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Factors Associated with Increased Risk of Early Severe Neonatal Morbidity in Late Preterm and Early Term Infants.

ABSTRACT: Although the risk of neonatal mortality is generally low for late preterm and early term infants, they are still significantly predisposed to severe neonatal morbidity (SNM) despite being born at relatively advanced gestations. In this study, we investigated maternal and intrapartum risk factors for early SNM in late preterm and early term infants. This was a retrospective cohort study of non-anomalous, singleton infants (34⁺⁰-38⁺⁶ gestational weeks) born at the Mater Mother's Hospital in Brisbane, Australia from January 2015 to May 2020. Early SNM was defined as a composite of any of the following severe neonatal outcome indicators: admission to neonatal intensive care unit (NICU) in conjunction with an Apgar score <4 at 5 min, severe respiratory distress, severe neonatal acidosis (cord pH < 7.0 or base excess <-12 mmol/L). Multivariable binomial logistic regression analyses using generalized estimating equations (GEE) were used to identify risk factors. Of the total infants born at 34⁺⁰-38⁺⁶ gestational weeks, 5.7% had at least one component of the composite outcome. For late preterm infants, pre-existing diabetes mellitus, instrumental birth and emergency caesarean birth for non-reassuring fetal status were associated with increased odds for early SNM, whilst for early term infants, pre-existing and gestational diabetes mellitus, antepartum hemorrhage, instrumental, emergency caesarean and elective caesarean birth were significant risk factors. In conclusion, we identified several risk factors contributing to early SNM in late preterm and early term cohort. Our results suggest that predicted probability of early SNM decreased as gestation increased.

SUBMITTER: Mengistu TS

PROVIDER: S-EPMC8004864 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundNeonatal acute respiratory distress syndrome (ARDS) is a critical clinical disease with high disability and mortality rates. Early identification and treatment of neonatal ARDS is critical. This study aimed to build a perinatal prediction nomogram for early prediction of neonatal ARDS.MethodsA prediction model was built including 243 late-preterm and full-term infants from Daping Hospital in Chongqing, China, hospitalised between Jan 1, 2018 and Dec 31, 2019. 80 patients from the Children's Hospital in Chongqing, China, hospitalised between Jan 1, 2018 and June 30, 2018 were considered for external validation. Multivariate logistic regression was performed to identify independent predictors and establish a nomogram to predict the occurrence of neonatal ARDS. Both discrimination and calibration were assessed by bootstrapping with 1000 resamples.FindingsMultivariate logistic regression demonstrated that mother's education level (odds ratio [OR] 0·478, 95% confidence interval [CI] 0·324-0·704), premature rupture of membrane (OR 0·296, 95% CI 0·133-0·655), infectious disease within 7 days before delivery (OR 0·275, 95% CI 0·083-0·909), hospital level (OR 2·479, 95% CI 1·260-4·877), and Apgar 5-min score (OR 0·717, 95% CI 0·563-0·913) were independent predictors for neonatal ARDS in late-preterm and full-term infants, who experienced dyspnoea within 24 h after birth and required mechanical ventilation. The area under the curve and concordance index of the nomogram constructed from the above five factors were 0·760 and 0·757, respectively. The Hosmer-Lemeshow test showed that the model was a good fit (P = 0.320). The calibration curve of the nomogram was close to the ideal diagonal line. Furthermore, the decision curve analysis demonstrated significantly better net benefit in the model. The external validation proved the reliability of the prediction nomogram.InterpretationA nomogram based on perinatal factors was developed to predict the occurrence of neonatal ARDS in late-preterm and full-term infants who experienced dyspnoea within 24 h after birth and required mechanical ventilation. It provided clinicians with an accurate and effective tool for the early prediction and timely management of neonatal ARDS.FundingNo funding was associated with this study.

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Factors Associated with Increased Risk of Early Severe Neonatal Morbidity in Late Preterm and Early Term Infants.

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