Personalized lung care: “Bronchopulmonary Dysplasia Risk Prediction
Tool Tailored for Neonates Born in the Resource-limited Settings.”
Abstract
Purpose: Predicting Bronchopulmonary dysplasia (BPD) to assess
the risk-benefit of the therapy is necessary due to the side effects of
medications. We developed and validated an instrument for predicting BDP
and compared it with an instrument currently used in neonates born in a
Brazilian hospital. Methods: Retrospective cohort of patients
born between 2016 and 2020, with gestational ages (GA) between 23 and 30
weeks. Predictive equations were elaborated using methods of selection
of component variables: stepwise, conditional inference tree, Fisher’s
exact test and all the collected variables; 70% of the sample was
randomly selected for the construction of risk prediction equations, and
the remaining 30% were used for their validation, application and
comparison with the National Institute of Child Health and Human
Development (NICHD) instrument published in 2011, currently used in that
institution. Sensitivity, specificity, and predictive values of the
equations were calculated. Results: The equation that used
variables whose p-value was lower than 5% in Fisher’s exact test
(clinical chorioamnionitis, GA, birth weight, sex, need for surfactant,
patent ductus arteriosus, late-onset sepsis, inspired fraction of
oxygen, and respiratory support) presented the best results: specificity
of 98% and positive predictive value of 93%. Our instrument allowed
applying the prediction to small-for-gestational-age (SGA). The
currently used calculator applied to our population had a specificity of
93% and a positive predictive value of 75% and could not be applied to
SGA patients. Conclusion: Our tool has a higher specificity and
positive predictive value than the foreign instrument and is suited for
SGA.