References
1. Reuter, S., Moser, C. & Baack, M. Respiratory Distress in the
Newborn. Pediatr Rev 35 , 417–429 (2014).
2. Yadav, S., Lee, B. & Kamity, R. Neonatal Respiratory Distress
Syndrome . (2023).
3. Jensen, E. A. Prevention of Bronchopulmonary Dysplasia: A Summary of
Evidence-Based Strategies. Neoreviews 20 , e189–e201
(2019).
4. Stoll, B. J. et al. Trends in Care Practices, Morbidity, and
Mortality of Extremely Preterm Neonates, 1993-2012. JAMA 314 , 1039–51 (2015).
5. Wright, C. J., Sherlock, L. G., Sahni, R. & Polin, R. A. Preventing
Continuous Positive Airway Pressure Failure: Evidence-Based and
Physiologically Sound Practices from Delivery Room to the Neonatal
Intensive Care Unit. Clin Perinatol 45 , 257–271 (2018).
6. Dunn, M. S. et al. Randomized Trial Comparing 3 Approaches to
the Initial Respiratory Management of Preterm Neonates.Pediatrics 128 , e1069–e1076 (2011).
7. Morley, C. J. et al. Nasal CPAP or Intubation at Birth for
Very Preterm Infants. New England Journal of Medicine 358 , 700–708 (2008).
8. SUPPORT Study Group of the Eunice Kennedy Shriver NICHD Neonatal
Research Network et al. Early CPAP versus surfactant in extremely
preterm infants. N Engl J Med 362 , 1970–9 (2010).
9. Avery, M. E. et al. Is Chronic Lung Disease in Low Birth
Weight Infants Preventable? A Survey of Eight Centers. Pediatrics 79 , 26–30 (1987).
10. Gulczyńska, E., Szczapa, T., Hożejowski, R., Borszewska-Kornacka, M.
K. & Rutkowska, M. Fraction of Inspired Oxygen as a Predictor of CPAP
Failure in Preterm Infants with Respiratory Distress Syndrome: A
Prospective Multicenter Study. Neonatology 116 , 171–178
(2019).
11. Abdallah, Y. et al. CPAP failure in the management of preterm
neonates with respiratory distress syndrome where surfactant is scarce.
A prospective observational study. BMC Pediatr 23 , 211
(2023).
12. De Jaegere, A. P., van der Lee, J. H., Canté, C. & van Kaam, A. H.
Early prediction of nasal continuous positive airway pressure failure in
preterm infants less than 30 weeks gestation. Acta Paediatr 101 , 374–379 (2012).
13. Dargaville, P. A. et al. Continuous Positive Airway Pressure
Failure in Preterm Infants: Incidence, Predictors and Consequences.Neonatology 104 , 8–14 (2013).
14. Ehwerhemuepha, L. et al. Cerner real-world data (CRWD) - A
de-identified multicenter electronic health records database. Data
Brief 42 , 108120 (2022).
15. Ehwerhemuepha, L. et al. HealtheDataLab - a cloud computing
solution for data science and advanced analytics in healthcare with
application to predicting multi-center pediatric readmissions. BMC
Med Inform Decis Mak 20 , 115 (2020).
16. Chen, T., He, T. & Benesty, M. Xgboost: extreme gradient boosting.R package version 0.4-3 1–4 (2015).
17. Chen, T. et al. xgboost: Extreme Gradient Boosting. Preprint
at (2019).
18. Dargaville, P. A. et al. Incidence and Outcome of CPAP
Failure in Preterm Infants. Pediatrics 138 , (2016).
19. Kakkilaya, V. et al. Early predictors of continuous positive
airway pressure failure in preterm neonates. Journal of
Perinatology 39 , 1081–1088 (2019).
20. Dargaville, P. A. et al. Continuous Positive Airway Pressure
Failure in Preterm Infants: Incidence, Predictors and Consequences.Neonatology 104 , 8–14 (2013).
21. Rocha, G. et al. Failure of early nasal continuous positive
airway pressure in preterm infants of 26 to 30 weeks gestation.Journal of Perinatology 33 , 297–301 (2013).
22. Fuchs, H., Lindner, W., Leiprecht, A., Mendler, M. R. & Hummler, H.
D. Predictors of early nasal CPAP failure and effects of various
intubation criteria on the rate of mechanical ventilation in preterm
infants of <29 weeks gestational age. Arch Dis Child Fetal
Neonatal Ed 96 , F343-7 (2011).
23. De Jaegere, A. P., van der Lee, J. H., Canté, C. & van Kaam, A. H.
Early prediction of nasal continuous positive airway pressure failure in
preterm infants less than 30 weeks gestation. Acta Paediatr 101 , 374–379 (2012).
24. Ammari, A. et al. Variables Associated with the Early Failure
of Nasal CPAP in Very Low Birth Weight Infants. J Pediatr 147 , 341–347 (2005).
25. Sidey-Gibbons, J. A. M. & Sidey-Gibbons, C. J. Machine learning in
medicine: a practical introduction. BMC Med Res Methodol 19 , 64 (2019).
Funding Support Statement
This work was supported by Chiesi Farmaceutici S.p.A.
Competing Interests
The authors declare no competing interests.
Ethics Approval and Consent to Participate
No patient consent was applicable for this paper.
Main Figure Legend