Predictive factors for hemodynamically significant patent ductus arteriosus in preterm infants and the construction of a nomogram prediction model.
10.7499/j.issn.1008-8830.2407143
- Author:
Jun MU
1
;
Shu-Shu LI
1
;
Ai-Ling SU
1
;
Shu-Ping HAN
1
;
Jin-Gai ZHU
1
Author Information
1. Department of Neonatology, Women's Hospital of Nanjing Medical University/Nanjing Women and Children's Healthcare Hospital, Nanjing 210004, China.
- Publication Type:Journal Article
- Keywords:
Hemodynamically significant patent ductus arteriosus;
Nomogram model;
Predictive factor;
Preterm infant
- MeSH:
Humans;
Ductus Arteriosus, Patent/etiology*;
Nomograms;
Female;
Infant, Newborn;
Infant, Premature;
Retrospective Studies;
Male;
Hemodynamics;
Logistic Models;
Pregnancy
- From:
Chinese Journal of Contemporary Pediatrics
2025;27(3):279-285
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVES:To explore the predictive factors for hemodynamically significant patent ductus arteriosus (hsPDA) in preterm infants and to construct a nomogram prediction model for hsPDA occurrence in this population.
METHODS:A retrospective analysis was conducted on the clinical data of preterm infants with gestational age <32 weeks diagnosed with patent ductus arteriosus (PDA) who were delivered at Nanjing Women and Children's Healthcare Hospital from January 2020 to December 2022. The subjects were divided into an hsPDA group (52 cases) and a non-hsPDA group (176 cases) based on the presence of hsPDA. Univariate analysis and multivariate logistic regression analysis were performed to screen predictive variables regarding the general information of the infants at birth, maternal pregnancy and delivery conditions, and relevant indicators during hospitalization. A nomogram prediction model for hsPDA occurrence was constructed using R software in preterm infants. Internal validation was performed using the Bootstrap method. Finally, the predictive model was evaluated for calibration, discrimination ability, and clinical utility.
RESULTS:Multivariate regression analysis showed that the ratio of the left atrium to aorta diameter (LA/AO), mode of delivery (vaginal), and duration of mechanical ventilation were independent predictive factors for hsPDA in preterm infants (P<0.05). Based on the results of univariate analysis and multivariate logistic regression analysis, variables used to construct the nomogram prediction model for hsPDA risk included: LA/AO ratio, mode of delivery (vaginal), duration of mechanical ventilation, 5-minute Apgar score, and the presence of neonatal respiratory distress syndrome requiring surfactant therapy. The area under the receiver operating characteristic curve for this model was 0.876 (95%CI: 0.824-0.927), and the calibrated curve was close to the ideal reference line, indicating good calibration. The Hosmer-Lemeshow test demonstrated that the model fit well, and the clinical decision curve was above the extreme curves.
CONCLUSIONS:The nomogram prediction model, constructed using five variables (LA/AO ratio, vaginal delivery, duration of mechanical ventilation, 5-minute Apgar score, and the presence of neonatal respiratory distress syndrome requiring surfactant therapy), has reference significance for predicting the occurrence of hsPDA in preterm infants and provides valuable guidance for the early clinical identification of hsPDA.
