Australia

    Shiraz Badurdeen

  7. Department of Paediatrics, Mercy Hospital for Women’s, Melbourne, VIC, Australia

    Shiraz Badurdeen

Authors
  1. Arun Sett
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  2. Gillian W. C. Foo
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  3. David G. Tingay
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  4. Shiraz Badurdeen
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Contributions

All authors contributed equally to review of the original submission and structure of the Editorial, with agreed paragraph lead authors shared equally. All authors contributed to redrafting the manuscript.

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Correspondence to Arun Sett.

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Funding

The authors are supported by the Victorian Government Operational Infrastructure Support Program (Melbourne, Australia). DGT is supported by a National Health and Medical Research Council Leadership Level 1 Investigator Grant (Grant ID 2008212). SB is supported by a Melbourne Children’s Global Health Postdoctoral Fellowship. AS is supported by a research grant from the Australian Society of Ultrasound in Medicine and PhD scholarship from the Centre of Research Excellence in Newborn Medicine, Victoria.

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The authors declare no competing interests.

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Sett, A., Foo, G.W.C., Tingay, D.G. et al. The best of both worlds: Refining respiratory phenotypes through combined non-invasive lung monitoring. Pediatr Res 95, 877–879 (2024). https://doi.org/10.1038/s41390-023-02910-w

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