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.
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