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Lung ultrasound score as a tool to predict severity of bronchopulmonary dysplasia in neonates born ≤25 weeks of gestational age

Journal of Perinatology volume 44, pages 273–279 (2024)Cite this article

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Abstract

Objective

The primary aim was to evaluate whether the addition of the posterior lung aided in diagnostic accuracy of predicting bronchopulmonary dysplasia (BPD) vs moderate-severe BPD (msBPD); the secondary aim was to explore the diagnostic accuracy of two protocols for BPD vs msBPD.

Study design

This was a single-center prospective observational study. Preterm infants with a gestational age ≤ 25 weeks were included. Two LUS score protocols were evaluated on the 14th day of life (DOL): (A) evaluating the anterolateral (LUS score-al) lung and (B) the anterolateral combined with posterior (LUS score-alp) lung. The LUS score range for the two protocols was 0–32 and 0–48, respectively.

Results

A total of eighty-nine infants were enrolled. Both the LUS score-al and LUS score-alp were higher in neonates developing BPD and msBPD than in the rest of the cohort (LUS score-al 24 (23,26) vs 22 (20,23); LUS score-alp 36 (34,39) vs 28 (25,32)) (LUS score-al 25 (24,26) vs 23 (21,24); LUS score-alp 40 (39,40) vs 34 (28,36)). The LUS score-al on the 14th DOL showed a moderate diagnostic accuracy to predict BPD and msBPD (AUC 95% CI: 0.797 [0.697–0.896]; 0.811[0.713–0.909]), while the LUS score-alp significantly improved diagnostic accuracy of BPD and msBPD (AUC 95% CI: 0.902 [0.834–0.970]; 0.922 [0.848–0.996]). A cutoff of 25 points in the LUS score-al provided a sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio of 76.9%, 79.4%, 3.7, and 0.3 respectively to predict msBPD. Meanwhile, that of 39 points in the LUS score-alp provided a sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio of 81%, 98.4%, 50.5 and 0.19 to predict msBPD, respectively.

Conclusions

The LUS score on the 14th DOL can predict BPD and msBPD with moderate diagnostic accuracy. Apart from that, scanning posterior enhanced diagnostic accuracy.

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Fig. 1: Probe used in lung ultrasound scanning.
Fig. 2: Description of the lung ultrasound Score.
Fig. 3: ROC curves for prediction of BPD and msBPD using LUS score.

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Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

References

  1. Liu J, Copetti R, Sorantin E, Lovrenski J, Rodriguez-Fanjul J, Kurepa D et al. Protocol and guidelines for point-of-care lung ultrasound in diagnosing neonatal pulmonary diseases based on international expert consensus. J Vis Exp. 2019; 145. https://doi.org/10.3791/58990.

  2. Kurepa D, Zaghloul N, Watkins L, Liu J. Neonatal lung ultrasound exam guidelines. J Perinatol. 2018;38:11–22. https://doi.org/10.1038/jp.2017.140.

    Article  CAS  PubMed  Google Scholar 

  3. Brusa G, Savoia M, Vergine M, Bon A, Copetti R, Cattarossi L. Neonatal lung sonography: interobserver agreement between physician interpreters with varying levels of experience. J Ultrasound Med. 2015;34:1549–54. https://doi.org/10.7863/ultra.15.14.08016.

    Article  PubMed  Google Scholar 

  4. Brat R, Yousef N, Klifa R, Reynaud S, Shankar Aguilera S, et al. Lung ultrasonography score to evaluate oxygenation and surfactant need in neonates treated with continuous positive airway pressure. JAMA Pediatr. 2015;169:e151797. https://doi.org/10.1001/jamapediatrics.2015.1797.

    Article  PubMed  Google Scholar 

  5. Raimondi F, Cattarossi L, Copetti R. International perspectives: point-of-care chest ultrasound in the neonatal intensive care unit: an Italian perspective. NeoReviews. 2014;15:e2–e6. https://doi.org/10.1542/neo.15-1-e2.

    Article  Google Scholar 

  6. Perri A, Riccardi R, Iannotta R, Di Molfetta DV, Arena R, Vento G, et al. Lung ultrasonography score versus chest X-ray score to predict surfactant administration in newborns with respiratory distress syndrome. Pediatr Pulmonol. 2018;53:1231–6. https://doi.org/10.1002/ppul.24076.

    Article  PubMed  Google Scholar 

  7. De Martino L, Yousef N, Ben-Ammar R, Raimondi F, Shankar-Aguilera S, De Luca D. Lung ultrasound score predicts surfactant need in extremely preterm neona.tes. Pediatrics. 2018;142:e20180463. https://doi.org/10.1542/peds.2018-0463.

    Article  PubMed  Google Scholar 

  8. Alonso-Ojembarrena A, Lechuga-Sancho AM, Morales-Arandojo P, Acuñas-Soto S, López-de-Francisco R, Lubián-López SP. Lung ultrasound score and diuretics in preterm infants born before 32 weeks: a pilot study. Pediatr Pulmonol. 2020;55:3312–8. https://doi.org/10.1002/ppul.25098.

    Article  PubMed  Google Scholar 

  9. Soliman RM, Elsayed Y, Said RN, Abdulbaqi AM, Hashem RH, Aly H. Prediction of extubation readiness using lung ultrasound in preterm infants. Pediatr Pulmonol. 2021;56:2073–80. https://doi.org/10.1002/ppul.25383.

    Article  PubMed  Google Scholar 

  10. El Amrousy D, Elgendy M, Eltomey M, Elmashad AE. Value of lung ultrasonography to predict weaning success in ventilated neonates. Pediatr Pulmonol. 2020;55:2452–6. https://doi.org/10.1002/ppul.24934.

    Article  PubMed  Google Scholar 

  11. Raimondi F, Migliaro F, Corsini I, Meneghin F, Dolce P, Pierri L, et al. Lung ultrasound score progress in neonatal respiratory distress syndrome. Pediatrics. 2021;147:e2020030528. https://doi.org/10.1542/peds.2020-030528.

    Article  PubMed  Google Scholar 

  12. Oulego-Erroz I, Alonso-Quintela P, Terroba-Seara S, Jiménez-González A, Rodríguez-Blanco S. Early assessment of lung aeration using an ultrasound score as a biomarker of developing bronchopulmonary dysplasia: a prospective observational study. J Perinatol. 2021;41:62–68. https://doi.org/10.1038/s41372-020-0724-z.

    Article  CAS  PubMed  Google Scholar 

  13. Loi B, Vigo G, Baraldi E, Raimondi F, Carnielli VP, Mosca F, et al. Lung ultrasound to monitor extremely preterm infants and predict bronchopulmonary dysplasia. a multicenter longitudinal cohort study. Am J Respir Crit Care Med. 2021;203:1398–409. https://doi.org/10.1164/rccm.202008-3131OC.

    Article  CAS  PubMed  Google Scholar 

  14. Raimondi F, Migliaro F, Sodano A, Ferrara T, Lama S, Vallone G, et al. Use of neonatal chest ultrasound to predict noninvasive ventilation failure. Pediatrics. 2014;134:e1089–94. https://doi.org/10.1542/peds.2013-3924.

    Article  PubMed  Google Scholar 

  15. Lui K, Lee SK, Kusuda S, Adams M, Vento M, Reichman B, et al. International Network for Evaluation of Outcomes (iNeo) of neonates investigators. Trends in outcomes for neonates born very preterm and very low birth weight in 11 high-income countries. J Pediatr. 2019;215:32–40.e14. https://doi.org/10.1016/j.jpeds.2019.08.020.

    Article  PubMed  Google Scholar 

  16. Cheong JLY, Doyle LW. An update on pulmonary and neurodevelopmental outcomes of bronchopulmonary dysplasia. Semin Perinatol. 2018;42:478–84. https://doi.org/10.1053/j.semperi.2018.09.013.

    Article  PubMed  Google Scholar 

  17. Ibrahim J, Bhandari V. The definition of bronchopulmonary dysplasia: an evolving dilemma. Pediatr Res. 2018;84:586–8. https://doi.org/10.1038/s41390-018-0167-9.

    Article  PubMed  Google Scholar 

  18. Onland W, Cools F, Kroon A, Rademaker K, Merkus MP, Dijk PH, et al. Effect of hydrocortisone therapy initiated 7 to 14 days after birth on mortality or bronchopulmonary dysplasia among very preterm infants receiving mechanical ventilation: a randomized clinical trial. JAMA. 2019;321:354–63. https://doi.org/10.1001/jama.2018.21443.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Alvarez-Fuente M, Moreno L, Lopez-Ortego P, Arruza L, Avila-Alvarez A, Muro M, et al. Exploring clinical, echocardiographic and molecular biomarkers to predict bronchopulmonary dysplasia. PLoS ONE. 2019;14:e0213210. https://doi.org/10.1371/journal.pone.0213210.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Álvarez-Fuente M, Moreno L, Mitchell JA, Reiss IK, Lopez P, Elorza D, et al. Preventing bronchopulmonary dysplasia: new tools for an old challenge. Pediatr Res. 2019;85:432–41. https://doi.org/10.1038/s41390-018-0228-0.

    Article  PubMed  Google Scholar 

  21. Förster K, Sass S, Ehrhardt H, Mous DS, Rottier RJ, Oak P, et al. Early identification of bronchopulmonary dysplasia using novel biomarkers by proteomic screening. Am J Respir Crit Care Med. 2018;197:1076–80. https://doi.org/10.1164/rccm.201706-1218LE.

    Article  PubMed  Google Scholar 

  22. Rivera L, Siddaiah R, Oji-Mmuo C, Silveyra GR, Silveyra P. Biomarkers for bronchopulmonary dysplasia in the preterm infant. Front Pediatr. 2016;4:33. https://doi.org/10.3389/fped.2016.00033.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Alonso-Ojembarrena A, Serna-Guerediaga I, Aldecoa-Bilbao V, Gregorio-Hernández R, Alonso-Quintela P, Concheiro-Guisán A, et al. The predictive value of lung ultrasound scores in developing bronchopulmonary dysplasia: a prospective multicenter diagnostic accuracy study. Chest. 2021;160:1006–16. https://doi.org/10.1016/j.chest.2021.02.066.

    Article  PubMed  Google Scholar 

  24. Alonso-Ojembarrena A, Lubián-López SP. Lung ultrasound score as early predictor of bronchopulmonary dysplasia in very low birth weight infants. Pediatr Pulmonol. 2019;54:1404–9.

    Article  PubMed  Google Scholar 

  25. Louis D, Belen K, Farooqui M, Idiong N, Amer R, Hussain A, et al. Prone versus supine position for lung ultrasound in neonates with respiratory distress. Am J Perinatol. 2021;38:176–81.

    Article  PubMed  Google Scholar 

  26. Abdelmawla M, Louis D, Narvey M, Elsayed Y. A lung ultrasound severity score predicts chronic lung disease in preterm infants. Am J Perinatol. 2019;36:1357–61. https://doi.org/10.1055/s-0038-1676975.

    Article  PubMed  Google Scholar 

  27. Higgins RD, Jobe AH, Koso-Thomas M, Bancalari E, Viscardi RM, Hartert TV, et al. Bronchopulmonary dysplasia: executive summary of a workshop. J Pediatr. 2018;197:300–8.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Sweet DG, Carnielli V, Greisen G, Hallman M, Ozek E, Te Pas A, et al. European consensus guidelines on the management of respiratory distress syndrome - 2019 update. Neonatology. 2019;115:432–50. https://doi.org/10.1159/000499361.

    Article  PubMed  Google Scholar 

  29. Liu J, Guo G, Kurepa D, Volpicelli G, Sorantin E, Lovrenski J, et al. Specification and guideline for technical aspects and scanning parameter settings of neonatal lung ultrasound examination. J Matern Fetal Neonatal Med. 2022;35:1003–16. https://doi.org/10.1080/14767058.2021.1940943.

    Article  CAS  PubMed  Google Scholar 

  30. Mercurio G, D’Arrigo S, Moroni R, Grieco DL, Menga LS, Romano A, et al. Diaphragm thickening fraction predicts noninvasive ventilation outcome: a preliminary physiological study. Crit Care. 2021;25:219. https://doi.org/10.1186/s13054-021-03638-x.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Martínez-Camblor P, Pardo-Fernández JC. The Youden index in the generalized receiver operating characteristic curve context. Int J Biostat (2019);15:/j/ijb.2019.15.issue-1/ijb-2018-0060 /ijb-2018-0060.xml. https://doi.org/10.1515/ijb-2018-0060.

  32. Mojoli F, Bouhemad B, Mongodi S, Lichtenstein D. Lung ultrasound for critically Ill patients. Am J Respir Crit Care Med. 2019;199:701–14. https://doi.org/10.1164/rccm.201802-0236CI.

    Article  PubMed  Google Scholar 

  33. Zong H, Huang Z, Zhao J, Lin B, Fu Y, Lin Y, et al. The value of lung ultrasound score in neonatology. Front Pediatr. 2022;10:791664. https://doi.org/10.3389/fped.2022.791664.

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  34. Woods PL, Stoecklin B, Woods A, Gill AW. Early lung ultrasound affords little to the prediction of bronchopulmonary dysplasia. Arch Dis Child Fetal Neonatal Ed. 2021;106:657–62. https://doi.org/10.1136/archdischild-2020-320830.

    Article  PubMed  Google Scholar 

  35. Wilson SM, Olver RE, Walters DV. Developmental regulation of lumenal lung fluid and electrolyte transport. Respir Physiol Neurobiol. 2007;159:247–55. https://doi.org/10.1016/j.resp.2007.10.004.

    Article  CAS  PubMed  Google Scholar 

  36. Steinhorn R, Davis JM, Göpel W, Jobe A, Abman S, Laughon M, et al. Chronic pulmonary insufficiency of prematurity: developing optimal endpoints for drug development. J Pediatr. 2017;191:15–21.e1. https://doi.org/10.1016/j.jpeds.2017.08.006.

    Article  PubMed  Google Scholar 

  37. Liu X, Lv X, Jin D, Li H, Wu H. Lung ultrasound predicts the development of bronchopulmonary dysplasia: a prospective observational diagnostic accuracy study. Eur J Pediatr. 2021;180:2781–9. https://doi.org/10.1007/s00431-021-04021-2.

    Article  PubMed  Google Scholar 

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Acknowledgements

We would like to thank the staff who participated in this study.

Funding

This study is supported by Shenzhen Science and Technology Program (JCYJ20190809170009528 to CX), Shenzhen Fund for Guangdong Provincial High-level Clinical Key Specialties (SZGSP009) and Sanming Project of Medicine in Shenzhen (SZSM201612045).

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Authors and Affiliations

  1. Neonatal Intensive Care Unit, Affiliated Shenzhen Maternity & Child Healthcare Hospital, Southern Medical University, Shenzhen, 518028, China

    Haifeng Zong, Zhifeng Huang, Yongping Fu, Xueyu Chen, Yanliang Yu, Yingsui Huang, Yichu Huang, Hongyan Sun & Chuanzhong Yang

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Contributions

Each author made substantial contributions to conception and design, acquisition of data, or analysis and interpretation of data. CY conceived and designed the study. ZH, YF, XC, YY, YH, and HY acquired data and analyzed data. The preliminary draft of the manuscript was prepared by HZ, YF, XC, and YY. All authors gave their approval for the final version of the manuscript.

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Correspondence to Chuanzhong Yang.

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The authors declare no competing interests.

Ethics approval and consent to participate

This study was reviewed by the hospital’s ethics committee (no. SFYLS2019119). Informed consent was provided by each child’s immediate family or guardian before the examination. The study was approved by the Ethics Committee of the Shenzhen Maternity & Child Healthcare Hospital. Oral and written informed consent was obtained from the parents.

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Zong, H., Huang, Z., Fu, Y. et al. Lung ultrasound score as a tool to predict severity of bronchopulmonary dysplasia in neonates born ≤25 weeks of gestational age. J Perinatol 44, 273–279 (2024). https://doi.org/10.1038/s41372-023-01811-4

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