AUTHOR=Reis Zilma Silveira Nogueira , Pappa Gisele Lobo , Nader Paulo de Jesus H. , do Vale Marynea Silva , Silveira Neves Gabriela , Vitral Gabriela Luiza Nogueira , Mussagy Nilza , Norberto Dias Ivana Mara , Romanelli Roberta Maia de Castro 

TITLE=Respiratory distress syndrome prediction at birth by optical skin maturity assessment and machine learning models for limited-resource settings: a development and validation study

JOURNAL=Frontiers in Pediatrics

VOLUME=Volume 11 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/pediatrics/articles/10.3389/fped.2023.1264527

DOI=10.3389/fped.2023.1264527

ISSN=2296-2360

ABSTRACT=Background: A handheld optical device was developed to evaluate the newborn's skin maturity by assessing the photobiological properties of the tissue and processing it with other variables to predict early neonatal prognosis related to prematurity. This study assessed the device ability to predict respiratory distress syndrome (RDS).: To assess the device utility enrolled newborns at childbirth in six urban perinatal centers from two multicenter single-blinded clinical trials. All newborns had inpatient follow-up until 72 hours of life. We trained supervised machine learning models in 780 newborns in a Brazilian trial and provided external validation in 305 low-birth-weight newborns from another trial that assessed Brazilian and Mozambican newborns. The index test measured skin optical reflection with an optical sensor and adjusted acquired values with clinical variables such as birth weight and prenatal corticoid exposition for lung maturity, maternal diabetes, and hypertensive disturbances. The performance of the models was evaluated using intrasample k-parts cross-validation and external validation in an independent sample.Results: Models adjusting three predictors (skin reflection, birth weight, and antenatal corticoids exposition) or five predictors had a similar performance, including or not maternal diabetes diseases. The best global accuracy was 89.7 (95% CI: 87.4 to 91.8, with a high sensitivity of 85.6% (80.2 to 90.0) and specificity of 91.3% (95%CI: 88.7 to 93.5). The test correctly discriminated RDS newborns in external validation, with 82.3% (95%CI: 77.5 to 86.4) accuracy. Our findings paved new tracks to assess the newborn's lung maturity, providing potential opportunities for earlier and effective care.Trial registration: RBR-3f5bm5, and ReBec: RBR-33rnjf, accessible at: http://www.ensaiosclinicos.gov.br/rg/RBR-33rnjf/.