A prediction nomogram for neonatal acute respiratory distress syndrome in late-preterm infants and full-term infants: A retrospective study. (August 2022)

• Record Type: Journal Article
• Authors: Liu, Hui; Li, Jing; Guo, Jingyu; Shi, Yuan; Wang, Li
• Is Part Of: EClinicalMedicine. Volume 50(2022)
• Publication Date: 2022-08
• Subjects: Neonatal acute respiratory distress syndrome -- Late-preterm infants -- Full-term infants -- Prediction nomogram; Medicine -- Research -- Periodicals; Medical policy -- Periodicals; Clinical Medicine; Health Policy; Public Health; Medical policy; Medicine -- Research; Periodical; Electronic journals; Periodicals; 613
• DOI: 10.1016/j.eclinm.2022.101523
• Languages: English
• ISSNs: 2589-5370

Abstract

Summary: Background: Neonatal 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. Methods: A 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. Findings: Multivariate 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. Interpretation: A 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. Funding: No funding was associated with this study.